to my mother, father, and sister - camfil · particulate fouling of hvac heat exchangers by jeffrey...

Particulate Fouling of HVAC Heat Exchangers

by

Jeffrey Alexander Siegel

B.S. (Swarthmore College) 1995 M.S. (University of California, Berkeley) 1999

A dissertation submitted in partial satisfaction of the

requirements for the degree of

Doctor of Philosophy in

Engineering – Mechanical Engineering

in the

GRADUATE DIVISION

of the

UNIVERSITY OF CALIFORNIA, BERKELEY

Committee in charge:

Professor Van P. Carey, Chair Professor Ralph Greif

Professor William W. Nazaroff

Fall 2002

i

To my mother, father, and sister

ii

TABLE OF CONTENTS

LIST OF FIGURES ...................................................................................................vi

LIST OF TABLES.....................................................................................................ix

NOMENCLATURE ..................................................................................................xi

ACKNOWLEDGEMENTS.......................................................................................xv

CHAPTER 1: PARTICULATE FOULING OF HVAC HEAT EXCHANGERS ....1

1.1 Introduction........................................................................................1

1.2 Review of Published Fouling Models................................................3

1.3 Scope of Dissertation Research .........................................................6

1.4 Important Non-dimensional Parameters ............................................8

1.5 Outline of Dissertation.......................................................................11

CHAPTER 2: MODELING PARTICLE DEPOSITION ON HVAC HEAT EXCHANGERS.........................................................................................................13

2.1 Introduction........................................................................................13

2.1.1 Fin-and-tube heat exchangers ................................................14

2.2 Previous Studies.................................................................................15

2.3 Preliminary Deposition Modeling using CFD ...................................17

2.4 Modeling the Mechanisms of Particle Deposition on HVAC Heat Exchangers.........................................................................................19

2.4.1 Deposition on leading edge of fins ........................................20

2.4.2 Impaction on refrigerant tubes ...............................................23

2.4.3 Gravitational settling on fin corrugations ..............................25

2.4.4 Deposition by air turbulence in fin channels .........................27

2.4.5 Deposition by Brownian diffusion.........................................31

2.4.6 Combining deposition mechanisms .......................................32

iii

2.4.7 Particle deposition mechanisms not considered ....................33

2.4.8 Particle reflection ...................................................................34

2.5 Non-isothermal Deposition Processes ...............................................36

2.5.1 Thermophoresis to fin walls...................................................36

2.5.2 Thermophoretic deposition on tubes......................................38

2.5.3 Diffusiophoresis to fin walls..................................................39

2.5.4 Presence of condensed water .................................................41

2.6 Modeling Parameters .........................................................................41

2.7 Modeling Results ...............................................................................43

2.7.1 Isothermal conditions.............................................................44

2.7.2 Non-isothermal conditions.....................................................54

2.7.3 Comparison with Muyshondt et al. (1998) ............................57

2.8 Conclusions and Implications of Model Results ...............................60

CHAPTER 3: MEASURING PARTICLE DEPOSITION ON HVAC HEAT EXCHANGERS.........................................................................................................62

3.1 Introduction........................................................................................62


3.3 Experimental Methods .......................................................................64

3.3.1 Measuring particle deposition fraction ..................................65

3.3.2 Measuring deposition fraction in a non-isothermal system ...75

3.3.3 Methods for experiment to determine fouling to pressure-drop relationship ...................................................................79

3.3.4 Measurement devices, sensors, and uncertainty ....................82

3.4 Experimentally Tested Parameters ....................................................84

3.5 Analysis..............................................................................................85

iv

3.5.1 Deposition fraction (both isothermal and non-isothermal)....85

3.5.2 Non-isothermal experiments..................................................86

3.5.3 Pressure drop experiments .....................................................87

3.6 Results ................................................................................................89

3.6.1 Isothermal deposition fraction ...............................................89

3.6.2 Non-isothermal deposition fractions......................................93

3.6.3 Dust deposition experiment ...................................................96

3.7 Discussion and Implications of Experimental Results.......................99

CHAPTER 4: BIOAEROSOL DEPOSITION ON HVAC HEAT EXCHANGERS AND IMPLICATIONS FOR INDOOR AIR QUALITY..........................................104

4.1 Introduction........................................................................................104

4.2 Bioaerosols of concern.......................................................................105

4.2.1 Fungi ......................................................................................106

4.2.2 Bacteria ..................................................................................108

4.3 Bioaerosol Deposition on Heat Exchangers ......................................111

4.4 Viability and Spread of Deposited Bioaerosols .................................114

4.5 Discussion..........................................................................................118

CHAPTER 5: FOULING TIMES AND ENERGY IMPLICATIONS OF HVAC HEAT EXCHANGER FOULING.............................................................................122

5.1 Introduction........................................................................................122


5.3 Estimation of Fouling Times and Energy Impacts ............................126

5.3.1 Residential systems................................................................126

5.3.2 Commercial systems ..............................................................147

5.4 Analysis Results.................................................................................150


v

5.4.2 Commercial systems .............................................................156

5.5 Discussion..........................................................................................158


5.5.2 Commercial systems ..............................................................160

5.6 Conclusions........................................................................................161

CHAPTER 6: CONCLUSIONS ................................................................................164

REFERENCES ..........................................................................................................169

APPENDIX A: EXPERIMENTAL PROTOCOLS...................................................179

APPENDIX B: TABULATED EXPERIMENTAL RESULTS................................193

APPENDIX C: MICROSCOPY OF MATERIAL ON FOULED COILS ................196

APPENDIX D: INDOOR PARTICLE NUMBER CONCENTRATION DISTRIBUTION FUNCTIONS ................................................................................199

vi

LIST OF FIGURES

Figure 1.1: Asymptotic fouling (modified from Bott, 1995) ...............................4

Figure 1.2: Analysis and experimental plan .........................................................12

Figure 2.1: Front view of leading edge of fins (left) and side view of heat exchanger and refrigerant tubes (right)..............................................14

Figure 2.2: Unrefined mesh from computational fluid dynamics simulation ......18

Figure 2.3: Top view of fin channel showing particle trajectory because of air turbulence...........................................................................................27

Figure 2.4: Critical velocity for onset of particle bounce (Cheng and Yeh, 1979) ..................................................................................................35

Figure 2.5: Deposition as a function of velocity for fin spacing = 4.7 fin/cm .....45

Figure 2.6: Deposition as a function of fin spacing for U = 2 m/s .......................45

Figure 2.7: Impaction deposition on fin edges as a function of velocity for fin spacing = 4.7 fin/cm...........................................................................46

Figure 2.8: Impaction deposition on fin edges as a function of fin spacing for U = 2 m/s............................................................................................47

Figure 2.9: Gravitational, tube impaction, and turbulent penetration fractions for U = 1 m/s and fin spacing = 4.7 fin/cm........................................48

Figure 2.10: Gravitational, tube impaction, and turbulent penetration fractions for U = 4 m/s and fin spacing = 4.7 fin/cm........................................48

Figure 2.11: Gravitational, tube impaction, and turbulent penetration fractions as a function of fin spacing for 2.4 fin/cm and U = 2 m/s .................49

Figure 2.12: Gravitational, tube impaction, and turbulent penetration fractions as a function of fin spacing for 7.1 fin/cm and U = 2 m/s .................50

Figure 2.13: Uncertainty for fin impaction for U = 2 m/s and fin spacing = 4.7 fin/cm .................................................................................................51

Figure 2.14: Uncertainty for tube impaction for U = 2 m/s and fin spacing = 4.7 fin/cm .................................................................................................51

Figure 2.15: Uncertainty for gravitational settling for U = 2 m/s and fin spacing = 4.7 fin/cm........................................................................................52

vii

Figure 2.16: Uncertainty in air turbulence impaction for U = 2 m/s and fin spacing = 4.7 fin/cm...........................................................................53

Figure 2.17: Overall uncertainty bounds for U = 2 m/s and fin spacing = 4.7 fin/cm .................................................................................................54

Figure 2.18: Comparison of deposition on isothermal coil, cooled coil, and cooled-and-condensing coil for U = 2 m/s and fin spacing = 4.7 fin/cm .................................................................................................55

Figure 2.19: Penetration by thermophoresis as a function of θ for U = 2 m/s and fin spacing = 4.7 fin/cm .....................................................................56

Figure 2.20: Comparison of present model and the work of Muyshondt et al. (1998) as a function of fin spacing for U = 1.5 m/s...........................59

Figure 3.1: Schematic of experimental apparatus ................................................65

Figure 3.2: Cross section of duct showing measurement points for pitot tube air velocity measurement ...................................................................69

Figure 3.3: Sampling locations immediately upstream of duct ............................73

Figure 3.4: Schematic of measurements and sensor locations for cooled and cooled-and-condensing coil experiments...........................................76

Figure 3.5: SAE coarse dust fractional mass distribution function ......................80

Figure 3.6: Apparatus for dust experiment...........................................................81

Figure 3.7: Modeled and measured deposition for 1.5 m/s air velocity ...............90



Figure 3.10: Non-isothermal deposition fraction for 1.5 m/s air velocity..............94

Figure 3.11: Normalized mass deposited vs. relative pressure drop for 2.0 m/s air velocity .........................................................................................97

Figure 3.12: Top view of idealized (left) and real (right) fin channels ..................101

Figure 4.1: Deposition fractions for air velocity of 1.5 m/s and fin spacing of 4.7 fin/cm ...........................................................................................113

viii

Figure 5.1: Duct penetration fractions vs. particle size for residential duct systems described in Table 5.1 ..........................................................129

Figure 5.2: Filter efficiency curves for parametric analysis.................................130

Figure 5.3: Filter Efficiency curves for spun fiberglass furnace filter from Hanley and Smith (1993) for U = 1.8 m/s .........................................131

Figure 5.4: Filter Efficiency curves for spun fiberglass furnace filter from Hanley et al. (1994) for U = 1.3 m/s..................................................132

Figure 5.5: Coil deposition fractions as a function of fin spacing for U = 2 m/s .133

Figure 5.6: Wet coil deposition fractions as a function of fin spacing for U = 2 m/s......................................................................................................134

Figure 5.7: Fan curve and system curves for clean and fouled coil .....................143

Figure 5.8: Fan curves used to determine flow ....................................................144

Figure 5.9: Performance degradation from reduced flow from Parker et al. (1997).................................................................................................145

Figure 5.10: Performance degradation from reduced flow from Palani et al. (1992) ................................................................................................146

Figure 5.11: Fouling time ratios (relative to Base Case)........................................152

Figure C.1: Optical Microscopy on Coil 1. .........................................................196

Figure C.2: SEM image from Coil 2.....................................................................197

Figure D.1: Urban submicron indoor air particle number concentration distributions........................................................................................199

Figure D.2: Urban supermicron particle indoor air number concentration distributions........................................................................................200

Figure D.3: Rural submicron indoor air particle number concentration distributions........................................................................................201

Figure D.4: Rural supermicron indoor air particle number concentration distributions........................................................................................202

ix

LIST OF TABLES

Table 1.1: Reynolds numbers and ranges for HVAC heat exchangers...............9

Table 1.2: Non dimensional parameters that govern particle behavior in HVAC heat exchangers......................................................................11

Table 2.1: Summary of approaches used to estimate model uncertainty............33

Table 2.2: Velocities considered in simulations .................................................42

Table 2.3: Geometric parameters for this study and for Muyshondt et al. (1998) ................................................................................................43

Table 2.4: Diffusiophoretic penetration as a function of air relative humidity, φ , for θ = 0.92, U = 2 m/s and fin spacing = 4.7 fin/cm....................57

Table 3.1: Test heat exchanger geometric parameters ........................................70

Table 3.2: Summary of particle sampling locations............................................73

Table 3.3: Summary of temperature and relative humidity measurement locations .............................................................................................79

Table 3.4: Measurements, sensors, and uncertainty............................................83

Table 3.5: Temperature conditions for non-isothermal experiments ..................94

Table 3.6: Moisture volumes for non-isothermal experiments ...........................95

Table 3.7: Modeled and measured deposition fractions for cooled-and-condensing experiments.....................................................................96

Table 3.8: Mass balance calculations..................................................................98

Table 4.1: Fungal species in different parts of HVAC systems..........................108

Table 4.2: Bacterial species in different parts of HVAC systems.......................110

Table 5.1: Residential duct systems for parametric analysis ..............................128

x

Table 5.2: Parameters varied in the simulation of mass deposition....................141

Table 5.3: Commercial HVAC fans....................................................................149

Table 5.4: Fouling time ratios .............................................................................151

Table 5.5: Contribution to mass deposited by particle size ................................154

Table 5.6: Flow reduction and pressure drop for different fan curves................155

Table 5.7: Fan power for clean and fouled coils.................................................156

Table 5.8: Commercial building fan power increase (W) based on fan type and flow and pressure conditions.......................................................157

Table B.1: Data from isothermal and non-isothermal deposition fraction experiments ........................................................................................193

Table B.2: Leading edge fraction for isothermal experiments ............................194

Table B.3: Data from pressure drop experiment..................................................195

Table C.1: Fiber diameter and lengths from two residential coils.......................198

xi

NOMENCLATURE Aduct duct cross sectional area Afin fin surface area Atube tube outer surface area Anozzle sampling nozzle entry area bf filter bypass bc coil bypass cf corrugation factor c8-c18 psychrometric coefficients from ASHRAE (2001) Cair,down downstream air concentration Cair,up upstream air concentration Cb,filter concentration of fluorescein extracted from filter Cb,holder concentration of fluorescein extracted from filter holder Cb,nozzle concentration of fluorescein extracted from nozzle Cc Cunningham slip correction factor CD coefficient of drag Cin indoor particle concentration Cm coefficient of momentum slip = 1.14 Cout outdoor particle concentration Cs coefficient of slip = 1.14 Ct coefficient of thermal slip = 2.18 da particle aerodynamic diameter dd droplet diameter dnozz nozzle diameter dp particle diameter dtube tube diameter D Brownian diffusion coefficient D12 diffusivity of water in air DC duty cycle of the air handler fan e coefficient of restitution f friction factor, frequency (of VOAG) fIPA fraction of isopropyl alcohol in particle solution g acceleration due to gravity = 9.8 m/s2

h average height of fin corrugations Tfl Lagrangian integral scale of time k Boltzmann constant = 1.38x10-23

J/K kg thermal conductivity of the gas kp thermal conductivity of the particle Kn particle Knudsen number m mass of deposit per unit area M mass of dust on coil for each insertion Mc mass concentration that deposits on coil Mcoil mass of fluorescein or test dust on heat exchanger Mduct,up mass of dust on the floor of the duct upstream Mduct,down mass of dust on the floor of the duct downstream

xii

Mf loaded filter mass Mf,0 clean filter mass Mfilter,up mass of dust collected on the upstream sampling filters Mfoul deposited mass that doubles heat exchanger pressure drop Minsert total mass of dust put into the system Mmound mass of dust that fell directly to the floor of the duct underneath the sifter Msifter mass of dust that remained in the sifter after each dust insertion n fouling exponent nm,in indoor particle size mass distribution function nrow number of rows of tubes in direction of flow nset number of sets of offset tube rows noffset number of offset tube rows per set p penetration fraction through cracks in the building envelope p1 partial pressure of water p2 partial pressure of gas P velocity pressure Pduct,r penetration through the return duct system Pduct,s penetration through the supply duct system PD penetration by Brownian diffusion Pdf penetration by diffusiophoresis PG penetration by gravitational settling Pfin penetration by fin impaction PH2O partial pressure of water vapor PH2O, sat saturated partial pressure of water vapor Ptube penetration by tube impaction PT penetration by air turbulence impaction PTh penetration by thermophoresis Pr Prandtl number Q air flow rate through the HVAC system Qcondensate volumetric flow of condensate QL VOAG liquid flow rate Qs air sampling flow rate Qs,iso isokinetic sampling flow rate Rep particle Reynolds number Retube tube Reynolds number Rf fouling resistance Rf∞ asymptotic fouling resistance St Stanton number Stkeff,fin particle effective Stokes number based on t Stketf,tube particle effective Stokes number based on dtube Stknozz particle Stokes number based on dnozz t time, experimental duration tfin fin thickness T average air temperature Tdown average downstream air temperature Tdp air dew point temperature

xiii

Tup average upstream air temperature Twall heat exchanger temperature u air velocity in bulk flow direction ufin bulk air velocity in fin channels u’ turbulent fluctuating air velocity in bulk flow direction up particle velocity in bulk flow direction up’ turbulent fluctuating particle velocity in bulk flow direction U air bulk velocity, instantaneous velocity Up instantaneous particle velocity v air velocity in vertical direction vc critical velocity for onset of particle bounce vi impact velocity vp particle velocity in vertical direction vr reflection velocity Vb,filter volume of buffer used to extract filter Vb,holder volume of buffer used to extract filter holder Vb,nozzle volume of buffer used to extract nozzle Vcondensate volume of condensate VH2O volume of condensed water on the coil Vs particle settling velocity w center-to-center fin spacing, wall normal air velocity (Muyshondt et al., 1988) w’ turbulent fluctuating component of air velocity in wall normal direction wp particle velocity in wall-normal direction wp’ turbulent fluctuating component of particle velocity in wall normal direction wtube center-to-center tube spacing in vertical direction WDf overall diffusiophoretic velocity WDf’ diffusiophoretic velocity WSf Stefan flow velocity Wup humidity ratio upstream of the duct Wdown humidity ratio downstream of the duct y peak to trough width of fin corrugations yT particle entering location z heat exchanger depth in direction of flow ztube center-to-center tube spacing in direction of flow β particle deposition loss rate to building surfaces, fouling constant, coefficient

in Equation (2.22) ∆ turbulent thermal boundary layer thickness ∆P pressure drop of fouled coil ∆P external static pressure drop of the system ∆Pinitial pressure drop of cleaned coil ∆P/z pressure drop per unit length of the duct є eddy viscosity φ air relative humidity φD deposition flux to heat exchanger surface φR removal flux from heat exchanger surface

xiv

γ1 mole fraction of water vapor γ2 mole fraction of dry air η deposition fraction ηasp aspiration efficiency ηc coil deposition fraction ηf filter efficiency ηfan fan efficiency ηmotor fan motor efficiency ηr HVAC filter efficiency (from Riley et al., 2000) κ thermophoretic coefficient λ air mean free path λi

envelope infiltration rate λr HVAC air exchange rate, µ air dynamic viscosity ν air kinematic viscosity θ temperature ratio ρ* unit density = 1 g/cm3 ρair air density ρp particle density τ shear stress τw wall shear stress τimp characteristic time for a particle impaction by air turbulence τp particle relaxation time

xv

ACKNOWLEDGEMENTS

I would like to acknowledge the contributions of my advisors: Van Carey, Bill

Nazaroff, and Ralph Greif. Their comments and guidance were crucial in shaping and

improving this dissertation. Van Carey and Bill Nazaroff guided me throughout my

graduate school career and Bill Nazaroff’s extensive comments on a draft of this

dissertation were particularly helpful. Iain Walker and Max Sherman at Lawrence

Berkeley National Laboratory were instrumental in obtaining funding and guiding this

project. John Proctor made many valuable suggestions over the course of this work,

Mark Sippola and De-Ling Liu, my colleagues in the Department of Environmental

Engineering, contributed to this work by reviewing papers, sharing information about

equipment, and assisting with the issues that arose in conducting the experiments.

Fabienne Boulieu from INSA Lyon assisted with data collection. Shana Bernstein and

Laura Siegel edited portions of this document and found many errors – the errors that

remain are mine, not theirs. Adam Lewinberg and Anna Greenberg, among many others,

contributed moral support over the years of dissertation research and writing.

Much of the work in this dissertation was sponsored by the California Institute for

Energy Efficiency (CIEE), a research unit of the University of California (Award No.

BG-90-73). Publication of research results does not imply CIEE endorsement of or

agreement with these findings, nor that of any CIEE sponsor. Support was also provided

by the Office of Research and Development, Office of Nonproliferation and National

Security, and the Office of Building Technology, State, and Community Programs,

Office of Building Research and Standards, US Department of Energy under contract

DE-AC03-76SF00098.

1

CHAPTER 1: PARTICULATE FOULING OF HVAC HEAT EXCHANGERS

1.1 Introduction

Heat exchangers are a significant part of many industrial processes that involve

energy exchange. Most of these heat exchangers become fouled with use. The United

Engineering Foundation, which hosts a conference every three years on the fouling

problem, estimates that the cost of heat exchanger fouling is 0.4 % of global Gross

Domestic Product (UEF, 2001). This high cost has lead to frequent study of the fouling

problem, including numerous books and conferences on the subject (Somerscales and

Knudsen, 1981; Melo et al., 1988; Bott, 1995). Much of this work has focused on

particular industries. Crude oil processing, dairy and food processing, and nuclear

reactor cooling are all industries that have conducted a large amount of research aimed at

understanding and mitigating fouling.

One of the most common uses of heat exchangers is the heating and cooling of

buildings. There are 107 - 109 heat exchangers installed in heating, ventilating, and air

conditioning (HVAC) systems in buildings in the United States. Building energy use

represents about one third of total worldwide energy use. Of that total, about one third is

for heating and cooling (EIA, 2002). Heat exchangers are a central part of most heating

and cooling systems, thus even small fractional performance degradations owing to

fouling have the potential to cause large societal energy consequences. Furthermore,

many heat exchangers used in HVAC systems are directly in the indoor air stream. Any

material that deposits on these heat exchangers can react with other deposited or airborne

contaminants and produce odorous compounds. If the deposited material is biological in

2

nature, it can grow and contaminate other parts of the HVAC system and spread to indoor

spaces.

The heat exchangers used on the air side of most HVAC systems are extended

surfaces. They are typically a fin-and-tube configuration, which consist of tubes that

carry a refrigerant and fins that facilitate energy exchange between the refrigerant and the

air. Fin-and-tube heat exchangers consist of refrigerant tubes that run perpendicular (and

almost always horizontal) to the flow, and fins that run parallel (and almost always

vertical) to the direction of flow. The fins are often corrugated or have other extensions

from the surface to further promote energy exchange between the refrigerant and the air.

Important parameters in the design of fin-and-tube heat exchangers are the

number and spacing of tubes and the number of fins (usually expressed as a fin pitch, i.e.

the number of fins per unit length). Energy efficiency and performance requirements

often lead to higher fin pitches which increases the heat transfer between the refrigerant

and the air. Pressure drop considerations and cost limitations lead to lower fin pitches.

It is well known to technicians and designers that HVAC fin-and-tube heat

exchangers become fouled with use (RSC, 1987; Neal, 1992; Turpin, 2001). Common

contaminants include airborne particulate matter and dusts. Corrosion, both from

chemical reactions between deposited material on the (often moist) heat exchanger

surface, and from acidic air contaminants is also reported (Proctor, 1998b). Cleaning of

the heat exchangers, usually with strong acids, bases or detergents and mechanical

scrubbing with wire brushes, is a standard part of maintenance and commissioning

procedures (Turpin, 2001). Biological contamination issues are also well known:

textbooks typically recommend the use of biocide coatings or fungicide applications on

and around HVAC heat exchangers (Kuehn et al., 1998).

3

Despite the documented occurrence of fouling of HVAC heat exchangers by

particulate matter, there has been relatively little study of the way in which particles are

transported to and deposit on heat exchanger surfaces. There are studies that document

biological growth on heat exchanger surfaces (Hugenholtz and Fuerst, 1992; Morey,

1988) and others that examine the role of HVAC heat exchanger surfaces as sources and

sinks of contaminants (Muyshondt et al. 1998). Others have explored aspects of the

energy consequences of heat exchanger fouling (Krafthefter and Bonne, 1986;

Krafthefter et al., 1987). In summary, despite the importance of HVAC heat exchangers

and anecdotal and scientific evidence that they foul, there has been relatively little study

of the mechanisms and processes that cause fouling of these systems.

The goals of the research reported on here are to improve our understanding of the

processes and rates of fouling by airborne particulate matter and to predict the impacts of

fouling. The structure of this chapter is to review the relevant fouling literature, to

present a scope for this study, to describe non-dimensional parameters that are useful in

characterizing HVAC heat exchangers and particle deposition, and to outline this

research project and dissertation.

1.2 Review of Published Fouling Models

The most widespread general model for heat exchanger fouling is described by

Bott (1995). A summary of the predictions of this model appears in Figure 1.1. The

amount of deposited material initially remains small during the induction period because

adhesive forces are small until sufficient material deposits to condition the surface for

future deposition. The length of the induction period can vary greatly for different

systems (Bott, 1995). The steady growth of the layer occurs as surface conditions permit

a constant increase in fouling. Finally, the deposit layer reaches a maximum and

4

asymptotes. This asymptotic behavior, although not universal, is caused by a balance

between deposition and removal of the fouling agent. The y-axis in Figure 1.1 can also

be interpreted as the fouling heat transfer resistance or the friction factor for the heat

exchanger.

Time

Dep

osit

Thic

knes

s

Induction orInitiation

SteadyGrowth

Asymptotic Limit

Figure 1.1: Asymptotic fouling (modified from Bott, 1995).

The asymptotic model has been experimentally verified for numerous fouling

problems (Bott and Bemrose, 1983; Epstein, 1981). Mathematically, the generalized

fouling process can be described as (follows Bott, 1995):

dd D Rmt

φ φ= − (1.1)

Where m is the mass of deposit per unit area, φD is the deposition flux to the heat

exchanger surfaces, and φR is the removal flux of fouling agent from the surface.

Experiments need to be done for each system and flow condition to determine the

functional forms of φD and φR.

Kern and Seaton (1959) provided the first detailed functional form for asymptotic

fouling:

5

( )1 e tf fR ( t ) R β−

∞= − (1.2)

Where Rf is the heat transfer resistance of the fouled heat exchanger as a function

of time, Rf∞ is the asymptotic limit of fouling resistance and β is a constant that is

dependent on the system. Fouling resistances span a very large range. Some reported

values in the literature include 10-5 – 10-4 °C/W⋅m2 for a cooling water system (Merry

and Polley, 1981) and 10-3 – 10-2 °C/W⋅m2 (Bott, 1981) for paraffin in an industrial heat

exchanger. Mills (1992) tabulates design values for fouling resistances for a wide range

of fluids that range from 10-4 – 10-2 °C/W⋅m2.

The Kern and Seaton expression is by far the most common functional form for

asymptotic fouling and is still used for a wide variety of fluids and heat exchanger

geometries. Other functional forms for asymptotic fouling have been proposed, including

a driving force model (Konak, 1976):

( )dd

nff f

R ( t )K R R ( t )

t ∞= − (1.3)

Where K and n are constants (note that Equation (1.3) and Equation (1.2) are equal for n

= 1 and K = β). Epstein (1988) assumed a constant temperature difference between the

heat exchanger and the fluid and that the heat flux follows a power law relationship. He

proposed the following model:

( )

ddf

nf f

R ( t ) Kt R R ( t )∞

=−

(1.4)

The models proposed in Equations (1.2) - (1.4) are all useful for conceptualizing

fouling, but all require extensive testing at all possible system conditions to obtain the

correct functional form and values of the coefficients. Most fouling research consists of

experiments to determine these parameters for a particular system. Very little research

6

has been done to determine fouling resistances and their functional form for HVAC heat

exchangers.

Equations (1.2) - (1.4) all focus on an increased resistance to heat transfer caused

by fouling. Bott (1995) points out that the pressure drop increases that result from

fouling can also have a significant effect on heat exchanger performance. This is true for

HVAC heat exchangers and is discussed in more detail in Chapter 5.

1.3 Scope of Dissertation Research

There are many different kinds of heat exchangers used in HVAC systems. In

order to focus the investigation, the following limits are put on this investigation. In this

study, I am primary interested in particulate fouling of air-side indoor fin-and-tube heat

exchangers used for cooling. Corrosion fouling, in addition to particulate fouling, can

occur in HVAC heat exchangers, but is often related to a particular airborne chemical

contaminant (Proctor, 1998b) or is caused by the more extreme temperatures that occur

from the development of a thick fouling layer (Bott, 1995) . Although there are many

water-side heat exchangers in HVAC systems, the fouling that occurs in these liquid

systems is typically one of scaling and precipitation (Somerscales and Knudsen, 1981),

not particle deposition. Outdoor heat HVAC exchangers, which reject/absorb heat that

the refrigerant acquires/loses at the indoor heat exchangers, also foul, but the fouling

mechanism is of a different nature than considered here. Large scale debris, such as

leaves, and wind-blown soil, as well as algal growth in evaporative condensers and

cooling towers are typical fouling agents for outdoor HVAC heat exchangers (RSC,

1987; Neal, 1992). Other designs, such as unextended tube bundles (no fins), are used as

heat exchangers in some larger HVAC systems, but by far the most predominant type are

fin-and-tube. The focus on heat exchangers used for cooling is because the effects of

7

fouling are more severe than for heating. Air conditioning systems are more sensitive to

flow reduction (Palani et al., 1992; Parker et al., 1997; Proctor, 1998a) than heating heat

exchangers. Also, cooling heat exchangers (evaporators) serve to dehumidify the air

stream which provides bulk water for microbiological growth and can accelerate the rate

of fouling.

The focus on particulate fouling means that the range of particle diameters being

considered is crucially important, as particle size determines most particle properties.

Previous work on heat exchanger fouling has typically considered supermicron particles

as these particles are sufficiently large to cause a significant fouling layer when they

deposit (Bott and Bemrose, 1983; Muyshondt et al., 1998). However, submicron

particles exist at much higher concentrations in typical indoor environments, so this study

will consider particles as small as 0.01 µm in diameter. Particles in the size range of 0.01

to 1 µm exist in indoor environments as the result of combustion (including tobacco

smoke), penetration from outdoor sources, and gas-to-particle conversion processes

(Hinds, 1999). Particles in the range of 1 - 10 µm include some soil grains, certain

bioaerosols, and particles from cooking and other household activities. Very large

particles, with diameters from 10 – 100 µm, are those found in indoor dusts (Hinds,

1999). It is important to note that smaller particles (i.e. those with a characteristic

dimension of 10 nm or even smaller) do exist in indoor environments. However, because

mass goes with the cube of particle diameter (for spherical particles), these very small

particles are unlikely to contribute significantly to pressure drop or deposited mass. Also,

certain particles, particularly dust fibers, exist in indoor air at sizes larger than 100 µm.

However, there are very limited data on the concentration of these particles in indoor

environments. They are typically non-spherical and thus have poorly understood

behavior in indoor air flows. Their large inertia leads to deviation from fluid streamlines

and makes them difficult to sample, which, combined with very limited regulatory

8

interest, explains the lack of data. Some analysis of larger dust fibers is included in

Chapter 5, but most of the analysis is limited to 0.01 to 100 µm spherical particles.

1.4 Important Non-dimensional Parameters

In addition to the particle diameter, there are also many non-dimensional

parameters that are relevant for the study of heat exchanger fouling. Table 1.1 lists

important air Reynolds numbers. The ranges of values in the table are based on flow

rates, dimensions, and heat exchanger geometries typical of residential and commercial

systems. The first parameter is the Reynolds number in the duct leading up to a heat

exchanger, Reduct. These flows are always turbulent and frequently are developing

because of bends, constrictions, and other geometric changes to the flow near the heat

exchangers. Another duct Reynolds number, Reτ,duct is based on the friction velocity, u*,

which is a parameter with dimensions of velocity ( *w airu /τ ρ= , where τw is the wall

shear stress and ρair is the air density) that is often used to characterize turbulent flow.

When flow enters the heat exchanger, the Reynolds numbers in the fin channels, Refin,

drops two to three orders of magnitude from Reduct because the characteristic dimensions

becomes the much smaller fin spacing. Even though the low values for Refin in Table 1.2

suggest laminar flow, the upstream turbulence in the duct and enhanced surfaces typically

lead to a transition flow in the heat exchanger core. The Reynolds number based on the

tube diameter, Retube, is used to describe flow around and the heat exchanger tubes, an

important geometric feature in HVAC heat exchangers.

9

Table 1.1: Reynolds numbers and ranges for HVAC heat exchangers.

Typical Ranges

Parameter Formulaa Residential Commercial

Reynolds number based on duct dimension

ductduct

d uReν

= 104 - 105 2⋅104 - 3⋅105

Reynolds number based on duct dimension and friction velocity

*duct

,ductd uReτ ν

= 6⋅102 - 5⋅103 103 - 104

Reynolds number in fin channels

finfin

w uRe

ν⋅

= 102 – 9⋅102 102 - 2⋅103

Reynolds number based on tube diameter

tube fintube

d uRe

ν⋅

= 6⋅102 - 5⋅103 6⋅102 - 104

aIn these expressions, dduct is characteristic dimension of duct, u is bulk air velocity, ν is kinematic viscosity

of air, u* is the friction velocity ( 8*u / u f /w airτ ρ= = where f=2dduct∆P/ρairzu2 where ∆P/z is the

pressure drop per length of the duct in the direction of flow and ρair is the air density), ufin is the bulk

velocity in the fin channels (ufin = u(1+tfin/w) where tfin is the fin thickness and w is the center to center fin

spacing), and dtube is the tube diameter.

The Reynolds numbers in Table 1.1 are important when describing and relating

different systems. Although the face area of heat exchangers varies over a large range,

from less than 0.1 m2 to over 4 m2, the parameters in Table 1.1 and the reduction of a heat

exchanger to the simplest unit of a fin channel allow conclusions to be generalized.

There are also several non-dimensional parameters that govern particle dynamics

and deposition in the system. Particle Reynolds number, Stokes numbers, and relaxation

times for spherical particles of the size range 0.01 – 100 µm and typical HVAC velocities

and geometric parameters are listed in Table 1.2. The particle Reynolds number, Rep is

used to calculate the coefficient of drag, CD, which appears in the other dimensional

parameters in Table 1.2. Stkfin is the particle Stokes number that governs deposition by

10

impaction on fin edges. The Stokes numbers in Table 1.2 are in a general form. Stokes

numbers are most commonly reported assuming that Rep < 0.1, for which spherical

particles are in the Stokesian range, and assuming that CD = 24/Rep. A similar parameter

that governs deposition on the refrigerant tubes is Stktube. Note that both Stokes numbers

vary by nine orders of magnitude in HVAC systems. This is mostly due to the

dependence of the Stokes numbers on dp2 (for Stokesian behavior, Rep < 0.1). Particle

diameter varies over four orders of magnitude for particles that we are relevant for

present purposes. The last parameter in Table 1.2, the particle relaxation time, is shown

in its dimensionless form as commonly used for particles in turbulent flow. This

parameter governs how rapidly a particle responds to changes in the fluid velocity.

The parameters in Tables 1.1 and 1.2 influence the different mechanisms by

which particles of various sizes are likely to deposit. Deposition mechanisms are

discussed in more detail in the modeling work in Chapters 2 and the experimental work

in Chapter 3.

11

Table 1.2: Non-dimensional parameters that govern particle behavior in HVAC heat exchangers.

Parameter

Formulaa

Typical Range In HVAC Heat Exchangers

Particle Reynolds number p pp

d u uRe

ν

−= 10-4 - 4⋅101

Particle Stokes number based on fin thickness

c

D

4C3C

p pfin

air fin

dStk

tρρ

= 5⋅10-6 - 103

Particle Stokes number based on tube diameter

c

D

4C3C

p ptube

air tube

dStk

dρρ

= 2⋅10-8 - 2⋅101

Particle relaxation time (dimensionless)

( )2c

D

4C3C

*p p

pair

udu

ρτ

ρ ν+ = 8⋅10-8 – 102

aIn these expressions, dp is particle diameter, up is the particle velocity, Cc is the Cunningham slip

correction factor (Cc is calculated from Hinds (1999); Cc>>1 for dp < the mean free path of air, λ, and Cc ~

1 for particles > 1 µm), CD = f(Rep) is the coefficient of drag for the assumed spherical particle calculated

from Seinfeld and Pandis (1998), ρp is the particle density.

1.5 Outline of Dissertation

The overall outline for this work is presented below in Figure 1.2. The integrated

structure of this investigation is to first determine what particulate contaminants are

present in indoor and in outdoor air and how they are transported through a duct system

to the heat exchanger. Some of these particles are filtered, the rest are available to

deposit on the heat exchanger. Simulation and experimental results are used to determine

what fraction of particles actually deposit in the heat exchanger. The model and

experiments are detailed in Chapters 2 and 3. Chapter 4 applies these results, combined

12

with data on bioaerosol concentrations, environmental requirements, and health effects,

to determine the indoor air quality implications of biological fouling (depicted in the

lower branch of Figure 1.2). Chapter 5 uses deposition fraction experimental and

simulation results, as well as results from an additional experiment relating pressure drop

to the mass of material deposited to determine the pressure drop that results from fouling

and the rate of fouling in typical HVAC heat exchangers. This information, combined

with research about fans and the impact of airflow on capacity, is used to estimate the

energy consequences of fouling.

Size ResolvedParticles Presentedto Evaporator Coil

ParticlesDeposited on

Evaporator andMass

Indoor AirParticle

Concentrations

Outdoor AirParticle

Concentrations

DuctLeakage andHVAC AirFlow Data

Filtration,Filter Bypass,Coil Bypass

Experimental andSimulated Particle

DepositionData

IncreasedPressure DropThrough Coil

Due to Fouling

Reduced AirflowDue to Fouling

Energy Impactsof Coil Fouling

Experimental Foulingvs. Pressure Drop

Data Typical FanCurves

Reduced AirFlow Energy

Consequences

Existing ACFlow Data

BioaerosolConcentrations

BioaersolDeposition

Growth andAmplification

Indoor AirQuality Impacts

of BiologicalCoil Fouling

EnvironmentalConditions

Spread toIndoorSpaces

Figure 1.2: Analysis and experimental plan.

13

CHAPTER 2: MODELING PARTICLE DEPOSITION ON HVAC HEAT EXCHANGERS

2.1 Introduction

One purpose of this dissertation is to create a simple, robust, and widely

applicable model of particle deposition on fin-and-tube heat exchangers. Particulate

fouling of air-side heat exchangers has been modeled by other researchers, mostly

because of its importance to industrial processes. Significant strides have been made in

the modeling of heat exchanger fouling processes in dairy processing (e.g. Lalande and

Rene, 1988), nuclear reactor cooling systems (e.g. Watkinson, 1988), crude oil

distillation (e.g. Marshall et al., 1988), and other process and industrial heat exchangers.

This body of work is important and has improved many of the processes that use heat

exchangers, but there are several limitations that prevent its application to the specific

problem of HVAC heat exchanger fouling. The first limitation is one of geometry. The

fin-and-tube heat exchangers that are typical of HVAC systems are not widely used in

industrial processes, and the existing models are not typically adaptable to new

geometries. The second limitation is one of medium. Many of the problems discussed in

the literature involve fouling of the liquid side of a heat exchanger. Although the physics

do not change as the medium changes, the limiting mechanisms for fouling of liquid

systems are often crystallization or precipitation reactions. These reactions are less

important in HVAC heat exchanger fouling and other low temperature particulate and gas

fouling problems. The third limitation has to do with the purpose of process heat

exchanger fouling work. In many studies, it is often less important to understand the

mechanisms than it is to find solutions. The purpose of this chapter is to develop a

mechanistic model of particle deposition on HVAC heat exchangers and to understand

the important parameters in the fouling process.

14

2.1.1 Fin-and-tube heat exchangers

Before describing different approaches to the problem, it is important to clearly

describe the system being studied. For the purposes of modeling, the fin-and-tube heat

exchanger geometry is reduced to a series of straight channels created by the fins with

cylindrical refrigerant tubes that run horizontally perpendicular to the fins. The fins are

often corrugated to increase area for heat transfer. A schematic of typical fin-and-tube

heat exchanger geometry appears in Figure 2.1.

h

ytfin w

dtube

wtube

z

Air flowdirection

Air flowinto page

Figure 2.1: Front view of leading edge of fins (left) and side view of heat exchanger and refrigerant tubes (right) where w is the center-to-center fin spacing, h is the average height of fin corrugations, tfin is the fin thickness, y is the peak to trough width of fin corrugations, dtube is the tube diameter, wtube is the tube spacing, z is the heat exchanger depth.

The tube geometry of HVAC heat exchangers can vary over a wide range of

diameters and configurations. To improve heat transfer, a typical heat exchanger will

have multiple rows of offset tubes. The heat exchanger depicted in Figure 2.1 has two

sets of offset tubes, for a total of four tube rows. This is typical of many HVAC heat

exchangers and matches the test coil used for the experiments described in Chapter 3.

15

The notation that is used to describe the heat exchanger in Figure 2.1 is noffset = 2, nset = 2,

and nrow = noffsetnset = 4.

2.2 Previous Studies

A general model of fouling by gas-side particulate matter is presented by Bott

(1988). He divides particle fouling into three distinct processes: (1) transport and

deposition of particles to surfaces, (2) adhesion of deposited particles, and (3)

reentrainment of adhered particles. He further subdivides the transport and deposition

portion into transport through the bulk flow to the boundary region (typically caused by

advection, Brownian and eddy diffusion, thermophoresis and gravity) and transport

across the boundary layer (typically caused by the same mechanisms, without advection,

but with the addition of inertial impaction). Although it lacks complete detail, this was

among the first mechanistic examinations of particle deposition in heat exchangers. The

adhesion and potential resuspension of particles are described as “complicated

phenomena” that depend on surface roughness, amount and properties of previously

deposited materials, the presence of a liquid, and turbulent bursts. This work is useful in

outlining a general model and presenting important terms and possible deposition

mechanisms. It stresses the need for experimental data to both verify mathematical

models and provide input data for particular heat exchanger geometries.

In the same volume as Bott (1988), Epstein (1988) presents an overview of the

mechanisms that can cause particle deposition in heat exchangers. He reviews the work

of several authors on particle deposition and discusses the applicably of this work to

particulate fouling problems. He discusses the potential role of and governing equations

for deposition by means of Brownian diffusion, inertial impaction, gravitational settling,

and thermophoresis. He also describes the mechanisms of particle bounce, adhesion and

16

re-entrainment. The work also suggests that individual deposition mechanisms can be

assumed to operate independently in many heat exchanger geometries.

Muyshondt et al. (1998) used a very different approach to model the specific

problem of particle deposition on typical fin-and-tube HVAC heat exchangers. They

used a computational fluid dynamics (CFD) package and a Lagrangian approach. The

CFD software solves approximations to the continuity, momentum, and energy equations

for the airflow through a system and then uses this solution in a force balance to track

particle motion through the system. The three-dimensional equations for particle

velocity, for particles of the diameter range of 1- 100 µm, are as follows: (note,

typographical errors in Muyshondt et al. are corrected here):

( )D3 C4

p airp p

p p

duu u U U

dt dρρ

= − − (2.1)

( )D3 C4

p airp p

p p

dvv v U U g

dt dρρ

= − − + (2.2)

( )D3 C4

p airp p

p p

dww w U U

dt dρρ

= − − (2.3)

where up, vp, and wp are the Cartesian components of the particle velocity, ρair is the air

density, CD is the coefficient of drag on the (assumed spherical) particle, ρp is the particle

density, dp is the particle diameter, u, v and w are the components of the air velocity and

U and Up are total air and particle instantaneous velocities ( 2 2 2U u v w= + + and 2 2 2

p p p pU u v w= + + ), and g is the acceleration due to gravity.

Muyshondt et al. approximated air turbulence with a Reynolds stress turbulence

model with an assumed turbulence intensity of 5%. The turbulence intensity is typically

defined as u´/u where u´ is the standard deviation of the normally distributed fluctuating

component of the air velocity. The turbulence introduced randomness into the model and

17

thus a Monte Carlo simulation for several thousand particles was done for each particle

size considered. The resulting collection efficiency curves for a simple HVAC heat

exchanger are presented at three fin spacings (3.9, 4.7 and 5.5 fin/cm), two air velocities

(1.5 and 2.3 m/s), and vertical and horizontal fin orientation. (It is not clear why

Muyshondt et al. varied this last parameter. HVAC heat exchangers are almost always

installed with vertical fins to limit gravitational settling, provide for condensation

drainage, and to facilitate cleaning.) The results of Muyshondt et al. suggest increasing

collection efficiency with particle size, moderate deposition (< 10 %) for all vertical fin

cases for particles of 1 – 10 µm aerodynamic diameter, and sharply increasing deposition

for particles >10 µm. Their reported collection efficiencies asymptote at ~70 - 80 % for

70 µm and larger particles. Their results are discussed later in a comparison with the

modeling work of this chapter.

Although the Muyshondt et al. (1998) simulation work provides estimates of

particle deposition on HVAC heat exchangers, it presents little information on the

physics of the deposition processes. Furthermore, gravitational settling on fin

corrugations was excluded from their analysis, as was deposition on the leading edge of

the fins. My field work indicates that this is an important deposition location.

2.3 Preliminary Deposition Modeling using CFD

A primary purpose of my study was to mechanistically model deposition

processes on HVAC heat exchangers. To this end, initial runs were made with a

commercial CFD package, Fluent™. The initial approach was to construct a 17 × 65, 2-

dimensional grid (see Figure 2.2) and then calculate the velocity flow field through the

system. The original runs were conducted for isothermal conditions (no cooling of the

heat exchanger) and the flow was assumed to be laminar. For simplicity, the fins were

18

initially assumed to be infinitely thin and uncorrugated. The grid was refined eight times

until there was less than 2% average difference in the velocity fields between successive

runs.

Figure 2.2: Unrefined mesh from computational fluid dynamics simulation.

A significant challenge occurred when turbulence was introduced into the system.

Typical CFD models have two basic turbulence models: the k-ε model and the Reynolds

stress model. Both of these models approximate turbulence and require unmeasurable

parameters as input. Initial runs were completed with a k-ε model using, initially,

standard turbulence coefficients of Cµ = 0.09, C1 = 1.44, C2 = 1.92, σk = 1.0, and σε = 1.3.

(Mandrusiak (1988) presents complete equations and descriptions of the coefficients and

their importance in his Appendix A.) There is no clear way to determine these

parameters as they are geometry and flow specific and the transition flow in HVAC heat

exchangers is particularly poorly understood. Successive runs of the flow field

generation and particle tracking software, which solves approximations to Equations (2.1)

- (2.3), produced deposition rates that, although roughly consistent with the results of

Muyshondt et al. (1998), had variations of 30 – 50% in deposition fraction for 15 µm

particles depending on the turbulence model inputs. Even small changes in the

turbulence model parameters resulted in significant changes in the flow field. A

particular area of concern was the boundary layer flows near fin walls and refrigerant

19

tubes, as their structure was very sensitive to model parameters and they are crucial to

correctly assessing particle deposition (Bott, 1988). It should be pointed out that the

transition flows (from turbulent duct flow to laminar or to low Reynolds number

turbulent channel flow) that are prevalent in HVAC heat exchangers are particularly

difficult to model numerically with existing models (Versteeg and Malalasekera, 1995).

Given the limitations associated with the CFD approach, even for the 2-D case,

this approach was deemed to be too computationally intensive and too dependent on

unknown turbulence model parameters. Although CFD has applications in the study of

particle deposition problems, the complex geometry and unknown turbulence model

parameters would require a significant effort to produce reasonable results for the system

of interest.

2.4 Modeling the Mechanisms of Particle Deposition on HVAC Heat Exchangers

Instead of using CFD, I developed a different approach, one that considers

deposition of particles by individual mechanisms. This approach also has many

limitations – it ignores details of boundary layer development, requires some empirical

calculations, involves many assumptions about the nature of the air flow and turbulence,

assumes independent interactions among deposition mechanisms, and makes

idealizations about the geometry. The limitations are discussed in more detail throughout

this chapter. The strengths of this approach are that it is computationally simple, it

allows for clear indication of the importance of various deposition mechanisms, it permits

straightforward investigation of important parameters that lead to particle deposition in

HVAC heat exchangers, and it can be adjusted to new geometries easily.

20

The particle deposition model accounts for impaction on refrigerant tubes and fin

leading edges, Brownian diffusion in fin channels, gravitational settling on fin

corrugations, and air turbulence effects. When the heat exchanger is cooled,

thermophoresis to the fins and tubes is also considered. When cooled below the

dewpoint, the effect of condensed moisture, both through the mechanism of

diffusiophoresis and owing to increased tube diameter and fin thickness from condensed

moisture, is also included. Each deposition mechanism is defined and described below.

2.4.1 Deposition on leading edge of fins

My field examination of fouled heat exchangers suggested that impaction on the

leading edge of the fins is an important deposition mechanism. For this analysis, I

assume that the fin edge is a blunt body and use Hinds’ (1999) analysis for rectangular

slit cascade impactors with a modification to account for the fraction of face area of the

coil that is occupied up by fin edges. This analysis assumes that the air approaching the

fin edge makes a 90° bend. All particles that impact on the surface are assumed to stick.

The penetration fraction accounting only for losses because of impaction on fin edges,

Pfin, is estimated as follows:

1

2fintfin eff , fin

tP S k cf

wπ = −

(2.4)

where Stkeff,fin is the particle Stokes number based on the duct air velocity and the fin

thickness, corrected for particles having particle Reynolds numbers > 0.1 (Israel and

Rosner, 1983; Seinfeld and Pandis, 1998),tfin is the fin thickness, w is the center-to-center

fin spacing, and cf is the corrugation factor. The corrugation factor takes into account the

fact that a corrugated fin is longer than a straight fin and thus has more area for particle

impaction. The corrugation factor is defined as 2 2y h / h+ where h is the average

21

height of the fin corrugations and y is the peak-to-trough corrugation width (see Figure

2.1 for a schematic of the geometry). The term in the parentheses in Equation (2.4) is

limited to a maximum value of one to limit deposition only to the fraction of particles that

are directly in front of each fin.

Hinds (1999) estimates a 10% uncertainty bound on deposition (1- Pfin) when

using the formulation of Equation (2.4) for cascade impactors. Although seemingly quite

crude, this uncertainty is adequate for this situation, because of the addition of the tfin/w

factor which, for the most extreme case (corresponding to a dense fin spacing) is 10%.

Thus the actual error in Pfin is at most 1% from using this analysis. This contribution to

uncertainty also is likely considerably smaller than that which results from the adaptation

of Equation (2.4) from cascade impactor geometry to analysis of deposition on the

leading edge of heat-exchanger fins.

Equation (2.4) predicts the penetration fraction for cascade impactor plates.

There is some question about how appropriate the analysis is for deposition on a fin edge

because fin edges are much thinner that cascade impactor plates and thus cause less

disturbance to fluid streamlines. The thinner fin edges would cause Equation (2.4) to

underpredict the penetration associated with fin edge-impaction. An alternative estimate

of the penetration fraction for this mechanism was calculated assuming that the fin edges

were vertical half-cylinders with diameter equal to the fin thickness. A modification of

the work of Wang (1986) for deposition of particles from turbulent flow onto circular

cylinders was used:

0 802 11 arctan 0 808

.fin

fin,round eff , fint

P . Stk cfwπ

= − − (2.5)

Equation (2.5) is discussed in more detail below, in the section about particle impaction

on refrigerant tubes.

22

Equations (2.4) and (2.5) require knowledge of the particle Reynolds number for

the calculation of the Stokes’ numbers. The particle Reynolds number (see Table 1.2)

requires calculation of both the gas and the particle velocity. Without a detailed flow

field, this difference is unknown. The particle Reynolds number is required for

calculating the drag coefficent (CD), which in turn is used to calculated Stkeff,fin. To

explore the effects of Rep on the results, an assumption was made that the difference

between the particle and the gas velocity was equal to the gas velocity for calculating Pfin.

The implications of this decision are discussed in the presentation of the simulation

results. For comparison purposes, Pfin was also calculated assuming that all particles

obeyed Stokes law for drag on a sphere.

There is reason to believe that Equation (2.4) is a more appropriate predictor of

fin-edge impaction than Equation (2.5). The geometry of a fin edge is more similar to a

blunt impactor plate than it is to the smoothly rounded edge assumed in Equation (2.5).

Also, although the fin edges represent a smaller collection area than impactor plates, the

details of how the air streamlines deviate around the fin edges is also important.

According to the analysis of Panton (1996), for appropriate Reynolds numbers (Refin), the

streamlines would deviate from their straight-through orientation much closer to the fin

edge than they would for a cascade impactor plate. This would cause more particles to

impact than if the streamlines curved further back from the fin edge.

Additional attempts to refine the calculations of the fin edge-impaction could be

done by using the flow field from the flow into cascading plates presented by Panton

(1996) and using a Lagrangian approach to track particles. In preliminary simulations

with 15 µm particles, a 2 m/s air velocity, and a fin spacing of 4.7 fin/cm (Refin ≅ 200),

this approach yielded similar results to Equation (2.4). This potentially more accurate

and computationally intensive avenue could be explored if greater accuracy was required

23

for the leading edge impaction calculation. However, because impaction on fin edges

accounts for, at most, 10% removal of particles (corresponding to complete removal of

particles in front of each fin edge), this deposition mechanism does not warrant these

more sophisticated calculations for my present purposes.

2.4.2 Impaction on refrigerant tubes

Particles may also impact on the refrigerant tubes that run perpendicular to the

airflow direction and the fins. There are several theoretical and experimental studies of

particle impaction on tubes. An extension of the analysis of Israel and Rosner (1983)

suggests the following formula for estimating penetration for flow past a network of

tubes:

14

2 31 1 11 1 1 25 0 014 0 508 10

setntube

tube offsettube

dP . . . na wa a

−−

= − + − + × (2.6)

where a = (Stketf,tube – 1/8) where Stkeff,tube is the particle Stokes number based on the air

velocity in the heat exchanger and the tube diameter, nset is the number of tube sets in the

direction of flow dtube is the refrigerant tube diameter, wtube is the center-to-center tube

spacing, and noffset is the number of offset tube rows in each tube set. The term in the

innermost parentheses is limited to value of less than or equal to one and the

dtube/wtubenoffset factor is added to limit the deposition to particles in the volume of air

directly in front of the tubes. The assumption that a given particle will not deposit if their

Stokes number is less than 1/8 was first proposed by Taylor and has been verified by

other researchers (e.g. Bott, 1988). Israel and Rosner (1983) report that single tube

impaction deposition calculated with this formulation is good to 10% root mean square

(RMS) error for isolated horizontal tubes.

For improved accuracy, the following fit from Wang (1986) was used:

24

( )0 8021 arctan 0 80setn

. tubetube offset

tube

dP . a nwπ

= −

(2.7)

The difference between Equations (2.6) and (2.7) is very small (< 2%) for Stkeff,tube > 5,

although it is much greater for Stkeff,tube < 1. Given the importance of relatively low

particle Stokes numbers in the fouling problem, Equation (2.7) was used for all modeling.

In all cases, Ptube was limited to a minimum value of 1 - dtube/wtubenoffset to only allow for

removal of particles directly in front of the tubes.

There are several important assumptions that must be made to allow the use of

Equation (2.7). The first is that each tube can be considered to be independent of the

other tubes in the system. The simulations and experimental work of Ilias and Douglas

(1989) suggest that this is a good assumption for tubes in a vertical plane with tube

spacings typical of those in HVAC heat exchangers. However, the wake of upstream

tubes can alter deposition for downstream rows of tubes. Braun and Kudriavtsev (1995)

conducted numerical flow simulations for flow past a tube network with dtube = wtube =

ztube, where ztube is the tube spacing in the direction of flow. The flow fields in their work

suggest that the wake effect can lead to greatly increased turbulence on downstream tubes

at Retube typical of HVAC heat exchangers. This greater turbulence would in turn lead to

increased particle deposition, although the magnitude of this effect is unclear. The

narrow fin channels tend to decrease the air turbulence, and geometric features that are

designed to restart the boundary layers and promote turbulence tend to increase air

turbulence. The effect of tube wake was not quantified because of lack of data on

turbulence characteristics in a representative geometry.

The second assumption is that the particles are uniformly mixed as they approach

each tube. Although the tube wakes promote mixing, the short characteristic time that it

takes particles to travel between the sets of tubes [O(10 ms)] means that the assumed

25

uniform particle concentration, particularly at high enough Stkeff,tube to cause significant

deposition (Stkeff,tube > ~1), is unlikely to be correct for downstream tube rows. Bouris

and Bergeles (1996) document this shielding effect for a very high flow system (Retube =

1.3 ×104) with very large particles (45 - 700 µm). Their experimental work in a

combustion boiler heat exchanger, suggests about 80% less deposition on the second row

of aligned tubes. Their work is not directly applicable (because of the high flows and

large particle sizes), but it does suggest that the shielding effect can be significant. This

would then lead to Equation (2.7) overestimating deposition. To establish the lower

bound on uncertainty resulting from the shielding effects, calculations were done

assuming complete shielding (i.e. only considering deposition on the first two vertical

row of tubes in Figure 2.1 by setting nset = 1 in Equation (2.7)).

Similar to the calculation of Pfin, the difference between particle and gas velocity

is not explicitly known. As in the fin impaction case, assumption of this difference being

equal to the air velocity was made for impaction on tubes. This is more clearly a good

assumption for impaction deposition on tubes than it is for fins because, as a consequence

of the larger tube diameter, deposition only occurs for much larger particles than impact

on the fin edges. Larger particles have significant inertia and larger relaxation times and

are less likely to quickly adjust to changes in air velocity near the tubes. Thus, the

assumption of non-Stokesian drag (i.e. using the Seinfeld and Pandis (1998) equations for

CD) is more appropriate and was used for all calculations.

2.4.3 Gravitational settling on fin corrugations

To increase heat transfer, manufacturers often corrugate fins. Large particles can

deposit by gravitational settling on the corrugation ridges. The penetration fraction

accounting for losses only from gravitational settling, PG, is estimated as follows (Fuchs,

1964):

26

( )1 V z ysPG hU w t fin

= − − (2.8)

where Vs is the particle settling velocity, z is the heat exchanger depth in the direction of

bulk air flow, h is the average height of the fin corrugations, U is the bulk air velocity in

the heat exchanger, and y is the peak-to-trough corrugation width (see Figure 2.1 for

geometric description). The ratio in the parentheses is limited to a value of one. Particles

are not assumed to be Stokesian for the calculation of Vs, for which this equation is used:

( )c

D

4C3C

p air ps

air

d gV

ρ ρ

ρ

−=

(2.9)

where Cc is the Cunningham slip correction factor (Hinds, 1999), ρp is the particle

density, ρair is the air density, dp is the particle diameter, g is acceleration due to gravity,

and CD is the coefficient of drag on the particle calculated assuming the particle is a

sphere and using the formulation presented in Seinfeld and Pandis (1998). Because CD

is a function of particle Reynolds number, which is a function of Vs, an iterative scheme

was used to determine Vs.

The largest uncertainty connected to deposition associated with gravitational

settling is that the channel geometry that Fuchs (1964) considered is significantly

different than the sloped wall and ceiling geometry that occurs in the fin corrugations.

Furthermore Fuchs’ analysis was limited to laminar flow, rather than the transition flow

in heat exchangers. Several researchers have considered gravitational settling in

horizontal tubes (e.g. Pich, 1972) and inclined tubes (e.g. Lipatov et al., 1988; Anand et

al., 1992), but these geometries are even less applicable because of their circular cross

section or the fact that they slope in the direction of flow, rather than across the channel

as occurs in a fin corrugation. To assess the variation in deposition by gravitational

settling, an upper bound on the penetration fraction associated with this mechanism was

27

made by doubling the average height of the fin corrugation. Similarly, a lower bound

was estimated by halving the average height of the fin corrugation.

2.4.4 Deposition by air turbulence in fin channels

Air turbulence in the duct leading up to a heat exchanger can also induce

deposition on heat-exchanger surfaces. The fluctuating components of velocity can

impart an angled trajectory to particles as they enter the heat exchanger (see Figure 2.3).

If the particle has a sufficiently large relaxation time and a sufficient deviation in velocity

direction from the bulk flow, it will impact on a fin and not penetrate the coil.

wp'wT

up'U

z

Figure 2.3: Top view of fin channel showing particle trajectory because of air turbulence where wT is the particle entering location, wp´ is the fluctuating particle velocity component perpendicular to fin channel, U is the bulk air velocity, up´ is the fluctuating particle velocity component in the direction of airflow, and z is the heat exchanger depth

Mathematically, I estimate the penetration associated with losses owing to

turbulent deposition as:

Prob 1imp

Tp

Pττ

= >

(2.10)

where τimp is the characteristic time for a particle to impact on the wall and τp is the

particle relaxation time. The impaction time scale, τimp is calculated from geometry and

trigonometry as follows:

28

T

impp

ww '

τ = (2.11)

where wT is the distance from the nearest fin when the particle enters the channel and wp´

is the particle turbulence fluctuating velocity component perpendicular to the fin channel

at a given particle entering location. The particle relaxation time, τp, was computed

according to the following expression, which does not assume Rep < 0.1 Hinds (1999).

( )c

D

4C

3Cp p

p 'air p

d

U u

ρτ

ρ=

+ (2.12)

where up´ is the particle turbulence fluctuating velocity component in the streamwise

direction at a given particle entering location

A Monte Carlo simulation was used to estimate PT. For a given particle size, 107

simulations were completed to minimize any numerical uncertainty. In the analysis,

particles were assumed to enter the channel uniformly distributed between the fins, by

selecting wT from a uniform distribution with maximum value of (w-tfin)/2. The

fluctuating components of the air velocity were assumed to be independent Gaussian

distributions whose shape, as a (weak) function of bulk velocity in the duct, comes from

direct numerical simulation (DNS) data presented by Moser et al. (1999). Although we

are considering impaction by air turbulence as a two-dimensional phenomenon (because

the vertical component of fluctuating velocity will not lead to significant increased

deposition), the Moser et al. (1999) simulations consider all three dimensions.

The Moser et al. (1999) data provide the fluctuating components of the air

velocity. Caporaloni et al. (1975) present a multi-step formulation for relating fluid

fluctuating velocity components to those of particles in the turbulent flow:

pu ' Ku'= (2.13)

29

2

1fl

fl

aT bK

aT+

=+ (2.14)

( ) 236

2 p air p

µadρ ρ

=+ (2.15)

3

2air

p airb ρ

ρ ρ=

+ (2.16)

where Tfl is the Lagrangian integral scale of time which is assumed to be equal to є/u´2

where є is the eddy viscosity determined from the Moser et al. (1999) data and µ is the

dynamic viscosity of the fluid (air). Equations (2.13) - (2.16) are also used for the wall-

normal fluctuating velocity component, wp´. The fluctuating components of the particle

velocities calculated from Equations (2.13) - (2.16) are used in Equation (2.11) to

determine the characteristic time for impaction. The dependence of Equation (2.15) on

particle diameter means that large particles, because of their inertia, will be less affected

by turbulent eddies. Binder and Hanratty (1991) experimentally determined (in an

annular geometry), the following relationship for K in Equation (2.13):

1

1 0 7 p

fl

K.

Tτ=

+ (2.17)

Practically, the use of Equation (2.17) does not predict significantly different turbulent

particle fluctuating velocities than does the use of Equation (2.14).

The assumption of a Gaussian turbulence distribution is common for many

problems (Hinze, 1959) and has been used for the specific problem of HVAC heat

exchanger fouling (Muyshondt et al., 1998). It is important to note that, because no

turbulence measurements have been made in any known study of flow through a

comparable heat exchanger, the actual spatial distribution of the turbulent fluctuations is

unknown. Also, the geometry of the Moser et al. (1999) simulations are for a channel,

30

rather than the duct flow upstream of the coil, which leads to some questions about the

validity of these assumptions.

The analysis presented in Equation (2.10) also assumes that the turbulence does

not persist from the bulk flow into the fin channels. This is based on the fact that the

largest turbulent eddies are the most persistent and contain the most turbulent energy

(Hinze, 1959). These large eddies from the bulk duct flow are most likely to be broken

up or constrained by the narrow dimension of the fin channels. In an idealized case, the

flow would relaminarize. However, real heat exchangers contain macroscale roughness

elements and fin discontinuities, which are designed to promote turbulence and restart the

boundary layer to increase heat transfer. The exact nature of the turbulent flow in the

heat exchanger is unknown, but there would likely be increased deposition from

turbulence in the channels.

To address concerns with this deposition mechanism, five uncertainty factors

were included in the analysis. The first uncertainty factor was that the fluctuating

components of the velocity were increased and reduced by 50% to account for any

incompatibility between the Moser et al. (1999) channel simulations and typical duct

flows. Secondly, ten successive sets of 1 × 107 Monte Carlo runs were completed at one

set of geometry and bulk flow conditions and the standard deviation of the resulting PT

values from these ten runs were considered to be the numerical uncertainty. Thirdly, the

deposition criterion established in Equation (2.10) ignores the role of the boundary layer

and surface roughness. To address this concern, this criterion was varied by 50% in both

directions to establish what effect this had on predicting PT. Fourthly, the role of

additional deposition by turbophoresis, the motion of particles down a turbulence

intensity gradient, was included by assuming that the duct turbulence parameters

persisted all the way through the fin channels in the heat exchanger. The magnitude of

31

deposition owing to turbophoresis was calculated following the work of Caporaloni et al.

(1975). The velocity component of the particle towards the wall due to turbophoresis,

wTF, was calculated as follows:

( )2'

pTF p

d ww

dwτ= −

(2.18)

where the derivative term is the slope of the squared fluctuating particle velocity

component perpendicular to the fin. The turbulence parameters come from the DNS

work of Moser et al. (1999). The penetration fraction as a result of deposition by

turbophoresis was calculated as follows:

( ) ( )21 TB

TB 'fin p

w zPw t U u

= − − +

(2.19)

The inclusion of turbophoresis produces a lower bound on the penetration fraction

associated with turbulence because the turbulence parameters that are used to calculate

Equations (2.18) and (2.19) are likely larger than those that actually exist in the fin

spacing. For the fifth factor, the penetration fraction owing to air turbulence, PT, was

calculated both assuming that Stokes law for drag holds and calculating the drag from the

Reynolds number based on the gas velocity using the formulations of Seinfeld and Pandis

(1998).

2.4.5 Deposition by Brownian diffusion

Small particles are most likely to deposit by means of Brownian diffusion. The

penetration fraction accounting for deposition only by Brownian diffusion is calculated

assuming laminar flow in the heat exchanger core and follows the work of DeMarcus and

Thomas (1952) for channel flow:

32

1 885 22 3 1520 915 0 0592 0 0259( . ) ( . ) ( )

DP . e . e . eξ ξ ξ− − −= + + (2.20)

where ξ=4Dz/[(w-tfin)2U] and D is the particle diffusion coefficient equal to

(kTCc)/(3µdpπ) where k is the Boltzmann constant, T is the air temperature, and µ is the

dynamic viscosity of the air. The penetration fraction only considering particle loss by

Brownian diffusion, PD, is limited to lie between zero and one.

Brownian diffusion was included in the model because it is the only possible

significant deposition mechanism for submicron particles in this system (at least for the

isothermal case). Nevertheless, due to the relatively short residence time in the system at

typical velocities, particles of interest do not deposit significantly by Brownian diffusion.

Hence, no uncertainty estimate was completed for this type of deposition.

2.4.6 Combining deposition mechanisms

The deposition mechanisms were combined assuming that they operate

independently, so that the overall deposition fraction, η, was estimated by Equation

(2.21). The assumption of independence is well justified for mechanisms that affect

widely different particle sizes, such as Brownian diffusion and gravitational settling

(Chen and Yu, 1993). The assumption has been applied to estimate deposition by

combined mechanisms in heat exchangers (Bott, 1988; Epstein 1988) and in other

systems, such as fibrous filtration (Hinds, 1999).

DTGtubefin PPPPP−= 1η (2.21)

Each term in Equation (2.21) is limited to be between one and zero.

The overall uncertainty in the calculation of η was determined by estimating an

upper and lower bound for each of the penetration factors in Equation (2.21), except

Brownian diffusion, because of its minimal importance to overall deposition. Table 2.1

33

shows a summary of the error and potential bias associated with each penetration factor

in Equation (2.21).

Table 2.1: Summary of approaches used to estimate model uncertainty.

Term Upper Bound Lower Bound

Pfin Maximum of penetration on circular half cylinder and Equation (2.4) plus 10% uncertainty and Rep based on gas velocity

Minimum of penetration on circular half cylinder and Equation (2.4) minus 10% uncertainty and assumed Stokes law for drag

Ptube Complete shielding by initial tube rows and Rep based on gas velocity

Assumed Stokes law for drag

PG Fin corrugation average height doubled Fin corrugation average height halved

PT u´and w´ reduced by 50% , plus one standard deviation from successive Monte Carlo runs, Equation (2.10) criterion increased 50%, and Rep based on gas velocity

u´and w´ increased by 50%, inclusion of turbophoretic deposition, minus one standard deviation from successive Monte Carlo runs, Equation (2.10) criterion decreased 50%, assumed Stokes law for drag,

2.4.7 Particle deposition mechanisms not considered

Two particle deposition mechanisms were initially considered, but were later

excluded from the analysis. Particle interception by refrigerant tubes and fin walls was

excluded because it was a very weak deposition mechanism that did not lead to

significant loss of particles of any size (relative to included deposition mechanisms). The

motion of particles in a shear force gradient (i.e. a boundary layer flow), referred to as the

Saffman lift force (Fan et al., 1992), was also excluded. This mechanism was not

considered because it only caused deposition for particles large enough to be completely

34

removed by other considered mechanisms and because its analysis requires detailed

knowledge of the boundary layer structure.

2.4.8 Particle reflection

There is an additional assumption in the model that all particles adhere once they

reach the surface. This is a good assumption for the liquid particles used in the

experiments described in Chapter 3 and is also the assumption made in the simulations of

Muyshondt et al. (1998). Cheng and Yeh (1979) established that particle bounce does

occur on uncoated cascade impactor surfaces. They experimentally verified a

relationship for the critical velocity at which particle bounce begins to occur:

ca

vdβ

= (2.22)

where vc is the critical velocity that signifies the onset of particle bounce, β is a

theoretically determined coefficient that depends on particle and surface properties (see

Dahneke, 1971 for details of calculating β), and da is the particle aerodynamic diameter

(for spherical particles a p p *d d /ρ ρ= where ρ* is the density of liquid water). The

range of values of β suggested by Cheng and Yeh (1979) for uncoated cascade impactor

plates (and verified for particles 0.5 – 10 µm in diameter) produces the low, typical and

high values for vc shown in Figure 2.4.

35

Aerodynamic Diameter, da (µm)1 3 5 10 30 50 100

Cri

tical

Vel

ocity

, vc (m

/s)

0

1

2

3

4

5

Figure 2.4: Critical velocity for onset of particle bounce (Cheng and Yeh, 1979).

Given that typical air speeds in HVAC systems are 1 – 5 m/s, Figure 2.4 suggests

that particle bounce may be an issue for solid supermicron particles in heat exchangers,

particularly for larger particles and higher velocities. Wang (1986) used a critical

velocity analysis to determine adhesion efficiency for particles that impact on a circular

cylinder. He used the work of Dahneke (1971) to establish the rebound velocity for

particles with a velocity greater than the impact velocity:

21 c

r ii

vv v ev

= −

(2.23)

where vr is the rebound velocity, vi is the impact velocity, and e is the coefficient of

restitution, which is a property of the materials of the surface and the particle. Equations

(2.22) and (2.23) could be used to assess the impact of particle bounce for impaction on

fins and tubes and for air turbulence impaction, the only deposition mechanisms that

affect particles large enough to have a concern with bounce (the velocities involved in

gravitational settling are too small to cause significant particle reflection). The

application would be approximate because of the unknown material properties and the

36

potential variation in vc, e, and β for real heat-exchanger surfaces. Also, heat-exchanger

surfaces have significant surface roughness, are often are coated with a layer of water,

and are often oily (from the manufacturing process and from previous deposits). This

means that Equations (2.22) and (2.23) overstate particle reflection from real heat-

exchanger surfaces. In the absence of reasonable coefficient values, particle reflection is

excluded from this analysis.

2.5 Non-isothermal Deposition Processes

The purpose of heat exchangers is to transfer energy between a refrigerant and an

air stream. Given the importance of air conditioning to energy use and peak electrical

demand, the case of cooled-coil deposition is particularly important. Many cooling coils

also serve to dehumidify air resulting in condensation on the surfaces of the heat

exchanger. There are three potentially important additional deposition mechanisms that

result from thermal effects: thermophoresis to fin walls and refrigerant tubes,

diffusiophoresis to fin walls and refrigerant tubes, and additional impaction because of

condensed moisture. Each of the penetrations associated with these mechanisms can be

added as a factor into Equation (2.21).

2.5.1 Thermophoresis to fin walls

Thermophoresis is the net motion of particles down a gas temperature gradient. It

occurs because gas molecules on the higher temperature side of a particle impart more

kinetic energy in collisions with the particle than gas particles on the colder side. Talbot

et al. (1980) presented the following formulation for thermophoretic velocity, WTh, the

velocity of a particle down a temperature gradient due to these collisions:

ThW TTνκ= − ∇

(2.24)

37

where κ comes from Equation (2.25) as described in Talbot et al. (1980), ν is the

kinematic viscosity of the gas, T is the gas temperature, and ∇T is the temperature

gradient. The thermophoretic constant, κ, is evaluated as follows:

( )

2 1

1 3 1 2 2

g

p

g

p

Ck Kns tk

km tk

C C Kn Kn A Be

C Kn C Knκ

− + + + =

+ + +

(2.25)

where Cs = 1.14, Ct = 2.18 and Cm =1.14 are the coefficients of thermal slip, temperature

jump, and momentum slip taken directly from Talbot et al. (1980), kg is the thermal

conductivity of the gas (air conductivity as a function of temperature in this case), kp is

the thermal conductivity of the particle (for comparison with the oil droplet experiments

described in Chapter 3, I used the conductivity of unused engine oil as a function of

temperature), Kn is the particle Knudsen number = 2λ/dp where λ is the mean free path of

the gas molecules, and A = 1.20, B = 0.41, and C = 0.88 are empirically fit coefficients

taken from Talbot et al. (1980). Unlike other deposition mechanisms that are strongly

dependent on particle size, thermophoresis is only weakly dependent on particle size

through κ.

The thermophoretic velocity is used to estimate a penetration factor only

considering thermophoresis, PTh, which compares the characteristic time for deposition

by thermophoresis to the characteristic time for particle penetration through a fin channel:

( )Th

Thfin

2 zWP = 1-w t U− (2.26)

When using Equations (2.24) - (2.26), the definition of ∇T would seem to be

critically important. Equation (2.24) is valid for particles in a boundary layer, so ∇T is

typically approximated by (T - Twall)/∆ where Twall is the wall (fin) temperature and ∆ is

38

the thermal boundary layer thickness. If the flow in the fin channel is turbulent, ∆ can be

calculated using the thermal law-of-the-wall relationships (e.g. Kays and Crawford,

1993) or by using simpler scaling relationships for turbulent boundary layer flow (e.g.

White, 1986). If the flow is laminar, ∆ can be analytically determined. However, the

boundary layer thickness cancels out in Equation (2.26) because ∆ appears in the

expression for ∇T as well as being the distance over which particle deposition occurs for

Equation (2.26).

To accurately estimate the temperature gradient term and the wall temperature

term in a heat exchanger, we need to know the average temperature of the fins. This is a

difficult term to measure, and very often, only the temperatures of the refrigerant flowing

into and out of the system are known. The relatively short length, minimal thickness,

and high conductivity of fin assemblies result in very high fin efficiencies (89 – 95%) for

the fins in a typical 4.7 fin/cm coil. To simplify the analysis, the fin surfaces are all

assumed to be at the average refrigerant temperature and the air temperature is assumed

to be uniformly at a value halfway between the coil inlet and outlet temperature.

2.5.2 Thermophoretic deposition on tubes

Equations (2.24) - (2.26) can be recast for thermophoretic deposition on tubes

with Equation (2.26) being modified to account for the different path length of a particle

traveling over a tube

tube Th

Th,tube set offsettube

d WP = 1- n nw U

π (2.27)

The very short characteristic time that particles spend traveling over each tube

suggests that thermophoretic deposition on tubes is likely to be a weak process. Park and

Rosner (1989) looked at combined impaction and thermophoresis on horizontal tubes

over a relevant Reynolds number range and suggested that for large particles PTh, tube <<

39

Ptube. For smaller particles Pth,tube can be a significant contributor to particle deposition

on tubes, although Pth,tube is typically small. Because of the small amount of deposition

associated with this mechanism, shielding and wake effects are ignored.

2.5.3 Diffusiophoresis to fin walls

Diffusiophoresis is the motion of particles in a concentration gradient in a gas

mixture. This motion is induced by the momentum imparted by the uneven frequency of

collisions on the different sides of the particle. In the case of HVAC heat exchangers, the

dehumidification of air causes a mass flux of moisture towards the condensing surfaces.

The total pressure is constant, so the resulting concentration gradient of dry air (lower

near the wall, higher near the surface) would cause a diffusive flux of air away from the

wall. The direction of the diffusiophoretic force on a particle should thus be in the

direction of the motion of the air (i.e. away from the surface), because it is the heavier

gas. Waldmann (as cited in Goldsmith and May, 1966) used kinetic theory to derive the

following equation for the diffusiophoretic velocity, WDf´:

2 1 1

122 2 1 1

Df 'm m dW D

dwm mγ

γ γ−

=+ (2.28)

where m1 and m2 are the mass of the vapor (water) and gas molecules (air), γ1 and γ2 are

the mole fractions of the vapor and gas, D12 is the coefficient of diffusion of the vapor in

the gas, and w is the wall normal direction. Hence it seems that particles are moved away

from the wall as a result of diffusiophoresis.

However, there can be no net flux of dry air at the wall. Therefore, the

phenomenon of condensation on the heat-exchanger surfaces necessitates a

hydrodynamic flow (called the Stephan flow) of air towards the surface that opposes the

diffusive air flux described above (Goldsmith and May, 1966). The velocity of this

40

phenomenon, Wsf, is opposite to the direction of diffusiophoresis and has the form shown

in Equation (2.29):

12 1

2sf

D dpWp dy

= − (2.29)

where p1 and p2 are the partial pressures of the vapor and the gas. Combining Equations

(2.28) and (2.29) and substituting γ1= p1/ (p1+ p2) and γ1+ γ2=1, the overall expression for

the velocity resulting from diffusiophoretic and Stephan velocity is Wdf:

1 12 1

21 1 2 2df

m D dpWp dym mγ γ

= −+ (2.30)

Practically, p1, p2, γ1, and γ2 are evaluated from the relative humidity of the air, φ,

and the saturation pressure of the air and its temperature, T. Equation (2.30) is strictly

only valid for (small) particles (Kn > 1), but it agrees with experimental data for larger

particles to within 9% (Goldsmith and May, 1966).

The combined diffusiophoretic velocity is used to calculate a penetration fraction

accounting for loss only by diffusiophoresis, Pdf, using the same rational that was used in

Equation (2.26).

( )df

dffin

2 zWP = 1-

w t U− (2.31)

Equations(2.30) and (2.31) are based on the same boundary layer thickness assumptions

that were made for Equation (2.26) (which cancel out in the final formulation).

It should be noted that at typical conditions in HVAC heat exchangers, Pdf, is

close to unity because of the relatively small humidity concentration gradients in these

systems. Diffusiophoresis is also the only deposition mechanism discussed with no

41

dependence on particle size, which suggests that its importance might be larger for

accumulation mode particles (those between 0.1 - 1 µm), which are unlikely to be

affected by other deposition mechanisms.

2.5.4 Presence of condensed water

The presence of condensed water on heat-exchanger surfaces is expected to

increase deposition. Although some of this water drains off the coil into the condensate

drain, much remains on the coil due to surface tension effects. This additional moisture

leads to an effectively larger fin thickness, decreased fin spacing, and increased tube

diameter. The changes in these factors lead to increased deposition by every previously

discussed deposition mechanism, except gravitational settling. It is difficult to model this

effect in the general way that was used for other deposition mechanisms that have been

discussed here, because the details of how much water condenses on a coil and how

quickly the condensate drains off the coil are specific to the heat exchanger and to the

environmental conditions. Practically, this effect will be modeled by calculating an

average water film thickness and increasing the fin thickness, tfin, and tube diameter, dtube,

by the layer thickness and decreasing the fin spacing, w, by this amount. An additional

effect of condensation is that the coating of bulk water on the fin-and-tube surfaces

should effectively eliminate particle bounce discussed in Section 2.4.8.

2.6 Modeling Parameters

The parameters chosen for the simulations are meant to be representative of the

range of velocities and fin spacings found in residential and commercial HVAC systems.

The face velocity of typical coils varies over about an order of magnitude range

depending on the type of coil being studied. Three typical velocities are compared in this

42

study and are chosen to represent three common types of coils. The velocities and their

bases are shown in Table 2.2.

Table 2.2: Velocities considered in simulations.

Velocity HVAC Coil Basis Reference

0.75-1.25 m/s Commercial reheat coil

0.094 m3/s duct flow through a 0.093 m2 square duct

Carter et al. (1998)

1.5-2.5 m/s Residential coil

0.57 m3/s flow through 0.28 m2 supply plenum

ACCA (1995)

2-6 m/s Chilled-water coil

5.7 m3/s flow through 1.4 m2 supply plenum

McQuiston et al. (2000)

I chose to model a complete range of fin spacings, w. The range spans low

efficiency coils like reheat coils or chilled-water coils (2.4 fin/cm), residential mid-

efficiency coils (4.7 fin/cm), and very high efficiency coils (7.1 fin/cm). The rest of the

geometric parameters are chosen to match those of the test coil described in Chapter 3

and are described in Table 2.3. For comparison to the coil simulated by Muyshondt et al.

(1998) the geometric parameters that they simulated are also listed in Table 2.3.

For simulating thermal effects, temperature ratios, θ = Twall/T, of 0.983, 0.966,

0.949, and 0.932 were modeled, covering the relatively modest temperature range found

in typical heat exchangers (based on indoor air temperatures of 293 - 303 K and coil

temperatures of 277 – 288 K). For simulating the effect of diffusiophoresis and

condensation, relative humidities, φ, of 50-90 % were considered. I also considered a

43

uniform water layer of 114 µm, corresponding to typical values from the experiments

discussed in Chapter 3.

Table 2.3: Geometric parameters for this study and for Muyshondt et al. (1998).

Coil Dimensions

Parameter This Study Muyshondt et al. (1998)

mm (inch) mm (inch)

tfin Fin thickness 0.114 (0.0045) No impaction on fin edge

dtube Tube outer diameter 9.53 (0.375) 9.53 (0.375)

wtube Center-to-center tube spacing 25.4 (1.00) 24.1 (0.950)

z Fin depth 44.0 (1.73) 58.4 (2.30)

h Fin corrugation average height 1.50 (0.0591) No corrugation

y Fin corrugation width 1.00 (0.0394) No corrugation

Tube Geometry

nset Number of sets of tubes 2 1.5a

noffset Number of offset tubes per set 2 2

nrow Number of tube rows 4 3

aMuyshondt et al. modeled a heat exchanger with 2 aligned tube rows and one offset tube row. This is an atypical configuration. Practically, this geometry was modeled by calculating tube deposition first for the aligned rows of tubes using Equation 2.7 with nset = 2 and noffset = 1 and then separately for the non-aligned tube row with nset = 1 and noffset = 1.

2.7 Modeling Results

In this section, I will discuss the deposition fraction results and the uncertainty

calculations for isothermal heat exchangers and cooled-and-condensing heat exchangers

as well as compare the results of the model to other published work.

44

2.7.1 Isothermal conditions

Deposition fraction as a function of velocity and fin spacing appears in Figures

2.5 and 2.6. For all except the smallest particles considered, deposition increases with

increasing particle size. Deposition fractions for all velocities and fin spacings is less

than 2% for submicron particles. Brownian diffusion is the dominant deposition

mechanism that affects smaller particles and the residence time in the coil is too short for

Brownian diffusion to cause significant deposition. Deposition for 1- 10 µm particles is

caused by impaction on fin edges: the kinks at 3 – 6 µm aerodynamic diameter in the

deposition fraction curves are caused by the fin completely sweeping the volume of air in

front of each fin (i.e. the parenthetical term in Equation (2.4) equaling one, so Pfin is equal

to cf tfin/w). Deposition of particles greater than 10 µm in diameter is caused by

gravitational settling, impaction on tubes, and air turbulence.

Deposition increases with increased velocity for the inertial deposition

mechanisms (impaction on fin edges and tubes and air turbulence impaction). Deposition

decreases with increasing velocity for Brownian diffusion (this effect is hard to see in

Figures 2.5 because so little deposition occurs by this mechanism), and also for

gravitational settling (this can be seen by the increased deposition for 8 – 12 µm particles

for 1 m/s as compared with the higher velocities in Figure 2.5). These increases are

caused by the increased residence time for particles in the system at slower velocities.

Deposition fraction increases with increased fin density for all particle sizes (Figure 2.6).

45

Aerodynamic Diameter (µm)0.01 0.1 1 10 100

Dep

ositi

on F

ract

ion

(%)

0

20

40

60

80

1001 m/s2 m/s4 m/s

Figure 2.5: Deposition as a function of velocity for fin spacing = 4.7 fin/cm.


Dep

ositi

on F

ract

ion

(%)

0

20

40

60

80

1002.4 fins/cm4.7 fins/cm7.1 fins/cm

Figure 2.6: Deposition as a function of fin spacing for U = 2 m/s.

Penetration accounting for loss only by fin edge-impaction is shown in Figures

2.7 and 2.8. The kinks caused by complete deposition of particles directly in front of the

fin are clearly evident on both plots. Increasing velocity leads to decreasing penetration

because of the dependence of the particle Stokes number on velocity (Figure 2.7). The

minimum penetration is unaffected by the particle velocity and thus remains constant for

46

a given fin spacing as velocity is varied. Penetration also decreases as fin spacing

decreases because of the proportional increase in fin edge area available for deposition.

The particle Stokes number is unaffected by the fin spacing; hence, the critical particle

diameter at which all of the particles directly in front of each fin edge are removed from

the air stream remains constant for a given velocity (Figure 2.8).

Aerodynamic Diameter (µm)1 2 3 4 5 6 7 8 910

P fin

0.90

0.92

0.94

0.96

0.98

1.00

1 m/s2 m/s4 m/s

Figure 2.7: Impaction deposition on fin edges as a function of velocity for fin spacing = 4.7 fin/cm.


P fin

0.90

0.92

0.94

0.96

0.98

1.00

2.4 fin/cm4.7 fin/cm7.1 fin/cm

Figure 2.8: Impaction deposition on fin edges as a function of fin spacing for U = 2 m/s.

47

Figures 2.9 – 2.12 show penetration fractions accounting for the mechanisms of

gravitational settling, impaction on tubes, and air turbulence impaction as a function of

air velocity (Figures 2.9 and 2.10) and fin spacing (Figures 2.11 and 2.12).

For the lower velocity (Figure 2.9), gravitational settling is the dominant

deposition mechanism for particles greater than 10 µm. Impaction on tubes causes loss

of 25 µm and larger particles. Air turbulence impaction would cause a very small

amount of deposition for very large particles. However, these particles are likely to

already be removed by settling on the fin corrugations or impacting on tubes.

Aerodynamic Diameter (µm)1 3 5 10 30 50 100

Pene

trat

ion

Frac

tion

0.00

0.25

0.50

0.75

1.00PG

Ptube

PT

Figure 2.9: Gravitational, tube impaction, and turbulent penetration fractions for U = 1 m/s and fin spacing = 4.7 fin/cm. The air turbulence penetration fraction is close to unity for all particle sizes.

For the higher velocity (Figure 2.10), impaction on tubes is the dominant loss

mechanism. The kink in the Ptube curves in Figures 2.10 – 2.12 is caused by the

complete removal of particles directly in front of the tubes. Even though the residence

time in the coil is shorter than at slower velocities, gravitational settling still causes

48

significant particle removal at this higher velocity. Air turbulence impaction contributes

to loss of very large particles.

Aerodynamic Diameter (µm)1 5 10 50 100303

Pene

trat

ion

Frac

tion

0.00

0.25

0.50

0.75

1.00PG

Ptube

PT

Figure 2.10: Gravitational, tube impaction, and turbulent penetration for U = 4 m/s and fin spacing = 4.7 fin/cm.

The larger fin spacing (Figure 2.11) shows more particle removal by impaction on

tubes than by gravitational settling, although both are important deposition mechanisms.

Impaction on the refrigerant tubes is unaffected by the fin spacing (to the first order –

there is a slight decrease in Ptube associated with the slightly higher velocities in the heat

exchanger core that result from an acceleration of the air through the smaller fin channels

associated with higher fin pitches). The fin channel is too wide for air turbulence to

cause any loss.

The tighter fin spacing shown in Figure 2.12 has more corrugations for

gravitational settling and hence this mechanism becomes dominant. Impaction on tubes

is also important. Air turbulence impaction causes a small amount of loss for very large

particles.

49


Pene

trat

ion

Frac

tion

0.00

0.25

0.50

0.75

1.00PG

Ptube

PT

Figure 2.11: Gravitational, tube impaction, and turbulent impaction penetration fractions as a function of fin spacing for 2.4 fin/cm and U = 2 m/s. The air turbulence penetration fraction is equal to unity for all particle sizes.


Pene

trat

ion

Frac

tion

0.00

0.25

0.50

0.75

1.00PG

Ptube

PT

Figure 2.12: Gravitational, tube impaction, and turbulent impaction penetration fractions as a function of fin spacing for 7.1 fin/cm and U = 2 m/s.

To illustrate uncertainties, the penetration fractions associated with the upper and

lower bound conditions described in Table 2.1 are shown in Figures 2.13-2.16 for

impaction on fins (Figure 2.13) and on tubes (Figure 2.14), gravitational settling (Figure

50

2.15), and for impaction caused by inlet turbulence (Figure 2.16). Brownian diffusion

causes negligible uncertainty by comparison.

The uncertainty in deposition caused by fin impaction is small in absolute terms

(note the scale of the y-axis), and is caused mainly by uncertainty about whether a

rectangular slit cascade impactor or the rounded fin edge better approximates the blunt

fin edges. For smaller than 2 µm particles, the upper bound on penetration is that

associated with assuming the cascade impactor geometry described by Equation (2.6)

rather than the rounded fin edge approximation summarized in Equation (2.7). The

situation reverses for larger particles. Uncertainty due to flow approximations and bias

due to the assumption of Stokesian drag are much smaller contributors to the upper and

lower uncertainty bounds.


Pfin

0.90

0.92

0.94

0.96

0.98

1.00

Central EstimateUncertainty Bounds

Figure 2.13: Uncertainty for fin impaction for U = 2 m/s and fin spacing = 4.7 fin/cm.

The uncertainty in impaction on tubes (Ptube) is relatively large (Figure 2.14),

particularly for larger particles and is predominantly caused by whether shielding of tube

51

rows is assumed (leading to the upper bound) or whether Stokesian drag is assumed (the

lower bound).


P tube

0.00

0.25

0.50

0.75

1.00


Figure 2.14: Uncertainty for tube impaction for U = 2 m/s and fin spacing = 4.7 fin/cm.

The uncertainty bounds on penetration associated with gravitational settling are

quite large (Figure 2.15). This is mainly due to the relatively crude way they were

approximated.

52


P G

0.00

0.25

0.50

0.75

1.00


Figure 2.15: Uncertainty for gravitational settling for U = 2 m/s and fin spacing = 4.7 fin/cm.

The unknown nature of the air turbulence in the fin channels leads to significant

bounds on uncertainty associated with deposition by air turbulence impaction. Figure

2.16 shows the contribution of each uncertainty factor described in the last row of Table

2.1 to the to the penetration fraction associated with air turbulence. Increasing the

fluctuating components of velocity cause a significant increase in penetration fraction.

Adding a decrease in the criterion in Equation 2.10 to this change further decreases PT.

Including turbophoretic deposition (based on the duct turbulence parameters) only

slightly decreases PT. This mechanism likely causes even less deposition in a real system

because the turbulence intensity in the duct is much less than in the fin spacing. The

assumption of Stokes drag on the particle decreases PT even further. The numerical

uncertainty contributed less than 1 % of absolute uncertainty to PT and was not included

in this analysis. The lowest bound on PT at this velocity suggests that it could contribute

to deposition much more than the best estimate suggests.

53


P T

0.00

0.25

0.50

0.75

1.00

Best EstimateUncertainty Bounds

Increase u' and w'by 50 %

Decrease Eqn 2.10criterion by 50 %Includeturbophoresis

Assume Stokeslaw for drag

Figure 2.16: Uncertainty in air turbulence impaction for U = 2 m/s and fin spacing = 4.7 fin/cm.

The overall uncertainty bounds are shown in Figure 2.17. The uncertainty bounds

were calculated by substituting the upper and lower bounds for each deposition

mechanism into Equation (2.21). The uncertainty bounds for particles smaller than 10

µm are those associated with uncertainty on fin edge-impaction. At this velocity and fin

spacing, most of the uncertainty for particles greater than 10 µm in diameter is caused by

uncertainty in gravitational settling with a significant contribution from deposition by

impaction on tubes. Turbulent impaction contributes to the uncertainty for particles

larger than 40 µm.

54


Dep

ositi

on F

ract

ion

(%)

0

25

50

75

100Best EstimateUncertainty Bounds

Figure 2.17: Overall uncertainty bounds for U = 2 m/s and fin spacing = 4.7 fin/cm.

2.7.2 Non-isothermal conditions

To examine the effect of cooling and condensing, simulations were performed for

2 m/s and 4.7 fin/cm at three conditions: isothermal (θ = 1), cooled but not condensing (θ

= .9325, Tw > Tdp where Tdp is the dew point of the air in the coil), and cooled and

condensing (θ = .9325, Tw < Tdp). The thickness of the water on the coil was

approximated to be a uniform layer 114 µm thick on all heat-exchanger surfaces. This

roughly corresponds to measured data from the test heat exchanger described in Chapter

3. The results of these simulations appear in Figure 2.18.

Figure 2.18 indicates that cooling the coil adds a small amount of deposition (2 - 4

percentage points) for submicron particles, indicating that thermophoresis is an important

deposition mechanism for smaller particles. Condensing moisture does not significantly

increase deposition above the cooled case for these small particles. Cooling adds a small

amount of deposition (~2 percentage points) for 1 – 10 µm particles, and condensation

adds significantly (10 – 20 percentage points) to deposition for this particle size range.

The increased deposition that resulted from condensation is to be expected as the fin

55

thickness is tripled. Although this decreases Stkeff, fin for particles, it increases the fraction

of incoming air that can be swept of particles, i.e. increasing the tfin/w factor in Equation

(2.4). Particles larger than 10 µm in diameter are also influenced by the presence of

condensation which is caused by a decrease in the fin spacing, w. This narrowing of the

channel might lead to changed gravitational settling, but the shape of the water layer

would have a large influence on the accuracy of the results from Equation (2.8). A more

minor contribution to increased deposition is the greater impaction on tubes because of

the small increase in tube diameter. Turbulent impaction does increase as a result of the

smaller fin channel, although this increase only affects the largest particles. These

particles will also likely deposit by other mechanisms.


Dep

ositi

on F

ract

ion

(%)

0

20

40

60

80

100Isothermalθ = 0.9325θ = 0.9325, Condensing

Figure 2.18: Comparison of deposition on isothermal coil, cooled coil, and cooled and condensing coil for U = 2 m/s and fin spacing = 4.7 fin/cm.

To examine the effect of temperature difference on thermophoretic deposition, PTh

was determined for four values of θ that roughly correspond to a 5, 10, 15 and 20 K

temperature difference between the heat exchanger and the air. The results in Figure 2.19

show that PTh ranges from 0.97 for very small particles and a large temperature difference

56

to greater than 0.99 for a small temperature difference and larger particles. The

dependence of PTh on particle size is a minor effect and occurs because of the presence

of Kn in Equation (2.25) .


The

rmop

hore

tic P

enet

ratio

n Fr

actio

n, P

Th

0.95

0.96

0.97

0.98

0.99

1.00

θ = 0.9831θ = 0.9662θ = 0.9493θ = 0.9325

Figure 2.19: Penetration by thermophoresis as a function of θ for U = 2 m/s and fin spacing = 4.7 fin/cm.

Diffusiophoresis is particle-size independent and, over the range of conditions

that are common in HVAC heat exchangers, it is a very weak deposition mechanism.

Penetration only accounting for diffusiophoresis, as a function of relative humidity, is

shown in Table 2.4. In all cases, even a close-to-saturated condition with a small θ

causes less than 1% deposition by diffusiophoresis, which suggests that this mechanism

can be neglected, particularly for larger particles where other deposition mechanisms will

completely dominate deposition.

57

Table 2.4: Diffusiophoretic penetration as a function of air relative humidity, φ , for θ = 0.92, U = 2 m/s and fin spacing = 4.7 fin/cm.

Relative Humidity

φ

Diffusiophoretic Penetration Fraction

Pdf

0.60 0.9986

0.70 0.9983

0.80 0.9979

0.90 0.9976

2.7.3 Comparison with Muyshondt et al. (1998)

The results of the model were compared with the simulations of Muyshondt et al.

(1998) for two velocities (Figures 2.20 and 2.21). For the purposes of comparison, the

deposition on the heat exchanger simulated by Muyshondt et al. (see Table 2.3) was

evaluated with the present model. Muyshondt et al. did not include impaction on the fin

edges or gravitational settling on corrugated fins, so these deposition mechanisms were

neglected for this comparison (specifically, PG and Pfin were fixed at unity). Only

impaction on tubes and air turbulence are likely to cause impaction of supermicron

particles in this comparison.

Although both models have a similar shape and show relatively little deposition

for small (< 10 µm) particles and rapidly increasing deposition for larger (> 10 µm)

particles, there are substantial differences between the models. The present model

predicts less deposition than Muyshondt et al., and shows fin-spacing independence for

all but the very largest particles. Impaction on tubes is the only mechanism causing

significant loss of particles in the present model, although air turbulence contributes for

58

the largest particles. Muyshondt et al. show minimal, but non-zero, deposition for small

particles. It is not clear what deposition mechanisms are causing deposition of these

particles. Their relaxation times are sufficiently small that they are unlikely to deviate

from fluid streamlines significantly. The gradual slope of the Muyshondt et al. work

suggests that the only deposition mechanism that causes particle loss is impaction on

tubes. This is further substantiated by the fact that their work shows similar, and in some

cases lower deposition fractions for higher fin pitches, which would only make sense if

the width of the fin channel had no effect on deposition. This suggests that air

turbulence impaction does not play a role in their model. The differences between

deposition fractions at various fin pitches are sufficiently small that they may be a

consequence of numerical uncertainty in their simulation of turbulence. Muyshondt et al.

completed 103 - 104 simulations for each particle size where I found that 107 runs were

required to obtain less than 1% difference in penetration between successive runs at the

same conditions.

Aerodynamic Diameter (µm)1 10 100

Dep

ositi

on F

ract

ion

(%)

0

20

40

60

80

1003.9 fin/cm4.7 fin/cm5.5 fin/cm3.9 fin/cm4.7 fin/cm5.5 fin/cm

Muyshondt et al. (1998)PresentModel

Figure 2.20: Comparison of present model and the work of Muyshondt et al. (1998) as a function of fin spacing for U = 1.5 m/s.

59

Aerodynamic Diameter (µm)1 10 100

Dep

ositi

on F

ract

ion

(%)

0

20

40

60

80

1003.9 fin/cm4.7 fin/cm5.5 fin/cm3.9 fin/cm4.7 fin/cm5.5 fin/cm

Muyshondt et al. (1998)PresentModel

Figure 2.21: Comparison of present model and the work of Muyshondt et al. (1998) as a function of fin spacing for U = 2.3 m/s.

Although this comparison neglected the impact of deposition because of

gravitational settling and impaction on fin edges, these mechanisms do occur in many

heat exchangers. The deposition fraction results depicted in Figures 2.4 and 2.5 are likely

more descriptive of particle removal in real heat exchangers.

2.8 Conclusions and Implications of Model Results

It is clear that of the particles that reach the coil, larger particles (>10 µm) are

most likely to deposit. Gravitational settling and impaction on tubes contribute to

deposition of these particles. Air turbulence does not add to deposition significantly,

especially for low velocities and small fin spacings. Deposition of coarse mode (1 – 10

µm) particles is caused primarily by impaction on fin edges. Gravitational settling also

contributes, especially at lower velocities. Submicron particles (those as small as 0.01

µm) are predicted to have low fractional deposition on HVAC heat exchangers as their

dominant deposition mechanism is Brownian diffusion and residence times in the coil are

sufficiently short that particles do not have time to diffuse across the fin channels.

60

The addition of cooling (without condensation) leads to a small increase in

deposition for all particle sizes. The biggest relative change occurs for submicron

particles. Although deposition fractions are still less than 5% on a cooled heat exchanger

for these particles, there are often two or three orders of magnitude more of these

particles (in number concentration) in indoor air (Riley et al., 2002), so they may make

up a non-negligible fraction of deposited material on coils. This is discussed in more

detail in Chapter 5. The addition of condensed water on heat-exchanger surfaces leads to

additional deposition by all mechanisms except for gravitational settling. The biggest

relative effect is for coarse mode particles. The effective increase in fin thickness and

corresponding decrease in fin spacing, leads to an approximate doubling of deposition by

fin impaction for these particles. In addition to increased deposition, moisture may also

make an environment suitable for microbiological growth. This is discussed in more

detail in Chapter 4.

The absolute bounds on the uncertainty of the model are typically relatively small

and they do not change the shape of the deposition fraction curves. The dominant

uncertainty for deposition of 1 – 10 µm particles is that associated with assuming a fin-

edge shape and consequent flow condition. A simple CFD study of the flow around a

blunt fin edge might reduce this uncertainty, but the importance of turbulence in the duct

flow leading up to the fin edge complicates determining the inputs to the CFD code and

may affect the applicability of CFD results.

The dominant uncertainty associated with deposition of larger particles has to do

with the modeling of gravitational settling. It would be useful to conduct specific studies

or simulations examining gravitational settling in a similar geometry to fin corrugations

to reduce the uncertainty associated with this mechanism.

61

More detailed simulations that allow a determination of the flow condition and

turbulence parameters in the fin channels would greatly improve understanding of the

mechanisms of turbulent deposition. Improving the turbulence information in the model

would constitute a significant challenge. The parameters that would greatly improve the

accuracy of predicting turbulent impaction (and inform the estimation of the other

deposition mechanisms) are 1) estimating how far the duct turbulence persists into the fin

channels 2) understanding the nature of any turbulence that arises from the microscale

and macroscale surface roughness elements in the fin channel and 3) predicting the

boundary layer development and growth in the channel. A CFD model with a fine

enough mesh to account for roughness elements would be extremely computationally

intensive and it would be a challenge to specify turbulence parameters at the inlet to the

fin channels. Furthermore, accurate CFD modeling would have to account for the

complexities associated with boundary layer development, particularly because the

boundary layers are continually being restarted by the roughness elements on the fins.

Experiments to validate the model discussed here, as well as future models, are

presented in Chapter 3. A goal of experiments is to determine whether the modeling is

accurate for a typical particle size range, geometry, and flow conditions. It is desirable

that the experiments be sufficiently accurate to capture the shape of the deposition

fraction curves (i.e. Figure 2.5) and also that some experiments occur at sufficiently high

velocities and large particle sizes to capture the increases that are suggested by the model

for gravitational settling and impaction on tubes. Such experiments are described in

Chapter 3.

62

CHAPTER 3: MEASURING PARTICLE DEPOSITION ON HVAC HEAT EXCHANGERS

3.1 Introduction

Although the modeling described in Chapter 2 is a potentially useful predictor of

important deposition mechanisms, many models tend to underpredict particle deposition

in real systems. This is often due to the effects of surface roughness or inhomogeneities

associated with air turbulence. Because the modeling of particle deposition in complex

geometries has not proven reliable, most of the work in this dissertation is focused on a

series of experiments to directly measure particle deposition associated with fin-and-tube

heat exchangers.

The purpose of this work described in this chapter is to directly measure particle

deposition on an HVAC heat exchangers. The results can serve to validate the simulation

work in Chapter 2 and also to inform the discussion in Chapters 4 and 5 on the indoor air

quality and energy consequences of heat exchanger fouling. The central question being

answered by the experiments is this: given an air speed, what is the likelihood that a

particle of a given size will deposit on a typical HVAC heat exchanger? Additional

experiments were designed to assess the following questions:

• What is the impact of a cooled coil on particle deposition relative to an isothermal

system?

• How much additional deposition occurs when the coil is condensing moisture

from the air stream?

63

• What is the relationship between mass deposited and pressure drop for a typical

HVAC heat exchanger?

These questions are designed to permit progress towards a more complete understanding

of the HVAC heat exchanger fouling problem.


There has been very little published experimental work on the deposition of

particles on air-side heat exchangers. Gudmundsson (1981) summarizes several

experimental studies on particle deposition on heat-exchanger surfaces. Almost all of the

studies that he cites investigate liquid, rather than gas, fluid systems. These have limited

application to HVAC heat exchanger fouling because of the importance of precipitation,

phase change, and corrosion in liquid-side heat exchangers. Particle transport to the

walls is not the limiting step in any of the studies, although it is for gas heat exchangers.

Townes et al. (1981) studied particle deposition on in ceramic-brick heat exchangers used

in large combustion boilers. They found significant fouling from fly-ash particles (MMD

= 6.27 µm with a range of 0.5 – 130 µm). The geometry of this system (long horizontal

tubes) and the high temperatures involved make it hard to directly apply the results to

HVAC heat exchangers.

Bott and Bemrose (1983) and Bott (1995) present experimental fouling data that

are most directly applicable to HVAC heat exchangers. They measured deposition of 3 –

30 µm calcium carbonate particles on a circular fin-and-tube heat exchanger with

64

relatively thick fins (0.41 mm), large tubes (25.4 mm), and a comparable (to HVAC heat

exchangers) fin spacing (4.1 fin/cm). Their results show changes in two dimensionless

parameters that represent mass- and heat-transfer resistances. The friction factor, f (τ/ρu2,

where τ is the shear stress at the wall), increased to about twice its initial value and the

Colburn J factor (StPr⅔ where St = AcNTU/A where Ac is total heat exchanger surface

area, A is the net free-flow area of the heat exchanger, and NTU are the number of heat

transfer units which is a log mean temperature difference between the refrigerant and the

air and Pr is the air Pandtl number = ν/α, where ν is the kinematic viscosity of the air

and α is the thermal diffusivity of the air), decreased about 10 % over 1600 minutes of

testing. The dust concentrations considered ranged from 0.65 - 1.5 g/m3 – these levels

are 4 or 5 orders of magnitude larger than dust concentrations in typical indoor

environments. Depending on dust injection rates and air velocities, fan power

requirements roughly doubled to maintain the same flow rate through the system,

suggesting serious operating consequences of fouling. Visual inspection of their system

found the most deposited material on the leading edge of the fins, upstream of the tubes,

and on the fins, in the wake area of the tubes.

3.3 Experimental Methods

I conducted three main groups of experiments, which are discussed below. Much

of the experimental work focuses on determining particle deposition fraction on a test

heat exchanger (referred to as the coil). These experiments are particle-size resolved and

were conducted at three air velocities. An additional set of experiments extends this

work to non-isothermal (both cooled and cooled-and-condensing) conditions at a single

65

velocity. The same apparatus was later used, with different fouling agents and analysis

methods, to determine the pressure drop associated with fouling.

3.3.1 Measuring particle deposition fraction

The apparatus used for these experiments is depicted schematically in Figure 3.1.

Each component of the experiment is discussed in detail below. Experimental protocols

are summarized here and reported in detail in Appendix A.

Figure 3.1: Schematic of experimental apparatus.

Monodisperse spherical particles are generated with a vibrating orifice aerosol

generator (VOAG, TSI Model 3450). The chemical constituents of the particles are

isopropanol, ammonium fluorescein (5 g fluorescein in 1 L 0.1M ammonium hydroxide),

and oleic acid. The particle solution is pumped through a vibrating orifice (20 or 35 µm

in diameter, depending on particle size desired) with a positive displacement high-

pressure pump (Rainin model Rabbit HP) at the flow rates recommended in the VOAG

manual (TSI, 1987), adjusted according to the author’s experience with this device. The

initial size of the droplets can be determined from geometry (Hinds, 1999) as follows:

66

136 L

dQd

fπ

=

(3.1)

where dd is the initial droplet diameter, QL is the volumetric flow rate of the particle

solution, and f is the oscillation frequency of the vibrating orifice. Note that Equation

(3.1) is independent of the orifice diameter; however, bigger orifices require higher liquid

feed rates, QL, and lower frequencies, f, to produce stable monodisperse suspensions.

This translates to larger diameter particles. Typical initial particle sizes were in the size

range of 15 – 60 µm. To aid in dispersal and to prevent coagulation, dispersion air flow

(typically 5 - 20 L/min) is provided at the orifice.

The dispersion air propels the particles into the drying column and charge

neutralizer (TSI model 3054). The charge neutralizer uses a KR-85 gaseous source that

is designed to remove most of the electrical charge on particles that occurs with most

generation methods, including the vibrating orifice. The particle residence time in the

neutralizer causes the particles to emerge with a Boltzmann distribution of charge (Hinds,

1999). Because I am not interested in electrostatic deposition, the test coil and duct

system (described below) were made up of electrically conductive materials and were

grounded through the data collection system.

Most of the isopropanol has evaporated from the particle by the time it leaves the

neutralizer, reducing the particle size to

( )136 1L IPA

dQ f

dfπ

− =

(3.2)

67

where fIPA is the volume fraction of the particle solution that is made up of alcohol.

The particles generated by the VOAG are sized with an aerodynamic particle sizer

(APS, TSI model 3320) in two locations: after a 1 m (3 ft) length of tube at the outlet of

the neutralizer/drying column and in the center of the test duct 13.4 m (44 ft) upstream of

the test coil. The APS uses a filtered sheath air flow to accelerate particles between two

closely spaced laser beams. The time between when the first and the second beam is

broken is related to the particle aerodynamic diameter. The APS is factory calibrated

with polystyrene latex (PSL) particles (TSI, 1998).

Although it produces a particle concentration distribution, the APS was used for

sizing purposes only. The APS is capable of measuring particles with aerodynamic

diameters over the range of 0.5 to 20 µm. The APS was calibrated twice over the two

years that experiments occurred, the first time was a field calibration with 3 µm PSL

particles (Duke Scientific model R300) and the second time was a factory calibration.

The particles are mixed with a high efficiency particle arresting (HEPA) filtered

air stream designed to eliminate ambient particles. Tests were done to confirm that

effectively all ambient particles were removed. Even when duct leakage caused particle

intrusion, blank experimental runs confirmed that the ambient particles did not affect the

fluorometric analysis described below. The air was then sent into 24 m (80 ft) of straight

15 cm (6 inch) square duct. The duct air velocity could be varied continuously over the 1

- 5 m/s (200 - 980 ft/min) range of interest. This velocity range corresponds to Reynolds

numbers of 10200 to 50800 in the duct (Reduct) and Reynolds numbers of 150 to 740 in

the heat exchanger core (Refin). From Tables 1.1 and 2.1, this indicates that the tested

68

heat exchanger is similar to those used in residential and small commercial applications.

Several honeycomb flow straighteners were used to promote fully developed turbulent

flow with a uniform concentration of particles at the test coil.

The velocity pressure (total pressure minus static pressure) was measured 6

diameters (0.9 m or 3 ft) upstream and 12 diameters (1.8 m or 4.5 ft) downstream of the

test coil with a pitot tube and digital micromanometer (Energy Conservatory model DG-

3) before and after each experiment. The velocity pressure is related to the air velocity

by the Bernoulli equation:

2 air

Puρ

= (3.3)

Where u is the local air velocity, P is the velocity pressure and ρair is the air density

(calculated assuming that air is an ideal gas). The pressure measurement was made

sixteen times across the duct in the locations depicted in Figure 3.2 and averaged in

accordance with the equal-area technique (ASHRAE, 2001).

The velocity measurements were also used to determine whether there was

significant leakage around the coil. More than 1% leakage (the uncertainty in velocity

measurement is about 1 - 2% with this technique) indicated that the test coil was not

adequately sealed. When this occurred, the coil seal was checked and the velocity

measurements were repeated. Pitot static measurements were also made in numerous

locations on the centerline of the duct to determine the duct pressure drop for use in

calculating the duct friction velocity.

69

1.9 cm

1.9 cm

3.8 cm

3.8 cm

3.8 cm1.

9 cm

1.9

c m

3.8

cm

3.8

cm

3.8

cm

15 c

m

Figure 3.2: Cross section of duct showing measurement points for pitot tube air velocity measurement.

The particle-laden air then passes through an experimental evaporator-type heat

exchanger, which consists of a 4.7 fin/cm (12 FPI) coil that entirely fills the duct. The

geometric parameters of the test coil geometry are summarized in Table 3.1. Each set of

refrigerant tubes is spaced 2.5 cm (1 inch) apart with an associated staggered line 2.1 cm

(0.86 inch) deeper into the coil (nset = noffset = 2, nrow = 4). The test heat exchanger has 72

fins and is very similar to the one depicted in Figure 2.1. With the exception of its small

face area of 0.025 m2, is typical of heat exchangers used in HVAC systems. The coil was

installed in the duct system with closed cell adhesive foam and bolted and clamped in an

aligned position before each experiment. The seal leakage was verified to be negligible

before each experiment. The static pressure drop across the coil was measured before

and after each experiment with a pitot tube and a micromanometer.

70

Table 3.1: Test heat exchanger geometric parameters.

Symbol Parameter Dimension mm (inch)

tfin Fin thickness 0.114 (0.0045)

w Center-to-center fin spacing 2.12 (0.083)

dtube Tube outer diameter 9.53 (0.375)

wtube Center-to-center tube spacing 25.4 (1.00)

z Fin depth 44.0 (1.73)

h Fin corrugation average height 1.50 (0.0591)

y Fin corrugation width 1.00 (0.0394)

Tube Geometry

nset Number of sets of tubes 2

noffset Number of offset tubes per set 2

nrow Number of tube rows 4

Surface Areas m2 (ft2)

Afin Total fin surface area 0.955 (10.3)

Atube Total tube outer surface area 0.109 (1.18)

Particle air concentrations were measured upstream and downstream of the test

heat exchanger by isokinetically sampling the air onto 47 mm (1.85 in.) 0.8 µm filters

(Osmonics model E08BG0470) held in Teflon™ filter holders. The isokinetic nozzles

(Apex Instruments) had a stainless steel shank, a tapered entry, and a gentle bend. The

nozzle inner diameter ranged from 4.42 - 4.67 mm (0.174 – 0.184 in.) Before and after

each experiment, the local velocity directly in front of each nozzle was measured with a

pitot tube and digital micromanometer. The isokinetic sampling flowrate was determined

71

by the relationship Qs,iso = Anozzleu where Qs,iso is the sampling flow rate that would lead

to isokinetic sampling, Anozzle is the nozzle cross sectional entry area, and u is measured

local velocity. Once the target sampling flow rate was determined, the flow through the

nozzle and filter was set to this value using a mass-flow controller (Sierra Model

Sidetrack III 0.040/0.055) or variable flow air pump (custom made for Lawrence

Berkeley National Laboratory, variable over the range of 1 – 4 L/min). The sampling

flowrate, Qs, for each nozzle was measured with a bubble flow meter (Sensidyne model

Gilian Gilibrator II) before and after each experiment. Pumps were grouped together to

obtain higher flow rates when necessary.

Although the goal was to achieve isokinetic sampling, drift in the pump and mass

flow controller flows over the course of an experiment did not always make this possible.

For this reason, the experimental work of Belyaev and Levin (1972, 1974) was used to

adjust the sampled particle concentrations for aspiration efficiency, defined as the ratio of

the concentration of particles transmitted though the nozzle to the concentration of

particles in the ambient environment:

11 1 11 2 0 617

s,isoasp

s,isosnozz

s

QQQ

Stk .Q

η

= + − − + +

(3.4)

where ηasp is the aspiration efficiency and Stknozz is the particle Stokes number with the

nozzle entry diameter as the characteristic dimension. In this expression, particle drag is

assumed to follow Stokes law, which is presumed to be valid here because Qs,iso/Qs was

72

typically 0.95 - 1.05 and hence the particle velocity is never greatly different from the air

velocity.

Upstream of the coil, the particle concentration in the duct was measured on the

duct centerline at two locations 2 m and 0.5 m from the coil. Concerns about uniformity

of mixing led to later experiments that had five nozzles and filters installed at the 0.5 m

upstream location in the pattern indicated in Figure 3.3. Downstream of the coil, three

nozzles were installed in a linear sampling array 2.6 m (8.5 ft) from the coil. This

location was chosen to strike a balance between allowing for particle mixing in the duct

and limiting the confounding effect of deposition to duct surfaces. Initially,

measurements were made with the downstream sampling probes positioned 0.76 m (2.5

ft) away from the test heat exchanger and the non-uniformity in air concentration was

observed to be very large. The use of three downstream sampling nozzles was an attempt

to compensate for non-uniformities associated with incomplete mixing. Nozzles were

installed on the vertical centerline at respective locations of 25.4 mm (1.0 in), 76.2 mm

(3.0 in), and 127 mm (5.0 in) from the top of the duct. Pilot sampling measurements

indicated that there was significant variation in air concentration for larger particles and

high velocities in the vertical direction, rather than the horizontal direction, likely because

of a small gap above and below the coil. Sampling and measurement locations are

summarized in Table 3.2.

73

15 c

m

2.5 cm

5.1 cm

2.5 cm

5.1 cm

2.5

cm

5.1

cm

2.5

cm

5.1

cm

Figure 3.3: Sampling locations immediately upstream of duct.

Table 3.2: Summary of particle sampling locations.

Distance from Mixing Box Outlet [Duct Diameters]a

Particle sizing (with APS) 52

First upstream isokinetic nozzle 117-127

Main upstream isokinetic nozzles 137

Test coil 140

Downstream isokinetic nozzles 157

End of test duct 160

aDuct diameter is 0.15 m (6 in).

After each experiment, the filter, nozzles, and filter holders were subjected to

extraction and fluorometric analysis. A bath containing 13.4 g/L sodium phosphate

buffer solution was used to extract the fluorescein on the sample filters. The nozzles and

filter holders were also washed with the buffer solution. The fluorescence of the

74

resulting solutions was measured with a fluorometer (Turner Designs model TD-700) to

determine air particle concentrations. The fluorometer was calibrated monthly with the

five point procedure specified in the fluorometer manual (Turner Designs, 1997). The

nozzles, filter holders, and filters were washed repeatedly with sodium phosphate buffer

until there was less than a 0.4 ng/mL (the assumed accuracy of the fluorometer, discussed

below) difference between subsequent readings. Typically three repetitions were

required. Dilution with additional sodium phosphate buffer was done as needed to keep

the fluorescence readings within the range of the fluorometer. The air concentration at a

given point was determined from this equation:

( )b, filter b, filter b,nozzle b,nozzle b,holder b,holder

airs asp

C V C V C VC

Q tη+ +

= (3.5)

where the Cb and Vb variables are the measured fluorescein concentrations and buffer

volumes for the filter, nozzle and filter holder, respectively, and t is the experimental

duration, defined as the period of time that particles were being injected into the mixing

box.

After each experiment, the test coil was removed from the duct and a gasketed

plate was attached to a flange on the leading edge side of the coil. With the plate

horizontal and underneath the coil, 650 mL of sodium phosphate buffer was added

through the plate with a syringe to extract the first 5 mm of the leading edge of the coil.

After soaking for 30 - 60 minutes, the coil was drained and the resulting solution

measured with the fluorometer. The procedure was repeated a second time. The rest of

the coil was then extracted with 1500 mL of buffer poured over the top of the coil and left

75

to soak for 30- 60 minutes, while being agitated frequently. The effluent was measured

with the fluorometer, diluted with measured amounts of buffer, as necessary to be below

full scale on the fluorometer. The whole-coil extraction was repeated until there was less

than 1500 ng (1 ng/mL fluorometer reading) remaining on the coil. For a typical

experiment this amount represented < 0.01% of the deposited mass or less.

3.3.2 Measuring deposition fraction in a non-isothermal system

Questions about how a cooled and condensing coil increases deposition led to

additional experiments. The purpose of these experiments was to determine the extent of

the increase of particle deposition due to the thermal mechanisms described in Chapter 2.

The methods for these experiments were similar to those described above, with

the following differences. A second test coil, geometrically identical to the coil described

in Table 3.1, was modified to allow for pumping of water through the refrigerant tubes.

It also had condensate drain lines installed in the bottom of the coil. These condensate

lines drained into a container for capture. A water pump and insulated ice-water storage

container were installed such that water could be continuously pumped through the coil.

Surface contact thermistors (Omega model 2252) were attached to the exterior of the

copper refrigerant tube at the inlet and outlet of the coil and insulated with 25.4 mm (1 in)

closed cell pipe insulation in accordance with refrigerant temperature measurement

guidelines described in Siegel and Wray (2002).

Narrow profile air temperature sensors (Omega model 2252 thermistors) were

installed in the centerline of the duct 25.4 mm (1.00 in) downstream of each isokinetic

sampling point. Relative humidity was measured with calibrated resistive RH sensors

76

(Vasailia model HMD) at two locations: 1.2 m (4 ft) downstream from the mixing box

and at the end of the system. The purpose of these sensors, and the associated air

temperature measurements, was to establish the humidity ratio before and after the coil.

The pressure drop across the coil was measured continuously with a micromanometer by

averaging the static pressure 0.5 m upstream and downstream of the coil with deburred

pressure taps installed on the center of all four walls of the duct.

A schematic of the apparatus, as well as measurement locations for temperature

and relative humidity, appears in Figure 3.4.

Water inlettemp.

Icewater

Insulated container

Waterpump

Wateroutlettemp.

Air RH and temp.(entering humidity

ratio)

Coil pressure drop

Air RH andtemp.

(temperaturemeasured

three placeson verticalcenterline)

Centerlineair temps.

Condensatecapture

Figure 3.4: Schematic of measurements and sensor locations for cooled and cooled-and-condensing coil experiments.

The protocol for these experiments was similar to that described in Appendix A.

One key difference was that cold water was circulated through the test heat exchanger by

means of a pump. The flow of chilled water was initiated 30 minutes prior to particle

generation to allow the coil thermal mass to come to a steady-state temperature, and for

condensation to build up and begin draining for the condensing experiments. The initial

77

condensate water was tested to confirm that there was no fluorescein contamination from

the drainage lines or other parts of the capture system.

Ice was added to the insulated container over the course of the experiment to

maintain the desired temperature and the air pressure drop across the coil was monitored

to confirm that the presence or absence of condensation was consistent with the particular

experimental goal.

The analysis of the experimental data was also very similar to the original

experiments with the addition of the collection and analysis of the measured temperatures

and relative humidities. The relative humidity, φ, and associated temperature

measurements were manipulated using psychrometric relationships to determine humidity

ratio and dew point. Of specific interest are the humidity ratio upstream of the test heat

exchanger, Wup, the humidity ratio downstream of the duct, Wdown, the temperature of the

air immediately upstream and downstream of the coil, the dew point temperature of air in

the heat exchanger, Tdp, and the temperature of the heat exchanger, Twall.

The partial pressure of water vapor, PH2O, can be expressed as follows:

2 2H O H O,satP Pφ= (3.6)

Where PH2O,sat (Pa) is the saturated partial pressure obtained from a curve fit (ASHRAE,

2001):

2 3

2

lnc8 c9 c10 T c11 T c12 T c13 TT

H O,satP e + + ⋅ + ⋅ + ⋅ + ⋅ = (3.7)

78

where c8 = -5.8002206 × 103, c9 = 1.3914993, c10 = -0.48640239 × 10-1, c11 =

4.1764768 × 10-5, c12 = -1.4452093 × 10-8, and c13 = 6.5459673 and T is the air

temperature (K).

The humidity ratio of the air, W, i.e., the mass of water per mass of dry air, can be

expressed as follows:

2

2

0 62198 H O

atm H O

PW .

P P=

− (3.8)

where Patm is the total pressure of the air (i.e., atmospheric pressure) which was assumed

to be 101.325 kPa.

The dew point, Tdp, temperature is defined as

( ) ( )

( ) ( )2 2

2 2

2

3 0 1984

ln ln

ln

dp H O,sat H O,sat

.H O,sat H O,sat

T c14 c15 p c16 p

c17 p c18 p

= + + +

+

(3.9)

where c14 = 2.7955 × 102, c15 = 14.526 , c16= 0.7389, c17 = 0.9486 × 10-1, and c18 =

0.4569 are curve fit coefficients from ASHRAE (2001). Note that pH2O,sat is in kPa for

Equation (3.9) and c14 has been changed from the reference to give Tdp in K (instead of

°C).

These psychrometric relationships are used in the analysis to estimate the amount

of moisture present on the coil, and the temperatures of the air and the heat exchanger.

Specifically, the average temperature of air in the coil, T, is defined as (Tup+Tdown)/2 and

79

this quantity is used with Wup to determine Tdp. Table 3.3 summarizes measurements and

measuring locations for psychrometric quantities.

Table 3.3: Summary of temperature and relative humidity measurement locations.

Variables Determined

Distance from Mixing Box Outlet

[Duct Diameters]a

Initial temperature and RH Wup 8

Upstream temperature Tup 138

Inlet and outlet heat exchanger temperature Twall 140

Downstream temperature Tdown 148

Exit temperature and RH Wdown 158

End of test duct 160

aDuct diameter is 0.15 m (6 in).

3.3.3 Methods for experiment to determine fouling to pressure-drop relationship

The final experiment was very different from the earlier two experiments. The

purpose was to produce a relationship between deposited material and fouling

consequences. Anecdotal accounts and fieldwork revealed that airborne dust was a

common fouling agent, and the purpose of this experiment was to determine a

relationship between mass of dust deposited and coil pressure drop. The goal of this

experiment is to provide a link between deposition fraction and pressure drop, which in

turn will be related to the energy consequences of heat exchanger fouling in Chapter 5.

To achieve these results, a sample of Society of Automotive Engineers (SAE)

standard coarse test dust (AFTL Laboratories SAE Coarse) was used. This dust was

80

selected because, although coarser than ASHRAE standard test dust, it better reflects the

particle size distribution of material found during fieldwork in deposits on evaporator

coils. SAE coarse test dust has a MMD of 23 µm (see Figure 3.5) and a particle density

of 2.5 g/cm3.

Aerodynamic Diameter [µm]

1 10 100

Cum

ulat

ive

Mas

s Fra

ctio

n [%

]

0

20

40

60

80

100

Figure 3.5: SAE coarse dust fractional mass distribution function.

The apparatus used for this experiment is depicted in Figure 3.6. A fan was used

to move air through a 0.15 m (6 inch) square duct. Twenty-five gram (0.055 lb) batches

of standard test dust (AFTL Laboratories SAE Coarse) were weighed on an electronic

mass balance (Satorious model H110V20) and sequentially introduced to the duct 4.3 m

(14.1 ft) upstream of the test coil. The introduction of each 25 g batch of test dust is

referred to as a “dust insertion” The dust was introduced with a flour sifter to promote

uniform mixing of the dust in the duct. The dust was sampled on previously weighed 25

mm (1 in) filters installed in samplers that were positioned the duct centerline 0.9 m (36

in) upstream and 0.9 m (36 in) downstream of the duct and. The nozzles were connected

to vacuum pumps and calibrated orifice flow meters (Bryant Inc.) and the pressure across

81

each orifice was measured with digital pressure sensors (Energy Conservatory Model

APT-2) and continuously recorded.

SampleFilters

Sample Pumps

CoilAirflow

TestDust

Figure 3.6: Apparatus for dust experiment.

The experiment was designed such that filter sampling would be approximately

isokinetic, but the pressure drop of the filter, and consequently the flow through the pump

dropped over the course of each dust addition as the filter became loaded. The

anisokinetic corrections suggest by Belyaev and Levin (1972, 1974) in Equation (3.4) are

not appropriate for the blunt dust sampler used in this experiment. Instead, the results of

experimental work and calculation procedure presented by Vincent et al. (1985) were

used (their Equations 22-32). Turbulent velocity fluctuations, a required input to the

Vincent et al. model, were based on the DNS data presented by Moser et al. (1999) and

discussed in Chapter 2.

Before and after each dust insertion, the filters were weighed with a mass balance,

and the air concentration was determined to be

0f f ,air

asp s

M MC

Q tη−

= (3.10)

82

Where Mf is the mass of the filter after each dust insertion, Mf,0 is the clean filter mass,

and ηasp is the aspiration efficiency from Vincent et al. (1985).

Additional mass measurements were made of test dust that remained in the sifter

after each dust insertion. At the end of the experiment, dust was also collected and

weighed (using the mass balance) from several locations: the duct surface area directly

under the sifter, the duct surface area directly upstream of both nozzles, from the floor of

the duct between the sifter and upstream nozzle, the upstream nozzle and the coil, and the

coil and the downstream nozzle.

3.3.4 Measurement devices, sensors, and uncertainty

Table 3.4 is a list of all of the sensors and their uncertainty. In the absence of a

calibration or other information, the accuracy of an instrument was considered to be five

times the least count of the instrument. The extraction and measurement of the

fluorescein on the test heat exchanger involved inaccuracies and potential loss of buffer

(due to leakage and spillage) so the uncertainty in this measurement was approximated

using engineering judgment.

83

Table 3.4: Measurements, sensors, and uncertainty.

Measured Quantity Measurement Device Uncertainty Basis

Deposition fraction

Pressure Energy Conservatory DG-3 and pitot tube/APT-2 and pressure taps

±0.1 Pa Manufacturer and recent calibration

Velocity Energy Conservatory DG-3 and pitot tube

2% Repeated measurements of same flow

Sampling pump flow

Sensidyne Gilian Gilibrator ±10 mL/min Comparison to calibrated sources

Fluorescence Turner Designs TD 700 Fluorometer

±0.5 ng/mL Manufacturer and repeated measurements

Fluorescent material on heat exchanger

Turner Designs TD 700 Fluorometer

2%a Engineering judgment

Cooled and condensing coil

Temperature Omega 2252 Thermistor ±0.2 °C Manufacturer and recent calibration

Relative humidity

Vaisala HMD Resistance RH Sensor

2%, φ <0.9 3%, φ >0.9

Manufacturer and recent calibration

Dust deposition

Pump flow Bryant flow nozzle 1% Recent calibration

Mass balance Satorious model H110V20 ±0.001g Frequent comparison to known masses

aBased on assumed maximum spillage of 10mL per 1000mL of buffer.

84

3.4 Experimentally Tested Parameters

The ideal scenario would be to test a wide range of fin spacings and air velocities.

The role of fin spacing was determined to be a lower priority than air velocity because

there was less uncertainty in the simulation results surrounding this parameter. The cost

of additional test heat exchangers was also a factor. The test heat exchangers had a fin

spacing of 4.7 fin/cm (12 FPI). Three duct air velocities were tested: 1.5, 2.2 and 5.1 m/s

(300, 440, 1000 ft/min). These velocities were chosen to represent two typical HVAC

heat exchanger velocities and an upper bound on bulk velocity (to clearly see the impacts

on air turbulence impaction). The lower two velocities compare well with those

simulated by Muyshondt et al. (1998).

The particle size range that was chosen was 1 – 20 µm. It would be desirable to

test both larger and smaller particles, but problems with using the vibrating orifice with a

10 µm orifice prevented generation of very small particles and problems getting very

large particles out of the neutralizer (which has a 90° bend at its outlet) proved difficult to

overcome. The actual size range tested was 1- 15 µm aerodynamic diameter.

For the non-isothermal experiments, it was desired to do three experiments over

the particle size range with a cooled only heat exchanger and three experiments with a

cooled and condensing heat exchanger. Air and coil at temperatures were set at typical

values for HVAC systems: air temperatures of ~ 25 °C and heat exchanger temperatures

of 10 – 15 °C for the cooled only cases and of 4 – 8 °C for the condensing cases. These

values correspond to temperature ratios, θ, of 0.94 to 0.97.

85

The pressure drop experiments were practically challenging because of the high

carbonaceous content of the test dust. This caused the work to be very dirty,

contaminating much of the experimental space. For this reason, a single velocity was

chosen, 2 m/s, because it corresponds to a typical velocity and because approximately

isokinetic sampling could be achieved over the course of each insertion. Dust was

inserted into the system until the pressure drop of the heat exchanger doubled over the

clean heat exchanger. This is the comparison point for other published work (Krafthefter

and Bonne, 1986).

3.5 Analysis

The analysis procedures for deposition fraction calculation for isothermal and

non-isothermal experiments are described below. Additional discussion of the analysis of

the pressure drop experiment data are also presented.

3.5.1 Deposition fraction (both isothermal and non-isothermal)

The deposition fraction, assuming perfect mixing and no deposition on any

surface other than the coil, is defined as:

,

,

1 air down

air up

CC

η = − (3.11)

where η is the deposition fraction, Cair,down is the downstream air concentration, and

Cair,up is upstream concentration. Equation (3.11) assumes that the only difference in

concentration between the upstream and downstream sampling point is due to deposition

on the coil. This is a good assumption for smaller particles at high velocities, but larger

86

particles are affected more strongly by gravitational settling and hence can settle between

the samplers and the coil and appear to increase η. To avoid this problem, a more

accurate relationship was used:

,

duct

coil

air upA

Mt C u dA

η =∫

(3.12)

This is approximated as follows:

,

coil

air up duct

MtC UA

η ≅ (3.13)

Where Mcoil is the mass of fluorescein deposited on coil, t is the experimental duration, U

is the bulk air velocity, and Aduct is the cross-sectional area of the duct. The deposition

fractions found with Equations (3.11) and (3.13) were typically very similar for dp < 5

µm. Equation (3.13) was used because of its increased accuracy for large particle sizes

and is the preferred choice for the results. Equation (3.11) was used to confirm results

and identify obvious measurement errors. Note that the experimental duration, t, factors

out of Equation (3.13) because the upstream concentration, Cair,up, is calculated using

Equation (3.5) in which t appears in the denominator.

3.5.2 Non-isothermal experiments

Additional analysis was required with the cooled and condensing experiments.

The average air temperature of the coil was defined to be the average temperature of the

air entering and leaving the coil. The average coil temperature was determined to be the

average of the refrigerant inlet and outlet temperatures. The presence of condensate on

87

the coil was determined with the pressure drop signal. The amount of condensate on the

coil was determined using Equation (3.14):

( )2

2

dairH O up down condensate

H O

mV W W Q tρ

= − −

∫

& (3.14)

where VH2O is the volume of condensed water on the coil, Wup and Wdown are the humidity

ratios of the air upstream and downstream of the coil, airm& is the mass flow of air

through the system, ρH2O is the density of water, Qcondensate is the volumetric flow through

the condensate drain during the experiment, and the entire expression is integrated over

the experimental duration. Equation (3.14) is approximated by

( )2

2

duct airH O up down condensate

H O

A UV W W t Vρρ

= − − (3.15)

Where Vcondensate is the volume of condensate collected over the experiment. The average

thickness of the water layer on heat-exchanger surfaces is VH2O/Ac, where Ac = Afin + Atube.

3.5.3 Pressure drop experiments

The pressure drop experiments used mass-based analysis techniques. The particle

concentrations upstream and downstream of the coil (calculated with Equation (3.10))

were used in Equation (3.16) to determine the mass that deposited on the coil, M, for each

dust insertion:

dduct

air ,up air,downA

M t ( C C )u A= −∫ (3.16)

88

This is approximated as follows:

air,up air,down ductM t( C C )UA= − (3.17)

The dust insertion time, t, cancels because of its appearance in the denominator of the air

concentration measurements. Aduct was replaced in Equation (3.17) with a corrected area

that took into account two factors. The first was a shielding effect of the nozzle and filter

holder, which was noticeable because of a large amount of dust that deposited directly on

the sampler. This was corrected by subtracting the projected area of the sampler from

Aduct. The second factor corrected for nonuniform mixing across the duct. Despite

attempts to achieve uniform mixing of dust in the duct, the pattern of dust on the floor of

the duct indicated that very little dust deposited near the vertical walls of the ducts.

Measurements across the duct in three locations (two upstream and one downstream of

the test heat exchanger) after the experiments provided information about the effective

mixing width of the dust in the duct and this was used to calculate a corrected Aduct. In

addition to these two factors, additional corrections had to be made to Equation (3.17)

because of dust that deposited on the floor of the duct between the test heat exchanger

and the sampling nozzles:

coil duct ,up duct ,downM M M M= − − (3.18)

where M is the mass of dust lost from the duct between the upstream and downstream

sampling locations as deposited on the coil calculated with Equation (3.17) (with the area

and shielding corrections), Mduct,up is the mass of dust on the floor of the duct between the

dust sampler and the test heat exchanger upstream of the duct, and Mduct,down is the mass

of dust on the floor of the duct between the test heat exchanger and downstream dust

89

sampler. The parameters, Mduct,up and Mduct,down were measured at the end of the

experiment and assumed to be constant for each dust insertion.

3.6 Results

The results for isothermal deposition fraction experiments, non-isothermal

deposition fraction experiments, and dust deposition experiments are discussed below.

Tabulations of experimental results appear in Appendix B.

3.6.1 Isothermal deposition fraction

Deposition fraction vs. aerodynamic diameter curves for three velocities appear in

Figures 3.7 – 3.9. The horizontal error bars show one standard deviation in particle

aerodynamic diameter (an indication of how monodisperse the particles produced by the

vibrating orifice were). The vertical error bars, which are difficult to see for some

smaller particles and lower velocities, reflect the results of a propagation-of-error analysis

on the deposition fraction using the uncertainties described in Table 3.4. The uncertainty

of the deposition fraction results for 5.1 m/s (Figure 3.9) are larger than for the other two

velocities. This is a consequence of the resuspension of deposited particles from previous

experiments. A blank experiment (no particle generation) was completed twice at all

velocities and the resulting fluorescence signal (which only occurred for 5.1 m/s) was

used to evaluate the contribution to uncertainty of resuspended particles. Two sets of

experiments were repeated three times for 3 µm particles at 1.5 m/s and 5.5 µm particles

at 5.1 m/s to test the validity of the uncertainty analysis. These repeated experiments

90

show an overlap of the vertical error bars from each repeated experiment and suggest

good agreement between the predicted and measured uncertainty.

The results of the simulations described in Chapter 2 also appear on each plot.

Aerodynamic Diameter (µm)1 2 3 4 5 6 7 8 10 15 20

Dep

ositi

on F

ract

ion

(%)

0

10

20

30

40ExperimentModel

Figure 3.7: Modeled and measured deposition for 1.5 m/s air velocity.

The general trend is increasing deposition with increasing diameter, with the

exception of 5 – 6 µm particles at 1.5 m/s. There is also increasing deposition with

increasing velocity for most particle sizes. There is very good agreement with the shape

of the model, and reasonable agreement, on average, between the modeled and measured

data. The modeled-measured agreement diminishes with increasing air velocity. The

simulations, with a few exceptions at 5 – 6 µm at 1.5 m/s air velocity and 2 – 3 µm at 5.1

m/s air velocity, tend to underpredict the measured deposition fractions.

91


Dep

ositi

on F

ract

ion

(%)

0

10

20

30

40ExperimentModel



Dep

ositi

on F

ract

ion

(%)

0

10

20

30

40ExperimentModel


The difference in deposition fractions calculated with Equation (3.11) and

Equation (3.13) was negligible (typically less than 5%) for particles up to 2.5 µm in

diameter, significant (10 – 20%) for particles between 2.5 µm and 7.5 µm, and typically

greater than 40% for particles greater than 7.5 µm. Equation (3.11) always predicted

greater deposition, which is consistent with particles depositing by gravity and in the

92

separation region downstream of test heat exchanger. All results reported here are

calculated with Equation (3.13) with the exception of two points (3 µm at 1.5 m/s and 2.2

µm at 5.1 m/s) because of problems with the coil extraction for those experiments. The

deposition fraction for those two cases was calculated with Equation (3.11) with a

correction based on the difference in the results of Equations (3.11) and (3.13) for similar

particle sizes and velocities.

The results of three experiments are not reported. They were done with large

particles injected 28 diameters (4.3 m) upstream of the test coil (the motivation was to

limit gravitational settling in the duct of large particles at the lower velocities). These

results, based on a single upstream centerline air concentration measurement, suggested

very high deposition fractions, which suggested the possibility of non-uniform mixing of

particles. To investigate, all subsequent experiments were performed with five filter

samplers upstream of the heat exchanger as depicted in Figure 3.3. Injecting the particles

so close to the heat exchanger did not allow for uniform mixing of particles: the variation

between air concentrations across the duct cross section ranged from 5 to 30%.

Subsequent experiments with particles injected at the mixing box showed uniform mixing

for particles less than 5 µm and slight variability for larger particles (< 5% difference

between measurement points on the cross section).

The coil was extracted in two sections. The first 5 mm closest to the leading edge

of the fins was extracted separately from the rest of the heat exchanger. The fraction of

particles that deposited on or near the leading edge of the heat exchanger varied

considerably (from 30 to 75 %) between experiments. The fraction of particles that

deposited near the leading edge for each experiment is listed in Table B.2 in Appendix B.

93

This measurement is imprecise because the gasket that was used when sealing the coil

would compress by slightly different amounts, which would change the fraction of coil

that was extracted in the initial measurements. Also, although every attempt was made to

keep the heat exchanger level during extractions, this was not always possible which led

to additional inaccuracies. The model predicts that more than 80 - 90% of the total

deposition should occur on the leading edge for particles smaller than 8 µm in diameter

(because fin edge impaction is the dominant deposition mechanism). This discrepancy

suggests that most of the discrepancy between modeled and measured deposition fraction

is because of additional deposition in the core of the heat exchanger.

3.6.2 Non-isothermal Deposition Fractions

A plot of the deposition fractions for non-isothermal conditions appears in Figure

3.10. The isothermal results are shown for comparison. Temperature and condensation

data are shown in Tables 3.5 and 3.6. Cooling without condensation slightly increases

deposition at all particle sizes. Condensation greatly increases deposition fraction. Two

experiments were conducted with condensation and particle sizes of 9 - 9.2 µm. Only the

experiment with a greater deposition fraction had continuous condensation because of

problems with the temperature control system in the other experiment.

Table 3.5 shows the dew point, air, and heat exchanger (coil) temperatures for all

six experiments. For the three cooling only cases (c1-c3), the heat exchanger was above

the air dew point temperature. For the three cooled-and-condensing experiments (cc4-

cc6) the heat exchanger was below the dew point temperature.

94


Dep

ositi

on F

ract

ion

(%)

0

10

20

30

40

50IsothermalIsothermal ModelCondensingCooling

Figure 3.10: Non-isothermal deposition fraction for 1.5 m/s air velocity.

Table 3.5: Temperature conditions for non-isothermal experiments.

Aerodynamic Temperatures (K) Temperature Experiment Diameter (µm) Dew Point Air Coil Ratio da Tdp T Twall θ = Twall/T

c1 2.68 283.2 296.0 286.0 0.9661

c2 7.61 285.1 295.5 288.6 0.9764

c3 11.93 286.5 295.7 287.3 0.9713

cc4 2.33 281.7 296.1 278.7 0.9411

cc5 9.01 286.5 295.7 285.0 0.9636

cc6 9.14 284.4 295.8 278.1 0.9402

Table 3.6 shows the amount of condensation on that occurred on the heat

exchanger. The “predicted” column reports the volume of water that was removed from

the airstream as inferred from the upstream and the downstream humidity ratios. The

“condensate” column lists the measured volume of condensate. The difference, in the

95

“On Coil” column, is the volume of water remaining on the test heat exchanger. The

small values for the cooled but not condensing cases (c1 – c3) is a measurement of the

uncertainty of the humidity ratio measurements. Almost all of this error comes from

uncertainties associated with the relative humidity sensors. The water layer thickness

represents the average thickness of water on all heat-exchanger surfaces and is defined as

the water volume on the coil divided by the heat exchanger surface area, Ac.

Table 3.6: Moisture volumes for non-isothermal experiments.

Aerodynamic Water Volumes (mL) Water Layer Avg. Experiment Diameter (µm) Predicted Condensate On Coil Thickness (µm)

c1 2.68 7 0 7 7

c2 7.61 -2 0 -2 -2

c3 11.93 9 0 9 8

cc4 2.33 568 245 323 303

cc4 9.01 206 72 134 125

cc6 9.14 660 328 332 312

Table 3.7 shows the modeled and the measured deposition fractions and their

difference for the cooled and the cooled-and-condensing cases. The model systematically

underpredicts the measured deposition fraction by 3 – 5 percentage points for the cooling

only cases. The model underpredicts the deposition fraction for the cooled-and-

condensing cases by 4 – 12 percentage points, although the case with the best agreement

also had about two and a half times less condensation on the coil during the experiment

than the others.

96

Table 3.7: Modeled and measured deposition fractions for cooled-and-condensing experiments.

Aerodynamic Deposition Fraction

Modeled – Measured Difference

Experiment Diameter Modeleda Measured Fractional Absolute da (µm) η (%)

c1 2.68 4.6 8.1 43% 3.5%

c2 7.61 8.9 13.3 33% 4.4%

c3 11.93 10.9 14.8 26% 3.9%

cc4 2.33 8.7 20.7 58% 12.0%

cc5 9.01 23.6 27.4 14% 3.8%

cc6 9.14 38.6 49.7 22% 11.1%

aBased on the average water layer thickness listed in Table 3.6.

3.6.3 Dust deposition experiment

A plot of the relative pressure drop vs. normalized mass of dust deposited on the

coil (Mcoil/Ac) appears in Figure 3.11. The horizontal error bars represent the uncertainty

in the mass deposited that arise both from the uncertainties associated with measurement

as well as the results of closing the mass balance on the system (see details below). The

vertical error bars are very small because of the small uncertainty (0.1 Pa) associated with

the pressure transducer. After an induction period, the relative pressure drop increased

exponentially with mass deposited until the pressure drop of the clean coil had more than

doubled. At that point, the experiment was stopped because the pressure drop suddenly

and significantly decreased. A visual inspection of the coil showed that a large amount of

face fouling at the leading edge of the test heat exchanger sloughed off and fell to the

bottom of the duct.

97

Normalized Mass Deposited (g/m2),Mcoil/Ac

0 40 80 120 160

Rel

ativ

e Pr

essu

re D

rop

∆P/ ∆

P initi

al

1.0

1.5

2.0

2.5

Figure 3.11: Normalized mass deposited vs. relative pressure drop for 2.0 m/s air velocity.

The deposition fraction for each dust insertion, calculated with Equation (3.11),

agreed on average to within 5 - 15% of that simulated with the model described in

Chapter 2, using the particle size distribution in Figure 3.5 for SAE coarse dust, and

assuming spherical particles. There was substantial uncertainty (15 – 30%) in the

calculated penetration fractions because some of the corrections, described in Equation

(3.18) and the surrounding discussion, had to be averaged over all of the dust insertions. I

expected to measure increasing deposition fraction as the test heat exchanger fouled, as

previous deposits increase surface roughness and provide greater surface area at the

leading edge for deposition. However, the penetration fraction showed no obvious

pattern of decreasing as the system fouled. This might be due to the large uncertainty

bounds on penetration. Also, there was no obvious asymptotic limit to fouling.

98

To confirm the validity of the mass deposited values (Mcoil in Equation (3.18)), an

overall mass balance on the system was completed. The mass that deposited on the coil

from this perspective is defined as:

mass balance insert sifter mound filter,up duct ,up

duct ,down duct air,down

M M M M M M

M t A U C

= − − − −

− − ⋅

∑ ∑∑

(3.19)

where Minsert is the total amount of dust put into the sifter over the course of the

experiment, Msifter is the amount of dust that remained in the sifter after each dust

insertion, Mmound is the amount of dust that fell directly to the floor of the duct underneath

the sifter, Mfilter,up is the amount of dust collected on the upstream sampling filters for

each dust insertion, Mduct,up is the amount of dust on the duct surfaces between the sifter

and the test heat exchanger and Mduct,down is the amount of dust on the duct surfaces

between the heat exchanger, and the downstream sampling nozzle. These values are

tabulated in Table 3.8.

The results of Equation (3.19) are a check on the overall experiment. This

method underpredicts the amount of dust deposited on the heat exchanger, as calculated

with Equations (3.17) and (3.18) by 14 %. This value, along with the uncertainties in air

concentrations and mass measurements was used to define the uncertainty on the mass

deposited values in Figure 3.11. The difference when compared to the total amount of

dust inserted into the system, indicated that the mass balance was closed to within about

3.3% of the mass inserted into the sifter.

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Table 3.8: Mass balance calculations.

Location Variable Mass [g]

Introduced to sifter Minsert 686.7

Remained in sifter Msifter 192.7

Mound underneath sifter Mmound 106.8

Upstream filters ΣMfilter,up 9.2

Floor of duct upstream Mduct,up 221.8

Floor of duct downstream Mduct,down 8.5

Downstream integrated tAductUΣCair,down 5.3

Mmass balance 142.5

Mcoil Equations (3.17) and (3.18) 165.0

Difference 14.6%

3.7 Discussion and Implications of Experimental Results

The experiments suggest that, over the ranges of air velocity and particle sizes

tested, particles deposit with increasing particle size. This is consistent with the

simulation work in Chapter 2. In most cases, the model underpredicted the experimental

deposition results, although the overall agreement between the modeled and measured

results is reasonable. In particular, there is good agreement between the shape of the

simulated and measured deposition fraction curves.

100

The model tends to show increasing underprediction of measured deposition with

increasing velocity. The highest velocity experiments (Figure 3.9) show that the steep

increase in deposition occurs at a smaller particle diameter than the simulations predict.

This raises some questions about the modeling of inertial mechanisms. One possibility is

that air turbulence leads to deposition of much smaller particles than the model predicts.

Given the importance of impaction on tubes as a removal mechanism for larger particles

at higher velocities, a deficiency with the modeling of this mechanism is a possibility.

The wake from upstream tubes could lead to increased deposition on downstream aligned

tubes.

Another question that the isothermal experiments can illuminate is whether the

division between deposition mechanisms in Chapter 2 is valid. Over the range of 1 – 7

µm in particle diameter, deposition by fin impaction is the dominant deposition

mechanism in the simulations. Experimental extractions of the leading edge (and the first

5 mm of the fin channels) suggest that 30 - 75% of the particles that deposit do so on this

part of the heat exchanger. Although these fractions have large uncertainty associated

with them (and a bias towards undermeasurement because of leakage of buffer out of the

coil during extraction causing less than the first 5 mm to be extracted), they suggest that

all of the discrepancy is caused by deposition in the fin channels, not on the leading edge.

A likely source of this error is the macroscale surface roughness elements and fin

discontinuities that occur in real heat exchangers. These irregularities occur for ease of

manufacturing and to promote air turbulence and improved heat transfer. Figure 3.12

provides a depiction.

101

Figure 3.12: Top view of idealized (left) and real (right) fin channels.

The test heat exchanger had 14 discontinuities in each fin. There is likely

additional inertial impaction on the leading edge of each discontinuity, although

modeling this phenomenon would be very difficult because of the difficulty in simulating

boundary layer growth on complex surfaces.

The cooling of the heat-exchanger surfaces led to an increase in deposition by an

amount that was higher in the experimental data than predicted by the simulations. The

underprediction of deposition (by about 4 percentage points) can only partially be

explained by the discontinuities discussed above. One possibility for the additional

difference is that the model for thermophoretic penetration was assumed to hold across

the whole fin channel. A two-layer model that divides transport of particles to the edge

of the boundary layer and then the existing model used to describe deposition of particles

across the boundary layer might result in better predictions of the thermophoretic

deposition. Such a model is beyond the scope of this dissertation, and would be

challenging to implement for real fin surfaces, but could result in better predictions. The

inclusion of a solution to the energy equation would also allow a better understanding of

102

temperature gradients and could also decrease the modeled-measured discrepancy for

non-isothermal systems.

The presence of condensed water led to a dramatic increase in the deposition

fraction. This effect was not predicted particularly well with the model. In absolute

terms, a 4 – 12 percentage point underprediction is observed between the modeled and

the measured data for each of the tests. The experiment with the smallest discrepancy

(on the order of the discrepancy associated with the cooling-only experiments described

above) had a much smaller average water layer thickness. This suggests the possibility of

a systematic problem with the model. One possibility is that the definition of an average

water layer thickness is not valid. If the water is not distributed evenly over all surfaces,

then the modeled increases in fin thickness and tube diameter are not accurate. The

refrigerant tubes are the coldest part of the heat exchanger, so more condensation might

occur on them. This would lead to the model further underpredicting deposition fraction

because the fractional change in tube diameter is much smaller than the change in fin

thickness, and the increase in fin thickness affects more deposition mechanisms.

However, water drains off tubes differently than it drains off fins, particularly real heat

exchanger fins (as opposed to idealized ones). Another future area of research is an

investigation of the nature of condensation on the heat-exchanger surfaces. If beading, or

other non-uniform water accumulation, occurs on different parts of the heat exchanger,

this would change the estimates of deposition fraction. Meanwhile, the model should be

considered to underestimate the actual deposition that results for condensation,

particularly for relatively thick average water layers.

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The experiment to measure pressure drop as a function of deposited material

showed a progressive increase in pressure drop with deposited material over a more than

doubling of the clean heat exchanger pressure drop. This is different than results

suggested by other fouling researchers (i.e. Bott, 1983; Epstein, 1988) who suggest an

asymptotic fouling rate and that the relative pressure drop should level off. There are two

possibilities to account for this discrepancy, the first is that the heat exchanger really

doesn’t foul asymptotically. The second is that had it been possible to keep fouling the

heat exchanger, the exponential curve would have developed an “S” shape and begun to

asymptote. One mechanism for this to occur is through sloughing of deposited material

as the heat exchanger becomes loaded. The high rate and short duration of loading might

have artificially limited this loss of material. However, Bott and Bemrose (1983)

investigated this theory for a circular fin-and-tube heat exchanger and found that the

same asymptotic pressure drop was reached regardless of the duration of fouling and the

air concentration of fouling agent. Although academically interesting, this argument is

not useful to HVAC heat exchangers: Parker et al. (1997) suggest that HVAC evaporator

coils should be cleaned when the increase in pressure drop reaches 10-15% of the clean

pressure drop, a much lower value than the more than doubling reported here.

The overall conclusions are that the experiments described here offer the first

available particle and air velocity resolved measurements of deposition in HVAC heat

exchangers. These results will be applied to typical HVAC systems to explore indoor air

quality and energy consequences in Chapters 4 and 5.

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CHAPTER 4: BIOAEROSOL DEPOSITION ON HVAC HEAT EXCHANGERS AND IMPLICATIONS FOR INDOOR AIR QUALITY

4.1 Introduction

One concern with HVAC heat exchanger fouling is that some of the material that

deposits may be biologically active. Under certain environmental conditions, this can

cause growth and colonization of the heat exchanger surfaces. In addition to the energy

and performance consequences of fouling (discussed in Chapter 5), this biological growth

can be associated with odors and occupant complaints. Contamination of other system

components, such as ducts, filters, condensate pans, water supplies, as well as indoor

surfaces, can result from an original contamination on a heat exchanger. In extreme

cases, occupant morbidity can be adversely affected. Biological contamination of HVAC

systems has been implicated in some cases of sick building syndrome (Godish, 1994).

There are numerous anecdotal reports of biological fouling of HVAC heat

exchangers (RSC, 1987; Belkin, 2001; Turpin, 2001). Over the course of this project,

visual inspections that I conducted revealed the visible presence of fungal spores on

evaporator heat exchangers in residential and commercial (particularly hospitality

industry) buildings in Texas, Georgia, New Jersey, Cincinnati, Ontario, and Minnesota.

In the literature, Muyshondt et al. (1998) discuss the HVAC system as both a source and

sink of biological and other contaminants. They suggest that the dark, moist areas around

evaporator heat exchangers represent ideal growing conditions for biological material and

that deposition of non-biological aerosols can provide the nutrients that can lead to

biological growth. Morey (1988) describes similarly ideal growing conditions for fungus

105

in the HVAC system in 13 commercial buildings: “The presence of adequate nutrients

(debris inherent on heat exchanger surfaces) and moisture provide an ideal site for fungal

amplification.” Hugenholtz and Fuerst (1992) describe measurements of bacteria

concentrations in a large commercial air handling systems and found a biofilm of bacteria

on several cooling heat exchangers. Other work, such as the review article of Batterman

and Burge (1995), further describes the implications of biological growth in HVAC

systems.

The purpose of this chapter is to apply the simulation and experimental work

detailed in Chapter 2 and 3 for the particular case of biological aerosol deposition on

HVAC heat exchangers. The major topics covered in this chapter are a review of existing

literature on bioaerosols of concern and contamination of HVAC systems and heat

exchangers, an application of the work in Chapters 2 and 3 to determine the role of

deposition in biological fouling, and a discussion of potential consequences.

4.2 Bioaerosols of Concern

A wide range of bioaerosols has been identified in indoor environments. They

come in many different forms and can be attached to inert particles or are contained in

water droplets. For deposition on cooling heat exchangers, I am predominantly interested

in two types of organisms: fungi and bacteria. There are other biological agents present

in indoor air that also present health concerns, such as viruses, dust mites, algae, and

pollen. These particles are either relatively unstudied in indoor environments (viruses),

large and not particularly biological active in HVAC systems (dust mites, pollen), or

106

commonly associated with pools of standing water (algae). Although standing water in

drain pans of air conditioners can present an environment suitable for algae growth, I am

focusing on the cooling heat exchanger itself in this work.

4.2.1 Fungi

Fungi are common in indoor environments and are often referred to as mold.

Mold are a subcategory of fungi that can grow on a wide variety of surfaces and are

responsible for deterioration many materials (Miller, 1992). Yeasts are another common

group of fungi that require liquid water to grow. Fungi can be allergenic or toxic

themselves. We are often more concerned with their spores that can also be allergenic,

toxic, and cause lung damage (Banaszak et al., 1970; Schata et al., 1989, Flannigan et al.,

1991). Additionally, as fungi grow, they can produce mycotoxins, metabolic byproducts

that can be harmful to humans (Foarde et al., 1994; Miller, 1992). Fungi can also be

associated with odors and related occupant complaints in buildings. There are many

species of fungi, and even limiting the range of interest to those species commonly found

in indoor environments, spore sizes span a very large range both among and within

fungal species. Foarde et al. (1994) lists the size ranges of spores from 12 common

indoor mold species (their Table 6.4) and they range from 2 µm spheres (Aspergillus

candidus) to 7 × 50 µm sickles (Fusarium solani). They often have irregular shapes that

can significantly affect their transport and deposition behavior.

Indoor fungal spore concentrations also span very large ranges. In a review of

studies in 21 large and small commercial buildings, Morey (1988) reported ranges of

spore air concentrations spanning six orders of magnitude from 10 to 13 × 107 colony

forming units (CFU) per m3. Significantly, the highest reading in the study came from a

107

sampling location 1 - 2 m downstream of a cooling heat exchanger that had “considerable

moist organic debris on it.” Foarde et al. (1994) summarized the work of six researchers

studying fungal concentrations in 383 residences and four office buildings with no

occupant mold complaints. They reported a wide range of airborne fungal

concentrations: 0 - 104 CFU/m3 at the residential sites and 1 – 103 CFU/m3 at the

commercial sites. The same study also summarized research on fungal concentrations in

buildings with occupant complaints and found a similar range, but typically with elevated

concentrations over the non-complaint buildings, and with differing dominant fungal

species. Reynolds et al. (1990) reports fungal concentrations of 103 – 104 CFU/m3 in six

residential and commercial buildings, all with reported occupant complaints. Molhave et

al. (2000) reported an average of 104 CFU/g of viable fungi in samples of settled dust

taken from seven Danish office buildings.

Table 4.1 lists the genus of fungi that have been found in different parts of HVAC

systems. Bold-faced genus names indicate that a single researcher found the genus in

multiple buildings at high surface concentrations or that multiple researchers found that

genus (in different buildings). Although several of these studies included multiple

buildings, most deliberately targeted problem buildings. There is no known

comprehensive data set of microbiological contamination of HVAC systems.

108

Table 4.1: Fungal species in different parts of HVAC systems.

Location Fungal Speciesa Reference

Cooling heat exchangers

Aspergillus spp., Cladosporium spp., Penicillium spp., Pithomyces spp., Unidentified Yeasts

Morey (1988)

Other heat exchangers

Alternaria spp., Aspergillus spp. Reynolds et al. (1990)

Ducts Penicillium spp., Cladosporium spp. Morey (1988), Reynolds et al. (1990), Ahearn (1996), Chang et al. (1996)

Duct Insulation Acremonium spp., Aspergillus spp., Chaetomium spp., Cladosporium spp., Rhizopus spp.

Price et al. (1994)

Fans Aspergillus spp., Cladosporium spp., Penicillium spp.

Heinemann et al. (1994)

Filters Alternaria spp., Aspergillus spp., Chaetomium spp., Cladosporium spp., Penicillium spp., Phoma spp.

Heinemann et al. (1994), Kemp et al. (1995)

Evaporative Coolers

Aspergillus spp., Cladosporium spp., Penicillium spp.

Macher and Girman (1990), Hyvarinen and O'Rourke (1995)

Humidifier water and components

Acremonium spp., Exophilia spp., Fusarium spp., Paecilomycaes spp., Penicillium spp., Phialphora spp., Phoma spp.

Heinemann et al. (1994)

aBold-faced species were found at significant concentrations on multiple systems or by multiple researchers

4.2.2 Bacteria

Bacteria can be allergens and can cause disease and sickness. Legionella

pneumophila, the bacterium associated with Legionnaires disease, is one of the more

infamous causes of HVAC system contamination. However, it is much more commonly

associated with water spray from cooling towers and potable water systems than directly

109

with indoor components of HVAC systems. Other airborne gram-negative bacteria can

contain endotoxins, which are known irritants and are also causative factors in human

lung disease (Hugenholtz and Fuerst, 1992). Bacteria common in the indoor environment

range in size from 0.1 – 6 µm (Foarde et al., 1994). The study of these bacteria is

complicated by the fact that they often are attached to larger particles. Even though

bacteria can be spherical, rod-shaped, or ellipsoidal, the larger particles to which they

attach themselves tend to have large surface areas and are typically highly irregular in

shape (Foarde et al., 1994). Data on indoor bacteria concentrations are not extensive.

Pelikka et al. (1986) report bacteria concentrations of 80 – 120 CFU/m3 in a study of four

homes and 5 – 50 CFU/m3 in three office buildings. In similar studies of three office

buildings, Holt (1990) found bacterial concentrations of 0 – 270 CFU/m3 and Feeley et

al. (1988) found 30 – 140 CFU/m3. Harrison et al. (1992) found 2 – 960 CFU/m3 of

viable bacteria in 15 English office buildings with a variety of different types of HVAC

systems. Hugenholtz and Fuerst (1992) found bacterial concentrations in the supply air

of a well-maintained HVAC system in a commercial building of 102 – 103 CFU/m3.

Table 4.2 lists contamination sites of different bacteria in HVAC systems. There

is a much less data available in the literature on bacterial contamination than on fungal

contamination.

110

Table 4.2: Bacterial species in different parts of HVAC systems.

Location Bacterial Speciesa Reference

Cooling heat exchangers

Acinetobacter spp., Arthrobacter spp., Bacillus spp., Blastobacter spp., Flavobacterium spp., Pseudomonas spp.

Hugenholtz and Fuerst (1992)

Drain Pans Blastobacter spp. Hugenholtz and Fuerst (1992)

Evaporative Coolers

Pseudomonas spp. Macher and Girman (1990)

Evaporative Condenser

Flavobacterium spp. Hugenholtz and Fuerst (1992)

Fans Bacillus spp., Thermoactinomyces spp. Heinemann et al. (1994)

Humidifier water and components

Thermoactinomyces spp. Heinemann et al. (1994)

AC system (non-specified)

Acinetobacter spp., Arthrobacter spp., Bacillus spp., Cedecca spp., Corynebacterium spp., Staphylocuccys spp.

Hugenholtz and Fuerst (1992)

aBold-faced species were found at significant concentrations on multiple systems or by multiple researchers

Despite the occurrence of individual buildings with high air concentrations of

bacteria and fungal spores and the documented contamination of some HVAC systems, it

is important to put these numbers in perspective. Pelikka et al. (1986) report that in

typical indoor environments, only 1 in 103 particles are a fungal spore, 1 in 106 of the

small (submicron) particles that dominate indoor air concentrations are associated with

bacteria, and 1 in 103 larger particles contain viable bacteria. However, despite these

seemingly low proportions, biological contamination of heat exchangers can still be a

problem because 1) there are large numbers of particles in indoor air (~103 per m3

111

(Wallace, 1996)) and 2) the volume of air that passes over heat exchangers is high (a flow

rate of four to five times the total volume of the air in a residential building per hour is a

rule of thumb for an operating cooling system). Commercial systems usually mix

outdoor air and return air, and have similarly high or even higher flow rates. These high

flows can therefore transport substantial amounts of material to the heat exchanger.

Some of the particles, particularly larger particles, in this air stream are likely to be

filtered, depending on the efficacy of the filter installed, which could lead to fungal

growth on filters as reported in Table 4.1. However, in typical systems there is often

unintentional filter bypass because of poor filter installation practices and duct leakage on

the return (negative pressure) side of the system, which can lead to some or all of the air

not being filtered. Filter bypass is discussed in more detail in Chapter 5.

4.3 Bioaerosol Deposition on Heat Exchangers

Given the microbiological growth described on heat exchangers and other HVAC

surfaces in Tables 4.1 and 4.2 and the potential for high airborne bioaerosol

concentrations, it seems likely that, at least in some systems, biological aerosols are

available to deposit on a heat exchanger. Before discussing the likelihood of deposition

further, there are two caveats in using the experimental and simulation results of Chapters

2 and 3 to predict biological aerosol deposition on heat exchanger. The first is that the

particles considered in the earlier chapters were spherical. Many biological aerosols are

not spherical, and this can affect their transport and deposition behavior. Hinds (1999)

and Willeke and Baron (1993) summarize the work of several researchers to develop

methods to determine an equivalent spherical diameter for non-spherical particles. Burge

112

(1995) reports that the irregular shape of many fungal spores, decreases settling velocity,

and increases surface drag, particle relaxation time, and Stokes number. These

characteristics would lead to higher deposition than the experiments and simulation work

predict. In the context of the specific experiments reported in Chapter 3, the added

uncertainty is not particularly large, but care should be taken when applying the results to

highly non-spherical particles.

The second caveat is that, although the experimental technique allows for some

determination of the separation of particle deposition on different parts of the evaporator,

it doesn’t allow for precise distribution information. This information would be very

useful for determining the viability of deposited biological material. If a fungal spore

deposits at the leading edge of the evaporator, the local humidity, temperature, and

nutrient availability will be very different than if it had deposited on a refrigerant tube.

This caveat raises some additional issues because biological systems are inherently quite

complex. Seemingly identical average conditions in two different HVAC systems might

lead to very different patterns of biological growth. The role of microenvironments is

very important for understanding microbiological viability (Burge, 1995). Also, although

there is frequently a dominant species contaminating a surface (i.e. Hugenholtz and

Fuerst, 1992), competition within species likely occurs, which can result in different

outcomes depending on a complicated set of factors including micro-environmental

conditions, system cycling, and contamination of adjacent surfaces.

Figure 4.1 shows the results of modeling and measurement for a 1.5 m/s air

velocity (data are identical to those in Figure 3.7). The horizontal lines show the range of

sizes for the most common bacterial and fungal genera found on cooling coils (see Tables

113

4.1 and 4.2). The results suggest that if these bacteria and fungal spores exist in a state

unassociated with other particles (a bigger assumption for the bacteria than for the fungal

spores) they would have deposition fractions of 0 – 10% for isothermal coils, 5 – 15% for

cooled coils, and 20 – 40% for cooled-and-condensing coils. The isothermal deposition

fractions increase to 0 – 15% for an air velocity of 2.2 m/s and 2 – 30 % for an air

velocity of 5.2 m/s. The non-isothermal deposition fractions for these higher velocities

would also increase (see Chapter 2 for details). Biological material that is associated

with larger particles would have larger deposition fractions.


Dep

ositi

on F

ract

ion

(%)

0

10

20

30

40

50 Pseudomonas spp.Blastobacter spp.

Penicillium spp.

Aspergillus spp.

Figure 4.1: Deposition fractions for air velocity of 1.5 m/s and fin spacing of 4.7 fin/cm. Circles are isothermal data, squares are cooled heat exchanger, triangles are cooled-and-condensed, the trace shows isothermal simulation results, and the horizontal lines are aerodynamic diameter range for known HVAC heat exchanger contaminant species.

For these four, and for other biological aerosols, these results suggest that as an

aerosol gets larger it has a greater probability of depositing. Given these results,

deposition of potentially viable bioaerosols, especially over a significant period of time,

is likely to occur. However, the limiting factor to heat exchanger contamination remains

unclear. Deposition fraction may not be the limiting aspect of the processes that lead to

114

contaminant growth. Several researchers (Morey, 1988; Miller, 1992; Foarde et al.,

1994; Molhave, 2000) have pointed out the association between dust and

microbiological, particularly fungal, growth. This raises the question of whether, under

the appropriate set of environmental and nutrient conditions, microbiological growth will

occur with the deposition of a very small number of viable bioaerosols. Stated

differently, are the conditions on typical heat exchangers such that contamination is

insensitive to the amount of bioaerosol that deposits? There is insufficient evidence in

the literature to answer these questions, but the presence of the bioaerosols of interest in

indoor air, the availability of a mechanism (deposition), and studies that have found

microbial growth on HVAC heat exchangers suggest the possibility and need for further

investigation of factors that lead to microbial growth on HVAC heat exchangers.

Controlled experiments, as well as additional characterization of existing biological

contaminants on heat exchanger surfaces, would be useful.

4.4 Viability and Spread of Deposited Bioaerosols

Once a bioaerosol particle has deposited on a heat exchanger, an important

question is whether it will be viable. To grow, fungi and bacteria have certain

environmental requirements, including bulk water or high relative humidity, nutrients,

suitable pH, temperature, and local airflow. It is difficult to make broad inclusive

statements about these requirements, as they are often species specific. Each

environmental requirement is discussed below.

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The moisture availability on a cooling heat exchanger is complicated, because it

can vary significantly as the HVAC system cycles. The heat exchanger can warm up and

dry out between cooling cycles. However, there are a substantial number of heat

exchangers that run for very long periods of time (in larger commercial systems), as well

as heat exchangers with inadequate drainage or sufficient surface roughness or previously

deposited hygroscopic material that they retain moisture for long periods of time.

Furthermore, many fungal spores can remain in a dormant state during periods of low

humidity (Gravesen et al. 1994; Miller, 1992). Moisture can vary spatially over the heat-

exchanger surfaces. The leading edge of a heat exchanger fin is typically quite close to

the ambient air temperature, whereas the base of a fin near a refrigerant tube is much

closer to the refrigerant temperature. This leads to different patterns of condensation,

relative humidity, and water activity over the fin surfaces. Biological growth has been

observed on all parts of heat exchangers (Morey, 1998; Hugenholtz and Fuerst, 1992),

indicating that in some cases, moisture conditions are adequate to sustain microbial

contamination. Although bulk moisture is a preferable water source for many

microorganisms, sufficiently moist air is enough to support bacteria on heating or fan-

only heat exchangers (Miller, 1992; Foarde et al., 1994), particularly if a moist enough

microenvironment on the heat exchanger surface is available.

The availability of nutrients and the pH of condensed water are largely

determined by the amount and constituents of previous deposition. Other researchers

have established that these quantities can be sufficient to sustain microbiological growth

(Morey, 1988; Hugenholtz and Fuerst, 1992).

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Typical cooling heat exchanger surface temperatures, which range from 5° C to

ambient, indicate that there are a number of fungal species that could be supported in the

microenvironments of a cooling heat exchanger, although many fungal species prefer

slightly warmer temperatures (Gravesen et al. 1994; Foarde et al. 1994). As with

moisture, cycling conditions, and spatial temperature variations exist. Bacteria tend to

prefer warmer conditions, although there are several species that can survive at the lower

temperatures typical of cooling heat exchangers, as suggested by the work of Hugenholtz

and Fuerst (1992). The temperatures associated with heat exchangers during fan

operation but with the heat exchanger off (i.e. unconditioned ventilation or recirculation),

are ideal for a wide range of fungi and bacteria.

Once a microbiological colony has established itself on a heat exchanger surface,

there is evidence that it spreads to contaminate other parts of the HVAC system. Morey

(1988) found contamination of air and duct liners immediately downstream of fungal

contaminated cooling coils. The genera of species that they found, as well as

experiments that involved agitation of the heat exchangers, suggest that the cooling coils

were the original contamination source. Bulk moisture can often form on ducts

immediately downstream of a coil, because the air downstream is near saturation. The

duct walls, particularly if their exterior is insulated, can be cooled below dew point

temperature by radiative heat transfer from the coil. This can lead to favorable conditions

for microbiological growth. Hugenholtz and Fuerst (1992) suggest that contamination of

a drain pan occurred by shedding of Bactoblaster spp. bacteria from the cooling coil as

there was no other source in the building and no other mechanism for the bacteria to get

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to the coil. Although they didn’t look at heat exchangers, the work of Heinemann et al.

(1995), suggests cross-contamination between filters, ducts, fans and humidifiers.

A common pathway for the spread of biological material is through airborne

dispersion. Fungal spores can easily be entrained in air flows typical in HVAC systems

(Foarde et al., 1994, Burge, 1995) and can have effects on the occupants as well as lead

to fungal growth in other parts of the building. Morey (1988) measured fungal spore air

concentrations downstream of cooled coils and found highly elevated levels (although the

original contamination of the coil led to contamination of duct-liner surfaces, which

could inflate this number). Reynolds et al. (1990) and Heinemann et al. (1995) present

evidence linking contaminated HVAC systems to airborne elevated fungal spore levels.

Relatively little work has been done on the viability and spread of bacteria in

HVAC systems. Macher et al. (1995) examined the transfer of bacteria to air in

contaminated evaporative air coolers (EACs). Even with an artificially high level of

contamination of bacteria in their study, there was relatively little water to air transfer of

bacteria in these systems. Furthermore, an EAC represents a more likely source of air

contamination than a heat exchanger, because EACs have hygroscopic materials and

direct contact between a water pool and an air stream. However, Hugenholtz and Fuerst

(1992) found relatively low, but still elevated, air concentrations of bacteria downstream

of an air-conditioning coil fouled with bacteria and they further found an order-of-

magnitude variation between different days depending on the operation of the cooling

coil.

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4.5 Discussion

There are several problems that might result from the deposition of bioaerosols on

a viable heat-exchanger surface. The first is that these organisms can create metabolic

byproducts, such as mycotoxins, which can cause irritation, allergies, odors, and in

extreme cases, occupant sickness (Miller, 1992; Godish, 1995). The second is that the

presence of fungal spores and bacteria in air can lead directly to occupant health

problems. Several researchers have documented a connection between contaminated

HVAC systems and SBS, allergies, and other health outcomes (Fink et al., 1971; Fink et

al., 1976; Molina, 1989). Lastly, even if not linked to odor or health problems,

deposition and growth of biological material on heat exchangers can lead to a variety of

adverse energy and air-conditioner performance impacts (Krafthefter and Bonne, 1986;

Krafthefter et al., 1987) as detailed in Chapter 5.

So far this chapter has looked at bioaerosol deposition on heat exchangers as a

potential source of indoor environment contamination. Muyshondt et al. (1998), among

others, has mentioned the possibility of HVAC system components being a sink for

contaminants. Although a cooling heat exchanger may not be the best place to store

biological material, cooling heat exchangers do serve to remove some bioaerosols from

the air stream. In the case of dust mite feces and parts, pollen and other biological

material that are unlikely to be viable on or spread from a heat-exchanger surface,

deposition is a trade off between diminished air conditioner performance and energy use

and removing these items from indoor air.

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Solomon et al. (1976) demonstrated that homes and examining rooms cooled with

window air conditioners have dramatically lower indoor concentrations of fungal spores

and pollen than equivalent spaces cooled with natural ventilation (open windows). The

results suggest that window air conditioners act to reduce these concentrations primarily

by the removal of bioaerosols by an in-line filter (although the role of the coil was not

considered). Several of the units in this study used condensate water to evaporatively

cool a condenser coil – bacterial contamination associated with spray systems of different

parts of the system or the room air wasn’t considered, but is a possibility.

Hyvärinen and O’Rourke (1995) examined airborne viable fungi concentrations

from 171 homes in Arizona equipped with either evaporative cooling or central air

conditioning. The results were analyzed in a paired study of a subsample of 46 houses

(23 each with evaporative cooling and central air conditioning) that excluded

confounding variables. Throughout the year, Cladosporium spp. concentrations were

significantly greater in homes with evaporative cooling, probably because these homes

had high average relative humidities. Penicillium spp. were higher in the non-cooling

season in houses with air conditioning. Given the work of Morey (1988), one possible

explanation for this is that Penicillium spp. spores deposited on the cooling heat

exchanger and spread through the home when the relative humidity conditions were

appropriate (Burge, 1995). An important difference between the two types of systems is

that the homes equipped with air conditioning use the same distribution system in both

the heating and the cooling system. This results in more air movement that can entrain

and transport spores from the HVAC system to the living space.

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Harrison et al. (1992) measured at bacterial and fungal concentrations in 15 office

buildings and found diminished bacterial air concentrations for buildings with cooling or

cooling compared to buildings with heating only. Bacterial concentrations decreased by

a factor of three between buildings with cooling and buildings without. Fungal spores

were lower by an order of magnitude. Although average relative humidities and

temperatures in the buildings were not significantly different, sampling took place at

different times of the year in each building and thus relationships between HVAC system

contamination and room air contamination are difficult to infer from the data.

Given the inaccessibility of most heat exchangers, they are far from ideal

microbial sinks. They are not always accessible for cleaning (particularly in residential

systems), the microbiological growth is not always visible (the bacterial biofilm

described in Hugenholtz and Fuerst (1992) was on an apparently clean and well

maintained heat exchanger), and the risks of air contamination by biocides and coil

cleaning products are not well understood. An additional concern is that cleaning of heat

exchanger could result in the dislodging of potentially allergenic and otherwise harmful

material. Also, the destruction of an established biofilm is often more difficult than

destroying individual organisms (Characklis and Marshall, 1990). Even in the absence of

a continuous source of bioaerosols, some heat exchanger cleaning methods might only

temporarily retard microbiological contamination. A preferable solution would be

properly designed and maintained filtration components, including the elimination of all

filter bypass. This is discussed more in Chapter 5.

This research represents a step toward understanding the causes and consequences

of bioaerosol contamination of heat exchangers. There are still important questions to be

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answered. Although there is evidence that many air conditioning heat exchangers present

viable environments for bacterial and fungal growth. Further research on microorganism

viability on heat exchangers would be useful. Further research on resuspension of

deposited biological material would also be important to close the knowledge gaps

between deposition, colonization, and occupant problems. And, perhaps most

importantly, field studies that measure how much and what types of biological growth

exist on HVAC heat exchangers in typical buildings would add greatly to our knowledge

of this topic. Further research on heat exchanger cleaning and other prevention and

mitigation techniques would also help building operators implement solutions to

biological fouling of HVAC heat exchangers.

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CHAPTER 5: FOULING TIMES AND ENERGY IMPLICATIONS OF HVAC HEAT EXCHANGER FOULING

5.1 Introduction

The Energy Information Agency reports that buildings are responsible for 38% of

United States energy use (EIA, 2002). About a third of this total is for heating and

cooling in both residential and commercial buildings. In 1997, residential space cooling

used 1.22 × 1011 kWh of electricity in the 7.26 × 107 U.S. households that have central or

room-based cooling. Americans spent $8.3 × 1010 heating their homes in 1997. In 1995,

commercial cooling accounted for 7.32 × 1011 kWh of electricity use at a cost of

$5.3 × 1010 (EIA, 2002). Furthermore, cooling is a substantial contributor to peak

electrical demand for both residential and commercial systems. Peak demand drives the

need for capacity of generating plants, stresses the reliability of electricity grids and

infrastructures, and causes a disproportionate share of electricity generation pollutant

emissions (because the most polluting and lowest efficiency power plants are often used

to handle the peak loads). Thus, even small degradations in HVAC performance can lead

to substantial monetary and environmental consequences.

In this context, the energy impacts of HVAC heat exchanger fouling merit further

study. The first purpose of this chapter is to determine the rate at which coils foul in

order to assess whether fouling occurs fast enough to cause significant performance

degradation. The second purpose is to assess the magnitude of these energy

consequences.

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Despite its potential importance, there has been relatively little research on

residential evaporator coil fouling. There have been several anecdotal reports of HVAC

heat exchanger fouling (RSC, 1987; Neal, 1992; Turpin, 2002). In the engineering

literature, Krafthefter and Bonne (1986) report that a typical residential heat pump

condenser coil will foul sufficiently to cause a 20% reduction in performance over a 4- to

7-year period. Although very useful in identifying the importance of heat exchanger

fouling, there is some reason to believe that the work of Krafthefter and Bonne (1986)

might overestimate the impacts of fouling because their analysis uses indoor particle

concentrations that are considerably larger than suggested by more recent literature.

Krafthefter et al. (1987) extend this work with further experiments and simulations to

examine the role of high efficiency air cleaners in reducing heat exchanger fouling. For

typical residential heat pump and air conditioning systems, they predict a 10 – 25%

average energy cost savings over the 15-year life of the heat exchanger with a properly

installed air cleaner.

For commercial HVAC heat exchanger fouling, infrared thermographic scans of

cooling coils in Arizona institutional buildings provide the strongest anecdotal evidence

of performance degradation. The work is part of an ongoing project to monitor and clean

fouled coils. These scans suggest that large chilled-water cooling coils have surface

temperatures from 5 °C to 20 °C greater than fouled coils, leading to substantial

reductions in heating and cooling capacity (Westberg, 2001). Although very useful for

diagnosis and evaluating cleaning efficacy, the data should be interpreted as qualitative

because of the potential inaccuracies in infrared coil temperature measurement. Braun

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(1986) reported on the fouling of a 141 kW (40 ton) cooling coil in a commercial

building. The coil had a fin spacing of 2.5 fin/cm, a face velocity of 2.3 m/s, and

corrugated fins. Over the period of a year, the heat exchanger pressure drop increased 35

- 44% because of fouling by indoor dusts. deKieffer et al. (1999) conducted experiments

in which an 18 kW (5 ton), 6.7 fin/cm coil was fouled with a sticky aerosol used to seal

ducts. The purpose of these tests was to determine the effect of flow reduction on

performance, not to obtain data on fouling rates. His work showed that the level of

fouling that caused the air flow to drop by a factor of two simultaneously decreased the

energy efficiency ratio (EER = total cooling capacity/electricity input) by 4 – 6%. The

efficiency degradation was linear with decreasing flow rate. Carter et al. (1998)

measured pressure drop of reheat coils in large institutional buildings on a university

campus. In a sample of 12 reheat coils, they found that the average coil was fouled such

that its pressure drop was 150% of its design value. On a subsample of four coils so

tested, cleaning reduced the pressure drop dramatically.

There are two potential mechanisms by which heat exchanger fouling can lead to

energy consequences. The first is by the development of an insulating layer on the fins

and tubes, thereby adding a fouling resistance to the total resistance to heat transfer

between the air and the refrigerant. The second is by increasing the pressure drop of the

heat exchanger. In HVAC heat exchangers the increased pressure drop is the dominant

effect. On a residential heat pump condenser coil, Krafthefter et al. (1987) reported that

90% of the loss of capacity and efficiency was due to the increased pressure drop (and

consequent decreased air flow). The effect on evaporator heat exchangers used for

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cooling will be even more related to air flow reduction, because of their sensitivity to

diminished flows (Palani et al., 1992; Parker et al., 1997; Proctor, 1998a).

There are several reasons why the increased fouling resistance is less important

than the flow reduction. The first is that much of the deposited material in heat

exchangers is located on the leading edge of the evaporator (face fouling) and material in

the heat exchanger core deposits preferentially on fin discontinuities. These locations are

not particularly important for heat transfer. Insulating the end of a narrow fin does little

to change the surface temperature profile of the fin and corresponding fin efficiencies for

the very thin fins typical of HVAC heat exchangers (Incropera and Dewitt, 2002). The

second reason has to do with area, as the total fin and tube area is very large relative to

the area of deposited particles. Thus, a very large number of particles have to deposit to

develop enough of a layer to decrease heat transfer. A scaling analysis reveals that about

500 g of dust would have to deposit uniformly on a residential cooling coil to cover the

fins with a 10 µm thick layer of dust. Although dust thermal conductivities are not

precisely known, I estimate (with a magnitude analysis) that this large dust load would

add only 10-4 to 10–6 W/m2K of thermal resistance, which is small relative to the air films

and other thermal resistances in the system. Kuehn et al. (1998) demonstrate that a thin

film does little to diminish fin efficiency in cooling coils.

Therefore, the analysis in this chapter will focus on the pressure drop. For some

systems, particularly residential and some small commercial HVAC systems, increasing

heat exchanger pressure drop causes a reduction in flow. The reduction in flow leads to a

decrease in fan and compressor power draw, decreased efficiency, and decreased cooling

capacity (Parker et al., 1997; Proctor and Parker, 2000). For larger commercial systems

126

that can vary fan speed to maintain a required flow, the increased pressure drop of a heat

exchanger leads to increased fan speed and energy usage (and often increased cooling to

remove the additional heat generated by the fan motor). In commercial systems, fan

energy typically represents 9% of total commercial building energy use (Modera et al.,

1999). Therefore, increasing the system pressure drop, such as would occur with a fouled

coil, can cause increased building electricity use and cooling requirements.

5.3 Estimation of Fouling Times and Energy Impacts

The purpose of this chapter is to apply the simulation and experimental results to

predict fouling times, performance, and energy impacts of the HVAC heat exchanger

fouling problem. The impacts, analysis techniques, and scope of investigation for

residential and commercial heat exchanger systems are substantially different, so they are

discussed separately throughout this chapter.

5.3.1 Residential systems

A parametric analysis is used to determine the relative importance of filtration,

duct system design, heat exchanger fin spacing, and indoor concentrations on residential

fouling times. The prediction of fouling time is based on the simulation and

experimental research described in Chapters 2 and 3. The deposition fraction and mass

deposited is translated into an effective flow resistance, pressure drop, and flow reduction

for the heat exchanger and for the entire system. The reduction in flow leads to estimates

of efficiency and performance degradation based on laboratory and field tests of other

researchers.

127

The overall analysis strategy is to start with indoor air particle and dust

concentrations and calculate what fraction of particles are removed by deposition in the

return (negative pressure) ducts and by filtration. The fraction that is not removed by

these mechanisms is then available to deposit on the heat exchanger. The particulate

matter that deposits on the heat exchanger causes an additional pressure drop, as

measured in the dust deposition experiment, which can then be related to a corresponding

drop in airflow. The reduced flow leads to performance impacts. Each of the relevant

calculations and the corresponding assumptions are derived and explained below.

The first important quantity is the mass concentration distribution function of

material that deposits on the coil, mc (mg/µm·m3). This is calculated, as a function of

particle diameter, as follows:

( ) ( )1 1c duct ,r f f f c c m,inm P b b nη η η= − + − (5.1)

where Pduct,r is the penetration through the return duct system, ηf is the filter efficiency, bf

is the filter bypass, bc is the coil bypass, ηc is the coil deposition fraction, and nm,in is the

indoor particle size mass distribution function. All of these quantities are functions of the

particle diameter, dp. The integration of Equation (5.1) over all relevant particle

diameters (dp = 0.01 - 100 µm) gives the total mass (per m3 of air flow) that deposits on

the coil, Mc (mg/m3):

( ) ( )1 1 dp

c d uct ,r f f f c c m,in pd

M P b b n dη η η= − + −∫ (5.2)

128

All of the terms in Equations (5.1) and (5.2) can be varied to explore their

importance. The following paragraphs describe each parameter and the assumptions that

went into determining the values of each parameter chosen for the simulations.

The fraction of particles that are not removed by deposition in the duct work,

Pduct,r, is calculated based on the empirical model of Sippola and Nazaroff (2002). Three

cases were considered based on a review of ACCA (1995) and fieldwork in 11 houses in

California, Nevada, and Texas that I completed as part of earlier research (Siegel et al.,

2002). The lengths (z), flow rates (Q), bulk velocities (U), and diameters (dduct) for these

duct systems are summarized in Table 5.1 and their penetration curves appear in Figure

5.1.

Table 5.1: Residential duct systems for parametric analysis.

Q z U dduct Duct System (m3/h) (m) (m/s) (m)

Simple Trunk 2380 3 3.6 0.48

Trunk 2380 5 3.6 0.48

Branch 1 1370 5 3.3 0.38

Typical

Branch 2 1010 5 3.3 0.33

Trunk 2380 3 3.6 0.48

Branch 1 680 5 3.7 0.25

Branch 2 680 82 3.7 0.25

Complex

(5 × 90° bends) 1

Branch 3 1010 5 3.3 0.33

1The effect on particle deposition in bends of large diameter ducts (as is typical of HVAC ducts) is not well known. Deposition in these bends was approximated based on engineering judgment and the work of Sippola and Nazaroff (2002).

2Four meters are vertical in Branch 2 of the complex system.

129


Duc

t Pen

etra

tion,

Pdu

ct

0.0

0.2

0.4

0.6

0.8

1.0

Simple TypicalComplex

Figure 5.1: Duct penetration fractions vs. particle size for residential duct systems described in Table 5.1.

An important limitation of the analysis considered here is that leakage into return

ducts is not considered. In theory, a leak in a return duct could suck particles into the

duct that could then deposit on the heat exchanger. This effect is not included in this

analysis because there is insufficient information in the literature about particle

concentrations in air surrounding the return duct (typically in attics, crawslpaces, garages

or basements) as well as limited information about how readily particles penetrate typical

duct leaks. Although the magnitude of this effect is not known, the direction of the effect

is clear. Duct leakage would tend to increase the fouling rate because of the availability

of additional particles to deposit on the heat exchanger. This assumption allows also

Equation (5.2) to be applied to systems with filters at the return grill (common in new

housing), as well as at the air handler.

The efficiency of the filter, ηf, is calculated from filter efficiencies described in

ASHRAE Standard 52.2 (1999). Standard 52.2 is a test method that produces a

130

Minimum Efficiency Reporting Value (MERV) rating, which is a measure of the

efficiency of the filter for removing particles of various sizes. For this analysis, three

cases are considered: a low efficiency, but very common, MERV 2 coarse spun fiberglass

furnace filter, a MERV 6 mid-efficiency filter (the minimum being considered by

ASHRAE Standard 62.2P, the proposed residential ventilation standard for new homes),

and a very high efficiency pleated MERV 12 filter. The filter efficiency curves appear in

Figure 5.2.

Particle Diameter (µm)0.01 0.1 1 10 100

Filte

r E

ffic

ienc

y, η

f

0.00

0.25

0.50

0.75

1.00MERV 2 MERV 6MERV 12

Figure 5.2: Filter efficiency curves for parametric analysis.

It is important to compare the performance of these theoretical filters to real

filters. Hanley and Smith (1993) and Hanley et al. (1994) measured the performance of a

spun fiberglass furnace filters. Although the description of the filter in both studies is the

same, the filter in the later study appears to be more efficient. They found that when

loaded with test dust to 250 Pa, which was 25 times the initial pressure drop, the filter

became considerably more efficient and behaved much like the MERV 12 case discussed

above. These filter efficiency curves appear in Figures 5.3 and 5.4. There are two issues

131

that must be considered when applying these real filter data to the present analysis. The

first is that the substantial decrease in efficiency that results from large particles bouncing

off of the filter fibers for the clean filter, also documented in ASHRAE (1999), may be an

artifact of the particles used to challenge the clean filter. Real indoor particles are likely

to be considerably stickier (see discussion in Chapter 2 on particle bounce) and Hanley

and Smith acknowledge that the bounce may not occur in real residential environments.

The second issue is that 250 Pa is a substantial pressure drop, one that would likely occur

only after the filter was left in place for months. I could find no data on actual residential

filter change rates and pressure drop for dirty filters. So, my analysis assumes clean (i.e.

frequently changed) filters and ignores particle bounce for large particles.

Particle Diameter (µm)0.01 0.1 1 10

Filte

r E

ffic

ienc

y, η

f

0.0

0.2

0.4

0.6

0.8

1.0Clean (10 Pa)First Dust Loading (125 Pa)Second Dust Loading (250 Pa)

Figure 5.3: Filter efficiency curves for spun fiberglass furnace filter from Hanley and Smith (1993) for U = 1.8 m/s.

132

Particle Diameter (µm)0.01 0.1 1 10

Filte

r E

ffic

ienc

y, η

f

0.0

0.2

0.4

0.6

0.8

1.0Clean (10 Pa)First Dust Loading (125 Pa)Second Dust Loading (250 Pa)

Figure 5.4: Filter efficiency curves for spun fiberglass furnace filter from Hanley et al. (1994) for U = 1.3 m/s.

The parameter bf represents the amount of air that bypasses a filter because of

poor installation or maintenance. There is almost no information on filter bypass in the

literature. Braun (1986) describes filter bypass around a heavily loaded filter as a likely

cause of heat exchanger fouling in a commercial building. Three cases are considered

here, based on documented anecdotal studies and a scaling analysis of filter bypass in

several residences. The first case corresponds to the situation of a filter in a loose-fitting

slot (10% bypass). The second case corresponds to a filter with a large gap around it, or

one that is only fixed on one edge (25% bypass). Although very likely to be uncommon,

the no-bypass case (requiring deliberate sealing or gasketing) is considered as well,

because one inexpensive option that might reduce coil fouling is to eliminate bypass.

Bypass is assumed to be constant for all particle sizes. The second order effect of bypass

increasing as filter loading occurs is not considered. This treatment is consistent with the

aforementioned assumption of frequent filter changes. However, increased filter bypass

with loading would tend to decrease fouling times.

133

The deposition fraction on coils, ηc, is calculated based on the experimental and

simulation work in Chapters 2 and 3. Three fin pitches, corresponding to the range of

values plus the midpoint typically found in residential HVAC heat exchangers, are

considered: 2.4, 4.7, and 7.1 fin/cm (6, 12, and 18 fins/inch or FPI). A single air velocity,

consistent with supply plenum velocity guidelines in ACCA (1995), of 2 m/s was chosen.

The curves for these heat exchangers were constructed using the simulations to extend

the experimental data to larger and smaller particle sizes and larger and smaller fin

spacings and to account for the “A-coil” geometry typical of residential central air

conditioning systems. The resulting deposition fraction curves appear in Figure 5.5.


Coi

l Dep

ositi

on F

ract

ion,

ηc

0.0

0.2

0.4

0.6

0.8

1.02.4 fin/cm4.7 fin/cm7.1 fin/cm

Figure 5.5: Coil deposition fractions as a function of fin spacing for U = 2 m/s.

A modification to account for increased deposition because of wet surfaces (based

on experimental results) was also included. The increased deposition was calculated

using the simulation to fit a curve to the experiment results for 1.5 m/s air velocity and

then apply this curve shape to other fin spacings. The deposition fractions for a wet heat

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exchanger appear in Figure 5.6. In all simulations, the heat exchanger was assumed to

have a condensed water layer for 500 hours of run time per year.


Coi

l Dep

ositi

on F

ract

ion,

ηc

0.0

0.2

0.4

0.6

0.8

1.02.4 fin/cm wet4.7 fin/cm wet7.1 fin/cm wet

Figure 5.6: Wet coil deposition fractions as a function of fin spacing for U = 2 m/s.

Typical residential HVAC heat exchanger installations also allow some air to

bypass the heat exchanger. That effect is represented by means of a fractional coil

bypass, bc. This bypass factor has a linear effect on Equation (2) and was fixed at 10%,

based on the geometry of a typical residential air handler cabinet. Coil bypass was

assumed to be independent of particle size and has a linear impact on mass deposited.

The indoor particle size distribution, min, is based on the model of Riley et al.

(2002), who considered typical particle distributions for diameters in the range of 10-3 µm

to 10 µm. The interest in this range is based on regulatory and health concerns as PM10

(particles less than 10 µm in diameter) is a federally regulated criteria pollutant.

However, the work in Chapters 2 and 3 suggests that HVAC heat exchanger fouling may

also be caused by deposition of larger particles, and this inference, as well as the role of

135

dust fibers as fouling agents, is substantiated by numerous anecdotal reports (RSC, 1987;

Neal, 1992) and forensic microscopy on fouled coils (see Appendix C).

Riley et al. utilized a time-averaged model of indoor particle concentrations of

outdoor origin. For residential buildings with closed windows, they determine the indoor

concentration, Cin, as

in i

out r r i

C pC

λη λ β λ

=+ +

(5.3)

where Cout is the outside concentration, p is the penetration fraction through cracks in the

building envelope, λr is the HVAC air-exchange rate, ηr is the HVAC filter efficiency, λi

is the envelope infiltration rate, and β is particle deposition loss rate to building surfaces.

Indoor particle sources were not considered in this model.

Several modifications to the Riley et al. model are needed to make it suitable for

the purposes of this chapter. These modifications include accounting for the removal of

particles by deposition on the heat exchanger and ductwork in the HVAC system, the

inclusion of larger particles and dust fibers resuspended from indoor surfaces, and the

inclusion of a duty cycle to account for an air conditioner that runs periodically.

Riley et al. considered removal by indoor deposition and the HVAC filter only.

Particles are also removed by deposition in the ductwork and by deposition on the heat

exchangers in the HVAC system. To account for this, the filter efficiency (ηr in their

notation and in Equation (5.3)) was replaced with:

( ) ( )1 1 1r duct ,r f f f c c c duct ,sP b b Pη η η η η= − − + − + (5.4)

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where Pduct,s is the penetration through the supply ducts and was approximated to be

equal to Pduct,r. The total number of cases simulated made calculating η for each set of

filter, bypass, duct, and coil conditions too computationally intensive. Instead ηr was

calculated based on the filter efficiencies (typically the dominant removal mechanism)

described above and the other variables were fixed at typical values (Pduct,r for typical

duct system, bf = 0.1, ηc for a 4.7 fin/cm heat exchanger, and bc = 0.1).

An additional challenge occurs when trying to address the importance of large

particles. Particles larger than 10 µm are unlikely to penetrate the building envelope, and

once in the indoor space they deposit rapidly by gravitational and inertial mechanisms.

However, examination of fouled coils reveals that many deposited particles are larger

than 10 µm, and most of these large particles are fibers with characteristic lengths of a

millimeter or greater. Although relatively little work has been done on the role and

prevalence of such larger particles in indoor environments, they are potentially important

to heat exchanger fouling because of the significant pressure drop that results from their

deposition.

To examine the role of larger particles play in deposition, two cases were

considered: a “clean” case that considered particles up to 10 µm in size (directly from the

Riley et al. (2002) model) with no indoor sources and a “dirty” case that considered

larger particles and dust fibers. To obtain the dirty case, I modified the work of Riley et

al. (2002) by extending the particle size distributions with an exponential decay fit to the

5-10 µm particle concentrations from the clean case. This is an approximate analysis that

assumes that large particles are only lost to horizontal surfaces by gravitational settling.

137

Ideally, measured large particle concentrations would be used. However, despite there

being a large body of literature on household dust (e.g. Allott et al., 1994; Kildeso et al.,

1999; Schneider et al., 1999; Chen et al., 2000; Croxford et al., 2000; Molhave et al.,

2000), I could find no particle-size resolved measured data for particle diameters greater

than 10 µm (either air concentrations or settled dust on surfaces). This is a substantial

gap in the literature. However, the implications of this approximation are not significant

for this analysis. The low concentrations of large spherical particles that this method

predicts will likely not contribute significantly to fouling.

The work of Thatcher and Layton (1995) was used to include the effect of

resuspension of particles from human activity. The increase in indoor concentration of

particles of all sizes was done using the concentration increase factors in their Figure 7,

assuming that four people were conducting normal activity in the house for eight hours a

day. This is an upper bound on particle resuspension.

Although beyond the scope of this dissertation, a more detailed analysis would

include data on other indoor sources. Wallace (1996) and others have pointed out the

importance of particles from cooking and smoking to indoor particle concentrations.

Although penetration from outside is typically the largest source of particles, up to 35%

of indoor PM2.5 (particles less than 2.5 µm in diameter) can come from smoking

(Wallace, 1996). The inclusion of such additional sources could increase fouling rates,

but the results of forensic microscopy suggest that dust fiber deposition is more important

to residential heat exchanger fouling.

138

There is very little data on fiber concentrations in normal indoor environment.

Much of the work has focused on particular fibers in industrial or mining environments.

For the dirty case, indoor fibers were assumed to be present at the average concentrations

of fibers in 11 randomly selected Danish schools described in Schneider (1986). There is

some question of the validity of using this environment to determine residential airborne

fiber concentrations, but it was the only well characterized data source that I could find.

Mean fiber length was determined to be 2.5 mm, which is consistent with work in

Mølhave et al. (2000) and with microscopy of fouling agents from the leading edge of

two fouled coils (see Appendix C). Fibers were assumed to deposit in the duct system by

gravitational settling only onto the duct floor. I originally determined fiber settling

velocity by calculating the cylindrical coefficient of drag presented by Panton (1996) in

his Table 14.14 and completing a force balance in the vertical direction on the fiber. This

velocity required an iterative solution and was independent of fiber length (seemingly

reasonable for the very long fibers considered here). However, the experimental work of

Cox (1971) found a dependence on fiber length and thus his empirical correlations were

used (his Equations 7.10 and 7.12b). All fibers were assumed to be oriented with their

long axis oriented horizontally consistent with the guidelines in Baron (1993). Fibers are

assumed to be completely removed by any filter (and thus are only potential heat

exchanger fouling agents when there is filter bypass) and, because of their length, are

assumed to deposit with perfect efficiency on the heat exchanger.

Two modes of air conditioner operation were considered. The first assumes that

the air handler fan runs continuously (an increasingly common mode of operation in

houses with interconnected mechanical ventilation and heating and cooling duct

139

systems). The air change rate through the air handler (λr in Equation (5.3)) is assumed to

be 4 h-1 for this case, and the infiltration flow rate, λi, is assumed to be 0.75 h-1. These

values correspond to the “residential CA [central air]” case from Riley et al. (2002). A

second case, where the air conditioner runs for an annual average duty cycle of 10

minutes of operation for every hour was also considered; λr = 0.66 ACH for this case and

λi = 0.57 ACH. The infiltration flow rate, λi, was assumed to have one sixth of the

increased infiltration due to the HVAC system of the continuously operating case.

Two outdoor concentration distributions, Co, were considered to represent

archetypal urban and rural conditions. These concentrations were taken directly from

Riley et al. (2002). Rural outdoor particle concentrations have a greater proportion of

coarse mode particles, but overall far fewer particles (in both number and mass). It is

anticipated that heat exchangers in rural homes will foul more slowly.

Plots of the particle number concentration distributions used in the analysis

appear in Appendix D.

The particles in all four cases were assumed to have a density of 1 g/cm3 for

particles smaller than 2.5 µm and for dust fibers and a density of 2.5 g/cm3 for particles

larger than 2.5 µm. This assumption was made to account for the larger density of coarse

mode particles and although particle density data are sparse, the assumption is consistent

with information in Seinfeld and Pandis (1998) and Riley et al. (2002) and with the

density of standard test dusts, such as the SAE coarse test dust described in Chapter 3.

140

A summary of the parameters considered and their corresponding information

sources appears in Table 5.2. A base case of the most common values of each parameter

was selected based on the engineering judgment of the most typical values for each

parameter. The base case system consists of a typical duct system, a MERV 2 filter, 10%

filter bypass, a 4.7 fin/cm (12 FPI) coil, and a particle concentration resulting from an

urban location with indoor resuspension of particles and dust fibers (the “dirty” case) and

a thermostatically cycling air handler.

141

Table 5.2: Parameters varied in the simulation of mass deposition.

Parameter Reference/ Display Element

Number of Parameter Values

Case Description (base case is in boldface)

Simple

Typical

Pd, Duct Penetration

Sippola & Nazaroff (2002)

Figure 5.1 and Table 5.1

2

Complex

MERV 2 MERV6

ηf, Filter Efficiency

ASHRAE (1999)

Figure 5.2

3

MERV 12

0%

10%

bf, Filter Bypass Anecdotal evidence and scaling analysis

3

25%

High fin pitch

Typical ηc, Coil Deposition Fraction

Chapters 2 and 3

Figures 5.5 and 5.6

3

Low fin pitch

Rural location 2

Urban location

Continuous fan 2

Cycling fan

Clean

nm,in, Indoor Particle Distribution Function

Riley et al. (2002) with additional information on resuspension from Thatcher & Layton (1995) and dust fibers from Schneider (1986)

Figures D.1-D.4 in Appendix D

2

Dirty

Once the mass concentration deposited on the coil is determined for a given set of

parameters, the fouling time, τfoul, which is defined as the time that it takes for the coil

pressure drop to double, is calculated as follows:

142

foulfoul

c

MQ M DC

τ = (5.5)

where Mfoul is the experimentally determined deposited mass of particles that causes the

pressure drop of the coil to double at constant flow (from Chapter 3), Q is the air flow

rate through the system (fixed at 2700 m3/h (1400 CFM) for a typical 12.3 kW (3.5 ton)

air conditioner), and DC is the duty cycle of the air handler fan (DC = 1 for continuous

operation and DC = 1/6 for cycling). The deposited mass that causes fouling, Mfoul, is

assumed to be a linear function of the heat exchanger area. The reduction in Q caused by

fouling is not taken into account because the doubling in pressure drop does not

substantially reduce the flow (as will be shown in the results). Furthermore, for the

cycling case, this reduced flow would mean that the fan in a heating or cooling system

would have to run for longer so the duty cycle would increase and the effect would be

further reduced.

Once the fouling time is established, the next step is to estimate the effect of a

doubling of coil pressure drop on air conditioner capacity, efficiency and power

consumption. This evaluation is not straightforward because the flow through most

residential air conditioner heat exchangers is determined by the intersection point

between the fan curve and the system curve (ACCA, 1995). This point is illustrated in

Figure 5.7. The fan curve is determined by the fan and the system curve is determined by

the pressure drop of all of the components in the system, including the return duct, filter,

coil and supply duct. So, doubling the pressure drop of a coil will have a different effect

on the system curve, depending on the flow resistance of the rest of the system.

143

Furthermore, residential fan curves have different slopes at different points, which means

that doubling the coil pressure drop of a system operating at one point in the curve will

have a different effect than would doubling the coil pressure drop at another point on the

curve.

Flow Rate (m3/h)

0 500 1000 1500 2000 2500 3000

Pres

sure

(Pa)

0

50

100

150

200

Air Flow (ft3/min, CFM)

0 400 800 1200 1600

Pres

sure

(inc

hes w

ater

col

umn,

IWC

)0.0

0.2

0.4

0.6

0.8Fan CurveClean Coil System CurveFouled Coil System Curve

FouledCoil

SystemFlow

CleanCoil

SystemFlow

Figure 5.7: Fan curve and system curves for clean and fouled coil.

To estimate the flow resistances of typical systems, I used supply and return duct

static pressures (based on measurements in more than 250 houses as measured by

Lawrence Berkeley National Lab staff and other researchers), and used the pressure-to-

flow relationship for a typical 12.3 kW (3.5 ton) air conditioner coil (Carrier 1991;

Carrier 1994; ACCA, 1995) to determine the average impact on flow of a doubling of

coil pressure drop in a residential system. Fan curves were obtained from manufacturers’

144

data in ACCA (1995), experimental data from Parker et al. (1997), and data that I

measured in a single house in Fresno, CA. These three fan curves appear in Figure 5.8:

Flow (m3/h)

0 500 1000 1500 2000 2500 3000 3500

Ext

erna

l Sta

tic P

ress

ure

(Pa)

0

50

100

150

200

250

300

350

ACCA (1995)MeasuredParker et al. (1997)

Figure 5.8: Fan curves used to determine flow.

Figure 5.8 contradicts the conventional wisdom that fan curves have an inverted

parabolic shape (ACCA, 1995; Kuehn et al. , 1998; ASHRAE, 2000; McQuiston et al.,

2000). All three fan curves are almost linear over a large range in flows. Further

measured data on installed fans in residential systems might help reconcile this

contradiction, but for my analysis, since flows do not drop significantly, this issue does

not substantially affect the analysis.

Once the system and fan curves are established, the effect of the flow reduction

on system performance can be determined. Figures 5.9 and 5.10 show the performance

degradations that were experimentally determined by Parker et al. (1997) for a 8.6 kW air

conditioner and Palani et al. (1992) for a 10.6 kW air conditioner. The conditions for

both experiments were as follows: indoor temperature = 24 °C, indoor relative humidity

145

= 60%, and outdoor temperature = 35 °C. The capacity in Figures 5.9 and 5.10 is the

total (sensible plus latent) capacity. The latent capacity increases as flow decreases

because the coil surface temperature drops and the sensible capacity decreases. The data

from both researchers suggest a similar, and roughly linear, decrease in all performance

metrics until the flow diminishes to 50 - 60% of the initial flow of 193 m3/kWh (400

CFM/ton). Both data sets show a dramatic reduction in flow past this point, although the

Palani et al. data shows a steeper reduction in performance. Practically, for the small

flow drops that are typical in systems with fouled coils, a linear relationship can be

assumed and the data from both studies are in good agreement in this domain

Flow Reduction (%)0 20 40 60 80 100

Perf

orm

ance

(%)

20

40

60

80

100

PowerCapacityEfficiency

Figure 5.9: Performance degradation from reduced flow from Parker et al. (1997).

146

Flow Reduction (%)0 20 40 60 80 100

Perf

orm

ance

(%)

20

40

60

80

100

PowerCapacityEfficiency

Figure 5.10: Performance degradation from reduced flow from Palani et al. (1992).

Another potential energy impact is the role of coil fouling in changing fan power

draw, an often neglected aspect of residential air conditioner use (Proctor and Parker,

2000). The HVAC fan power, W, is given by,

fan motor

Q PWη η

∆= (5.6)

where Q is flow through the fan, ∆P is the total external pressure drop of the system, ηfan

is the fan efficiency, and ηmotor is the fan motor efficiency. The conventional wisdom is

that decreasing flow decreases the power use of the fan in a cubic relationship. This is

because pressure varies with the square of flow (according to conventional fan curves).

There is relatively limited information in the literature, but the data of Parker et al. (1997)

show a linear decrease in fan power draw with decreasing flow. The size and magnitude

of fan power changes are a function of the fan performance curves and the system curve.

The product of the efficiencies (ηfanηmotor) in Equation (5.6) is a function of flow and

147

pressure as well, although in residential systems, ηfanηmotor varies over a relatively small

range. Parker et al. (1997) assumed a value of 22.5% for ηfanηmotor in their analysis and

their measured data shows a range from 18.8 to 23.7%. Phillips (1995), in a study of

residential central heating systems in Canada, found an average efficiency product of

19%. I assumed a constant 20% for this analysis, which is appropriate because of the

small flow and pressure drop range between clean and fouled coils. An important

secondary effect of changing fan power draw is that it also changes the amount of energy

that the cooling system needs to remove.

5.3.2 Commercial systems

Prediction of fouling times for commercial systems is considerably more

complicated than for residential systems because typical commercial buildings can have

different types and sizes of HVAC heat exchangers (direct expansion cooling coils,

reheat coils, chilled water coils), and a large variety of shapes and configurations of duct

work. In addition, commercial filtration is more varied than it is in residential systems.

Furthermore, most commercial buildings have an economizer cycle in which a direct

connection between the HVAC system and outdoor air is established. Flow rates through

commercial systems are often variable, changing to match ventilation and conditioning

loads. Thus fouling times span a large range and are difficult to predict in a general

manner. For these reasons it does not make sense to estimate commercial fouling times

using the approach developed for the residential case.

The following general comments provide some indication of commercial fouling

times. Commercial buildings tend to have variable flow rates, which are considerably

148

higher then those in residential systems (suggesting shorter fouling times). Commercial

buildings also have larger coils than residential systems (suggesting longer fouling times)

and also have economizers to introduce fresh air to the building (producing an

indeterminate effect that depends on relative indoor and outdoor concentrations of

particles that would deposit on heat exchangers, economizer filters, and economizer flow

rates). Commercial buildings also tend to have much more complicated duct systems

(longer fouling times) and better filters (longer fouling times) and more regular filter

changes (shorter fouling times). There is no compelling reason to think that commercial

systems foul any slower or faster than residential systems, but a detailed analysis using

the techniques for residential buildings could be done to illuminate this issue. The

analysis would have to be extended to account for multiple heat exchangers (such as a

main coil and individual reheat coils) as well as widely varying flows that can occur in

commercial HVAC systems.

The energy impacts of a doubling in pressure drop of a heat exchanger will vary

depending on the system being considered. Many small commercial systems are much

like large residential systems with the addition of an economizer. The analysis of the

energy impacts in this case is much the same as for residential systems with the fan

energy component representing a larger proportion of total building load. Many large

commercial buildings, and some newer small commercial buildings, have systems that

are designed to deliver either a constant flow (constant air volume systems) or a variable

flow (variable air volume systems) to satisfy a conditioning or ventilation load. These

systems can adjust fan speed over a continuous range to achieve the desired flow. The

governing equation for fan power draw for this type of system is Equation (5.6). A

149

difference from residential systems is in the fan motor efficiencies, which can vary over a

large range for a given fan depending on flow and pressure drop conditions. There are

also many more types of fans that are used in larger buildings. Because of longer and

more complicated duct runs and ventilation requirements, fan energy in commercial

buildings represents a much larger proportion of total building energy than for residential

systems (Modera et al., 1999). The potential costs of fouling are greater and fan energy

increase is likely to be the dominant energy impact of fouling. Also, the heat generated

by fans needs to be removed if fans are in conditioned areas and this effect will increase

the energy consequences of increased fan energy usage.

To analyze the range of impacts of a doubling in pressure drop, the typical HVAC

fan types were selected from the technical literature (Carter et al., 1998; Kuehn et al.

1998; Webster, 2002). The range of efficiencies (the product of ηmotorηfan in Equation

(5.6)), flows, and external static pressures are listed in Table 5.3.

Table 5.3: Commercial HVAC fans.

Fan Type Efficiency (%) Flow (m3/h) Static Pressure (Pa)

Low High Low High Low High Backward Curved 50 80 3400 136000 250 2990

Forward Curved 40 70 300 3400 120 1490

Vane axial 40 65 1400 5900 120 1370

These data are used in Equation (5.6) to determine the energy impacts of fouling

in commercial systems. A further assumption is that coils represent 25 % of the total

150

static pressure drop in commercial systems. This estimate is consistent with analysis of

institutional buildings (Carter et al., 1998) and design guidelines (ASHRAE, 2000).

5.4 Analysis Results

In this section, I will first present the fouling time results for residential systems.

The energy impacts of residential coil fouling are also discussed. Following the

discussion of residential systems, I will present the fan energy impacts of fouling in

commercial buildings.


The fouling times, defined as the time it takes for the pressure drop of the coil to

double at constant flow, varied over a very large range, depending on input parameters.

The mean fouling time for all conditions was 42 years, but this value was skewed by

several very high fouling times (500+ years). The median fouling time was 9.4 years.

The fouling time for the base case (MERV 2 filter, urban outdoor concentration, cycling

air conditioner, dirty indoor environment, typical coil (4.7 fins/cm or 12 FPI), 10% filter

bypass, and typical duct penetration) was 4.3 years.

The fouling time ratio is a measure of how sensitive fouling time is to a specific

change of a given parameter. The fouling time ratio is calculated by holding all

parameters constant except for the parameter of interest. The mean fouling time ratio for

a particular parameter change is the average change in fouling time resulting from

151

changing the value of that parameter. Table 5.4 lists fouling time ratios for changing

each parameter from that of the base case to every other possible value.

Table 5.4: Fouling time ratios.

Fouling Time Ratio Variable Base Casea Going to Median GM GSD

MERV 6 1.40 1.40 1.08 Filter Efficiency MERV 2

MERV 12 7.82 10.6 2.65

Urban Rural 2.24 2.24 1.03

Cycling CA 0.31 0.31 1.08

Indoor Concentration

Dirty Clean 1.59 1.68 1.30

2.4 fin/cm 1.89 1.84 1.08 Coil Efficiency 4.7 fin/cm

7.1 fin/cm 0.70 0.71 1.04

None 1.12 1.81 2.26 Filter Bypass 10%

25% 0.86 0.73 1.38

Simple 0.99 0.99 1.01 Duct Penetration Typical

Complex 1.02 1.02 1.01

aBase Case = MERV 2 filter, urban outdoor concentration, cycling air conditioner, dirty indoor

environment, typical coil (4.7 fins/cm or 12 FPI), 10% filter bypass, typical duct penetration.

The geometric mean and standard deviation were used as descriptive statistics in

Table 5.4 because the particle size distributions and many of the parameters in Equation

(5.2) come from lognormal or composite lognormal distributions. As a simple test, the

median of each distribution was compared to the geometric mean (they should be equal

for a true lognormal distribution). In all cases, there was less than a 5% discrepancy with

152

the exception of changes of filter efficiency and filter bypass, which had much larger

discrepancies (up to 38%). The non-lognormality of the results for these parameters has

to do with the interactive effects between these two variables. The data in Table 5.4 also

appears graphically in Figure 5.11. The error bars do not represent an uncertainty, but

represent one geometric standard deviation above and below the geometric mean for

changing the parameter for all cases.

MER

V 6

MER

V 1

2

Rur

alC

ontin

uous

Cle

an

2.4

fin/c

m7.

1 fin

/cm

Non

e25

%

Foul

ing

Tim

e R

atio

0

1

2

3

4

5 FilterBypass

Indoor AirConcentration

FinSpacing

FilterEfficiency

10.6

Figure 5.11: Fouling time ratios. Error bars indicate one geometric standard deviation above and below the mean. Base Case = MERV 2 filter, typical coil (4.7 fins/cm or 12 FPI), urban outdoor concentration, cycling air conditioner, dirty indoor environment, 10% filter bypass.

From the results in Table 5.4 and Figure 5.7 the importance of varying each

parameter becomes clear. Filter efficiency, particularly going to a MERV 12 filter from

the base MERV 2 filter, has a large impact on fouling times, causing the fouling time to

increase, on average, by ten times. There is substantial variation in this value because of

the interaction between filter bypass and filter efficiency. For very high efficiency filters,

153

filter bypass makes a big difference in whether or not particles are available to deposit on

the heat exchanger. Increasing the indoor particle concentrations also has a big impact on

fouling times. Going from a typical urban to typical rural location increases fouling time

by about a factor of two on average. This increase is caused by the lower outdoor

concentration of particles in rural environments. Running the air conditioner

continuously has an even larger effect on fouling time (decreasing it by two thirds on

average), largely because the coil is continually exposed to particle-laden air. This effect

is somewhat moderated by the fact that the continually cycling air is also continuously

filtered by the HVAC filter and other components. Eliminating resuspension of indoor

particles and dust fibers increases the fouling ratio by a factor of 1.5. Changing the filter

bypass causes a 25-50% change in fouling time on average; however, there is a strong

interactive effect with filter type. The added efficiency of a MERV 12 filter can be

largely compromised by filter bypass. Correspondingly, filter bypass does not

significantly degrade the performance of a MERV 2 filter.

Another important result of this study is that, over the 0.01 – 100 µm particle

diameter range considered, the particles that are most responsible for fouling are those in

the size range between 1 – 10 µm. The contribution to fouling by particle size is shown

in Table 5.5 for all simulation cases, for the subgroup of dirty cases, and for dirty cases

with non-zero filter bypass. Although larger particles cause more of a pressure drop

when they deposit, and they deposit with high efficiency, they are also more likely to be

filtered or to deposit in return ductwork. Also, large particles exist in indoor air at much

lower concentrations than small particles. A related result is that even submicron

particles, which are relatively unlikely to deposit on the coil, contribute to fouling

154

because they exist in indoor air at very high concentrations and are relatively unlikely to

be filtered or deposit in duct work. Fibers are estimated to contribute 22% of total

fouling mass, on average, in homes where they deposit on heat exchangers (dirty cases

with non-zero filter bypass). This significant contribution suggests that more research on

indoor residential fiber concentrations would be useful in order to evaluate their impact

on fouling, particularly given the scant data on indoor fiber concentrations. Such data

would also resolve the discrepancy between forensic microscopy, which suggests that

most of heat exchanger fouling is by dust fibers rather than spherical particles, as

suggested here.

Table 5.5: Contribution to mass deposited by particle size.

Particle Size Range (µm) 0.01 - 0.1 0.1 – 1 1 - 5 5 - 10 10 - 100 Fibers All cases µ 0.2% 9.4% 48% 29% 6.7% 7.3%

n=648 σ 0.4% 13% 13% 10% 7.8% 15%

Only dirty µ 0.2% 8.1% 38% 25% 13% 15%

n=324 σ 0.4% 13% 11% 8.5% 5.8% 18%

Dirty/filter bypass µ 0.1% 4.0% 34% 26% 14% 22%

n=216 σ 0.1% 3.4% 10% 5.9% 3.5% 18%

Table 5.6 shows the pressure drop and flow through a typical coil when both

clean and also when fouled enough such that its pressure drop at constant flow has

doubled. Although the pressure drop at constant flow doubles (as measured in the

155

experimental data), the consequent reduced flow from the added pressure drop causes a

less than doubling of the pressure drop at the new flow. This effect is included in the

analysis. Although the resulting flows and pressure drops are substantially different, the

flow was reduced by 5 – 7%, regardless of which fan curve was used. Much greater

impacts are possible for systems with already reduced flow or on a steeper point on the

fan curve.

Table 5.6: Flow reduction and pressure drop for different fan curves.

Heat Exchanger Pressure Drop (Pa)

Flow (m3/h)

Fan Curve Source Clean Fouled Clean Fouled Reduction

ACCA (1995) 54.0 83.4 2280 2160 5.4%

Parker et al. (1997) 36.1 49.9 1860 1780 5.8%

Measured 32.8 41.8 1780 1660 6.5%

Once this effect on flow was determined, I used the experimental work of Parker

et al. (1997) and Palani et al. (1992) to estimate the effect of reduced flow on air

conditioner performance. For a properly tuned air conditioner, a 5 - 10% drop in flow

causes a 2 - 4% drop in Energy Efficiency Ratio (EER), capacity, and power draw.

However, for a more marginal system (i.e. a system with insufficient air flow across the

coil), these effects can be 10 – 20% or even greater. Also the effect of low refrigerant

charge can have an interaction with low airflow, further degrading system performance

(Proctor, 1997).

156

The total external static pressure for the system as well as the power draw appears

in Table 5.7. In a system with a fouled coil, the flow drops by 5 – 7%, but the pressure

increases by 6 – 16%, so the power draw of the fan increases by 1 - 10%, depending on

the fan curve being used. This contradicts the fan laws, which suggest that the fan power

would decrease by 15 – 18 %. Using the Parker et al. (1997) measured data, the fan

power would decrease by 3.8 - 4.6%. Although beyond the scope of this dissertation,

more work needs to be done to ascertain both the sign and to assess the magnitude of fan

energy use changes resulting from an increased system pressure drop and a corresponsing

decreased flow. In the absence of research on fan energy, my results suggest that

residential fan power draw increases owing to coil fouling by an amount in the range of 5

- 60 W, with an additional penalty of this heat having to be removed from the air stream

during cooling operation.

Table 5.7: Fan power for clean and fouled coils.

Fan Curve Source

External Static Pressure (Pa)

Fan Power (W)

Clean Fouled Clean Fouled Increase Predicted Decreasea

ACCA (1995) 179 208 567 624 10 % 15%

Parker et al. (1997) 158 167 408 413 1.2 % 18%

Measured 161 175 398 403 1.4 % 16%

aBy application of the P α Q3 fan law.


Table 5.7 shows the range of fan power increases for commercial HVAC fans.

The assumptions that went into this table are that the flows, static pressures, and

157

efficiency conditions are as described in Table 5.3. Table 5.8 suggests relatively modest

impacts for low speed fans at low pressures, but as fan speed increases, the impacts can

become very large, particularly for low-efficiency fans. Given that building fans

represent 9% of total commercial building electricity use (Modera et al., 1999) for larger

systems, these effects can be significant. Furthermore, the values in Table 5.7 do not

include the additional cooling required to remove the fraction of motor heat that is

dissipated into conditioned space. This amount will further increase the consequences of

fouling.

Table 5.8: Commercial building fan power increase (W) based on fan type and flow and pressure conditions.a

Flow/External Static Pressure Fan Type Low High

Low Efficiency 120 W 56500 W Backward Curved

High Efficiency 70 35300

Low Efficiency 6 900 Forward Curved


Low Efficiency 30 1400 Vaneaxial


aSource data from Table 5.3 used in Equation (5.5). Efficiency data for each fan type is from columns 2

and 3 of Table 5.3. System airflows and external static pressures for different fan types are from columns 4

- 7 of Table 5.3.

158

5.5 Discussion

In this section, I will discuss the implications of the results for residential and

commercial systems.


The fouling time of the base residential case was 4.2 years. This is within the

range of 4-7 years reported by Krafthefter et al. (1987). The median fouling time for all

cases was 9.4 years, longer than Krafthefter et al. suggest. The primary reason for the

difference is because Krafthefter et al. used higher indoor particle concentrations in their

experiments and simulations than I considered here.

It is important to put the fouling time in the context of the lifetime of the coil.

Typical residential coils have an approximate lifetime of about 15 years. However,

indoor evaporator coils frequently remain in service even when the outdoor portion of the

system or the compressor is replaced. Indoor coils often stay in service for 30 years.

From this perspective, a conservative fouling time of approximately 15 years or less is

the target for when remedial action (such as coil cleaning or improved design or filtration

to limit fouling) should be considered. This work suggests that coils foul such that their

pressure drop (at constant flow) typically increases one and a half to four times over a 15-

year period.

We have used the doubling of the clean coil pressure drop at the original flow as a

measure of a fouled coil. For this level of pressure drop, in a typical residential system,

the airflow is reduced by 5 - 10%, and the efficiency and capacity of the air conditioner is

159

decreased by 2 – 4%. This is a relatively modest decrease in performance; however, the

results assume that the system started with correct airflow. Several researchers (Parker et

al., 1997; Proctor, 1997; Proctor, 1998a) have found that low air flow is common in

many residential air conditioning systems and hence performance impacts can be much

greater because the change in air conditioner capacities are more sensitive to flow

changes at lower air flows.

Coil cleaning is not a routine part of maintenance in residential systems, and it is

unclear whether coil cleaning always removes deposited material, rather than just pushing

it deeper into the coil. If deposited material is not removed from a coil, the pressure drop

at constant flow continues to increase at a geometric rate (see Figure 3.11), assuming

non-asymptotic behavior. After twice as long as the fouling times reported in this paper,

the coil pressure drop, at constant flow, will have increased by about a factor of four.

This can lead to much more serious airflow reductions (10 - 20%) and performance

degradations (5 - 15%). Even greater pressure drops might result if coil penetration

fractions decrease as fouling (particularly with fibers) occurs.

Coil fouling may also change duct distribution losses. The increased pressure drop

at the coil will lead to higher static pressures in the air handler cabinet upstream of the

coil and lower static pressures in the ducts. These pressure differences can cause more or

less duct leakage at each of these locations. However, the decrease in flow rate also leads

to diminished duct leakage. The net effect is not clear as there is very little research on

the effect of reduced or increased pressure drop on duct leakage, but it is a topic of future

research interest. However, reduced flows would lead to increased conduction losses (βs

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and βr in Equation 1 in Siegel et al. (to be published in 2003)), although the effect is

likely to be small because of the small changes in flow in typical systems.

The effects on residential fan power are also small. Although theory predicts a

large decrease in fan power draw, and measured data suggest a small decrease in power

(Parker et al., 1997), the application of the system curve and the duct curve predicts a

small increase in power of 1 - 10%, depending on which fan curve is used. This can be

considered to be a small portion of the overall performance degradation of the system.


According to Modera et al. (1999), fan energy accounted for 9.0 % of the 87 TWh

of total electricity consumption in California commercial buildings in 1997. Doubling

the pressure drop across a heat exchanger, particularly in large office buildings with high

HVAC flows and low-efficiency fans, can lead to over 50 kW of additional demand and

20 MWh of additional annual energy use in a single air handler. These are substantial

impacts, and they suggest that the problem of coil fouling in commercial buildings

deserves more attention.

Although coil cleaning is a routine part of maintenance procedures in commercial

buildings, there is relatively little data that verifies its efficacy. Carter et al. (1998)

investigated pressure drops and cleaning efficacy in reheat coils in several university

campus buildings (their Table 3.2). They report pressure drops for four reheat coils in

their as-found condition, after cleaning, and design values (Table 5.9). Their as-found

pressure drops were 50 – 400% times greater than the design values. Cleaning the coils

reduced the average pressure drop to 13% greater than design values. Although this is a

161

small data set, it does suggest significant potential for cleaning to mitigate adverse affects

of fouling.

Table 5.9: Pressure Drop of Four Reheat Coils (Carter et al., 1998).

Pressure Drop of Reheat Coils (Pa) Pre-Cleaning Post-Cleaning Design

237 97 60

87 67 57

100 50 62

122 75 82

5.6 Conclusions

In this chapter, I applied experimental and simulation results describing particle

deposition on evaporator coils, as well as research about indoor particle and dust

concentrations to estimate the fouling rates and energy impacts of coil fouling. The

results suggest that typical residential heat exchangers foul rapidly enough to double

evaporator pressure drop (at constant flow) in about 9 years, on average. The fouling

time for a base case was 4 years. This is considerably shorter than the typical evaporator

coil lifetime of 15 - 30 years. The most important parameters in determining coil fouling

times are indoor particle concentrations and the efficiency of the filter. Filter bypass and

fin spacing are secondary, but still important factors. Efforts to improve the prediction of

fouling time would greatly benefit from more detailed information about large particle

(>10 µm) concentrations in indoor air.

162

The reduced air flows that result from coil fouling cause typical efficiency and

capacity degradations of less then 5% in residential systems; however, they can be much

greater for marginal systems or extreme conditions. The importance of residential air

conditioning energy use means that these degradations also may affect peak electricity

demand. This effect on peak demand is complicated because the overall power draw of a

house with a fouled coil is smaller than the same house with a cleaned coil (power

consumption decreases 2 - 4%). But, the capacity of the air conditioner decreases more

than the power consumption does, which suggests that the air conditioner will have to run

for longer in the house with the fouled coil in order to satisfy the building load.

Depending on the timing of the additional operation, and when averaged over a large

number of homes, the net effect can be to increase peak demand or to increase the

duration of peak power needs. Additional energy consequences resulting from increased

fan power draw and potentially increased duct leakage amplify the magnitude of the

potential energy consequences. Residential commissioning procedures should include

coil inspection and verified cleaning (measured pre- and post-cleaning pressure drops as

well as comparison to design values) to mitigate against adverse energy and indoor air

quality consequences.

The energy impacts of coil fouling in commercial buildings can be considerably

larger than those in residential buildings. Also, since fan power is a much larger

proportion of building electricity use, commercial building coil fouling can substantially

increase the power demand and energy use of individual buildings. Although coil

cleaning is already a part of routine maintenance procedures in many commercial

buildings, greater attention should be paid to verification of the outcome of cleaning

163

protocols. Additional research on manufacturers’ claims of significant energy-use gains

from cleaning commercial heat exchangers should be verified in a random and

statistically significant sample of buildings.

164

CHAPTER 6: CONCLUSIONS

Particulate fouling of HVAC heat exchangers can lead to negative energy and

indoor air quality impacts. This work investigated the mechanisms and consequences of

particle deposition on fin-and-tube heat exchangers.

A deposition mechanism model suggests that particles between 0.01 and 1 µm do

not deposit to a significant extent on typical HVAC heat exchangers. These particles are

too large to diffuse to the walls over their short residence time in fin channels and are too

small to deviate significantly from fluid streamlines around fins and tubes or be affected

by air turbulence. Coarse particles (1 – 10 µm) deposit by fin edge impaction with a

minor contribution by gravitational settling. Deposition fractions of up to 20% are

common for this size range over a typical range of air velocities. Very coarse (10 µm and

larger) particles deposit by impaction on refrigerant tubes and gravitational settling on fin

corrugations. Complete deposition occurs for 50 µm and larger particles for the range of

velocities (1 - 4 m/s) and fin spacings (2.4 – 7.1 fin/cm) considered.

Relative to isothermal conditions, the addition of cooling causes a modest

increase in deposition for all particle sizes. The biggest relative increase occurs for 0.01

– 1 µm particles. These particles can have deposition fractions as high as 5% for typical

temperature, velocity and fin spacing conditions. The further addition of condensed

moisture increases deposition significantly. This increase is caused by the narrowing of

fin channels, and the increases in the effective thickness of the fins and diameter of the

refrigerant tubes.

165

Experiments to verify the simulation work were conducted over a range of

particle sizes and air velocities on a 4.7 fin/cm test heat exchanger. Increasing the air

velocity leads to increased deposition. The results suggest reasonable agreement with the

modeling work. The experiments demonstrate more deposition than the model predicts,

particularly for larger particles at higher velocities. The experiments verify the shape of

the deposition fraction versus particle diameter curves. Discontinuities in the fins and

unknown details about the propagation of air turbulence into the heat exchanger are

postulated to be responsible for the difference between experimental and modeling

results.

The addition of cooling causes an increase in measured deposition that is slightly

larger than the predictions of the model. The inclusion of condensed water on the surface

also leads to considerably more deposition than the model predicts. The shape and

location of the condensed water layer is hypothesized to cause these discrepancies.

Experiments to foul the test heat exchanger with standard test dust suggest a

monotonically increasing relationship between pressure drop and mass of dust deposited

on the heat exchanger surface. There is a clear induction period in the results, but no

asymptotic limit was reached even though the heat exchanger was fouled to more than

double its original pressure drop. Face fouling was found to be an important contributor

to the overall increase in pressure drop.

The measured and simulation results were applied to explore the potential for

bioaerosol deposition on HVAC heat exchangers. The results, as well as data in the

literature, suggest that fungi and bacteria, and their spores, will deposit on heat exchanger

166

surfaces. Environmental conditions are often adequate for their growth and

amplification. However, the precise connection between bioaerosol deposition and

microbiological growth has not been studied. Bioaerosol deposition may not be the

limiting factor to growth. The spread of biological colonies from contaminated heat

exchangers to other HVAC surfaces, as well as to conditioned air, has been demonstrated

by other researchers in a small number of buildings. This suggests that the problem

deserves further attention.

Further simulation led to estimates that residential HVAC heat exchangers foul

enough to double their pressure drop in about 4 - 9 years with substantial variations

depending on filtration efficiency, filter bypass, heat exchanger geometry, and indoor

particle concentrations. This is a short enough time period to merit cleaning the surface.

However, the energy and performance impacts in a well tuned system that result from

this fouling are relatively small: flow through the system drops by 5 - 6%, and capacity,

efficiency, and power draw drop between 2- 4%. The marginal impact of these effects on

poorly tuned systems is larger, particularly in systems that are already on a steep part of

the fan curve or have insufficient refrigerant charge.

Fouling times in commercial systems were not estimated due to the diversity in

size and number of coils, duct system layouts, and filtration options. However, the

energy impacts of fouled coils in commercial systems are much more significant than in

residential systems. Fan power represents about 9% of commercial-building electricity

use and fouling has the potential to add more than 50 kW of peak power to the load of a

large commercial building.

167

Fouling has the potential to cause significant problems and merits further

attention. Particular research issues that would contribute to our understanding of the

phenomenon include the collection of experimental data for deposition of dust fibers and

other large particles that are found on heat exchangers in real environments. More

general research on the prevalence and behavior of large particles and fibers in indoor

environments would also be a substantial contribution. Although there is very limited

regulatory interest in these particles, and there are substantial experimental challenges for

accurate sampling, their importance in the fouling problem and possible association with

bacteria and other viable biological material makes them worthy of further study.

Biological growth has been anecdotally reported on a large number of systems, and

demonstrated (in the archival literature) to be present on a much smaller number of

systems. Further investigation of the frequency of growth, and the responsible species, in

more buildings would be useful in directing future work. Study of the direct connection

between biological growth on heat exchanger surfaces and sick building symptoms

should also be undertaken.

Although the energy consequences of heat exchanger fouling in residential

systems are typically small, this study raised issues about the shape of fan and efficiency

curves in real systems. Work to investigate their shape in a statistically significant

number of homes could be applied to increase the accuracy of fouling predictions, as well

as to influence the study of duct distribution losses, fan electricity use consequences, and

duct system design.

This study has demonstrated that particulate deposition in a complex geometric

system can be modeled reasonably accurately with a computationally simple approach.

168

The generation of new experimental data on particle deposition on heat exchanger coils is

likely the largest contribution that this work makes. The application of the experimental

and simulation results, combined with other work in the literature, has allowed for

estimation of fouling times and their sensitivity to several key parameters. The problem

of heat exchanger fouling deserves more research attention as both a cause of indoor air

quality problems and also a cause of air conditioning performance degradation.

169

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APPENDIX A: EXPERIMENTAL PROTOCOLS

Contents

Mixing Particle Solution............................................................................................180

Using the Fluorometer ...............................................................................................181

Calibrating the Fluorometer.......................................................................................182

Setting up an Experiment...........................................................................................183

Starting an experiment ...............................................................................................185

Using the APS to measure particles...........................................................................187

Ending an Experiment................................................................................................188

Extractions .................................................................................................................189

Cooling and condensing experiments ........................................................................190

Pressure Drop Experiment .........................................................................................191

Laboratory and Contact Info

Wet Laboratory 644 Davis Hall (510) 642-4135 Apparatus 136D Davis Hall No phone Office 659 Davis Hall (510) 642-5323 Professor in charge of laboratory Professor Nazaroff: [email protected] (510) 642-1040 Jeffrey Siegel: [email protected] At LBL: (510) 495-2780, at home (510) 841-8351 Mark Sippola: [email protected] At UC: (510) 642-5323

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Mixing Particle Solutions Jeffrey Siegel 4/16/01

1. The purpose of mixing particle solutions is to prepare solutions for the vibrating

orifice aerosol generator (VOAG). Cleanliness is very important as contamination can dramatically affect particle size – use clean glassware and wear gloves.

2. The recipes for current particle sizes are in the following spreadsheet Current particle solutions (as of 3-21-2001).xls

3. Small quantities (<1ml) of oleic acid should be measured with the µL pipette. Do not set the dial above 200µL as it distorts the diaphragm. Practice with a scale and distilled water until you develop good technique. Dispose off all tips after a single use. Large quantities of reagents (>100ml) should be measured with volumetric flasks (kept in 667 Davis). 1-100ml pipettes are kept in 643 Davis Hall.

4. All solutions should be labeled with tape listing their name, who made them, their constituents, and the date.

5. Solutions should be double sealed with parafilm.

6. Cleanup: All pipettes should go in the dirty pipette bin. When there is enough to be washed, use the pipette washer in 643 Davis. All of the dirty glassware should go in the dirty glassware bin. When there is enough for a load, it should be washed in the dishwasher (which is currently broken – 4/16/01). All counters should be cleaned, etc.

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Using the Fluorometer Jeffrey Siegel 4/16/01

1. The purpose of the fluorometer is to measure the fluorescein (or other fluorescent

material) content of a solution. Our hands have oils on them than can be fluorescent: make sure that you wear latex gloves and replace them if they get contaminated.

2. Turn on the fluorometer – it takes 10 minutes to warm up. Using optical tissue to clean off any dried buffer on the cuvette (small test tube) holder or lip of fluorometer.

3. Take a reading with the solid standard in both positions.

4. Make sure that the solution that you are measuring is well mixed.

5. Before reading a sample make sure that the cuvette is mostly full, and that you have wiped the outside with optical tissue. Take care not to spill liquid by dropping it into the fluorometer.

6. Let the reading stabilize, but don’t let it go too long as the light will break down fluorescein over a timescale of ~minutes. You will notice this particularly with high concentrations.

7. Take care to keep things organized – it is easy to mix up solutions.


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Calibrating the Fluorometer Jeffrey Siegel 4/16/01

1. The fluorometer needs to be calibrated ~monthly because it drifts over time. It is

crucial to accurately measure the stock solutions. A small error in the fluorescence of one of the test solutions can introduce uncertainty for all future experiments done with that calibration.

2. Print out the existing calibration by going to the calibration menu (by pressing ENT) and then pressing the D button. The printer must be turned on.

3. Test the solid standard in both positions, write it on the printout, and put the printout in the lab book.

4. Mix the following solutions (the spreadsheet fluor_calib.xls contains the mixtures). Small quantities (<1 ml) should be measured with the µL pipette. Do not set the dial above 200µL as it distorts the diaphragm. Practice with a scale and distilled water until you develop good technique. Dispose off all tips after a single use. Large quantities of reagents (>100ml) should be measured with volumetric flasks (kept in 667 Davis Hall). 1-100ml pipettes are kept in the drawers on the south wall of 643 Davis Hall.

5. Follow the calibration directions in the fluorometer manual for a 5 solution direct

concentration calibration. Set the max concentration at 125 ng/ml.

6. Print out new calibration – if calibration is not linear, then make new solutions are repeat it.

7. Test solid standard in both positions and write it on calibration.

8. Paste calibration printout in lab book and give a copy to Mark.


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Setting Up an Experiment Jeffrey Siegel 4/16/01

1. The purpose of setting up an experiment is to get everything ready so that you can

start an experiment fairly quickly. Whenever sticking your hands inside of the duct wear gloves and then dispose of them. The duct is full of fluorescein and it is easy to contaminate filters and other parts of the experiment.

2. Bring drill, coil, lab notebook, five 0.180 nozzles and filter holders, particle solution, IPA (if needed) downstairs to 136D Davis Hall.

3. Put mass flow controller or pumps where they will be useful to you. Tee pumps as necessary. Turn on pumps so that they warm up. Also turn on the mass flow control and the associated pump. Make sure all hoses are off the floor so that you don’t suck up dirt. Make sure Gilibrator (check with De-Ling and Mark) will be available when you want it and that it is charging.

4. If the coil, the nozzles, or the filter holders are wet, then use the compressed air source to dry them completely. Wear safety goggles (in the drawer below the tool drawer) when doing this.

5. If Mark has used the apparatus last:

a. Reset dampers (using big wrench) to isolate the top section of duct.

b. Seal off open sections at top of duct with duct sealing tape reinforced with blue tape.

c. Replace missing duct section in bottom duct run with duct standing up against the wall. Seal seams with duct sealing tape and blue tape.

6. Put in 5 isokinetic nozzles. Make sure that they are appropriately aligned – pointing directly upstream. The usual procedure is #3 furthest upstream, #2 upstream of coil, #1 in the center downstream of coil, #5 downstream of coil at top, #6 downstream of coil at bottom. They should be quite tight so that they don’t rotate, but not so tight that they can’t be removed. You will need to use a wrench inside and another outside of the duct.

7. (Added 5/15/01) 5 nozzles should be place upstream in an +-pattern in the duct. The usual pattern is #2 on the centerline, #3 in the top middle, #4 on the right (wall-side) middle, #5 on the left (tunnel side) middle, and #6 in the top middle. Nozzle #1 should be placed on the centerline downstream of the duct.

8. Attach coil using drill, screws, and wing bolts. It is only necessary to put in 8 screws on each side. Do final tightening with a screwdriver.

9. Attach HEPA filter duct at end of coil. Also attach break in duct between damper and coil. Tape over all exposed seams with duct sealing tape reinforced with blue tape.

10. Turn on fan to appropriate speed (12.3 Hz = 1.5 m/s, 16 Hz = 2.1 m/s, 36 Hz = 5.2 m/s) and straighten duct

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11. Thoroughly leak check all seams, joints, dampers, etc with the smoke stick or your hand and seal any leaks with foil tape. Any leaks can lead to intrusion of ambient particles or lead to inflated estimates of deposition.

12. Put filters in filter holders (use clean gloves and tweezers).

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Starting an Experiment Jeffrey Siegel 4/20/01

1. The purpose of these steps is to start the experiment in a repeatable way and to find

problems before injecting particles. All steps should be recorded in the lab notebook following the format of previous experiments. The experiment information should be entered in the table of contents. Make copious notes about any problems or other issues.

2. Turn on fan to appropriate speed (12.3 Hz = 1.5 m/s, 16 Hz = 2.1 m/s, 36 Hz = 5.2 m/s).

3. Check for leaks, especially at duct connectors, coil joints, and open nozzle and sensor holes. Straighten the duct.

4. Measure the velocity pressure with the pitot tube (both hoses connected) at all isokinetic nozzle locations. Uses the grooves in the pitot tube to correctly orient the tip. You are trying to measure the velocity right in front of the isokinetic nozzle entrance. Record the values in the lab notebook. Check to see that they are similar to previous days and look for and resolve any leaks, obstructions, or other problems if they are not.

5. Enter the nozzle diameter (from table), the pump designation (MF1-4, Blue), and the velocity pressure measurements into a new dep_temp.xls to find out the velocities and the required pump rates for isokinetic sampling:

6. Rename the dep_temp.xls to a new name that is the date mmddyy_expt.xls (i.e. 041701_expt.xls). Separately record any changes that need to be made to dep_temp.xls.

7. Find the required pump rates for isokinetic sampling from the spreadsheet and record them in the lab notebook.

8. Set the pumps/mass flow controllers to the right flows using the Gilibrator. Take ten good readings and record the average. Watch for drifting in the flow rate and act accordingly. Record the pump flow as the initial pump flow.

9. Start the procedure for generating particles with the VOAG (instructions on the VOAG, on the wall near the VOAG, in the lab notebook, and in this file). While waiting for fluids to pump through, you can install filters and filter holders (if you haven’t already done so). You can also do a final check on the pump flows with the Gilibrator and record the values as the Pre-Test Pump Flow rate in the lab notebook and in the spreadsheet.

10. Once you have a mondisperse particle stream, let it run into a paper towel for a few minutes (to check for stability) while you straighten up the lab, connect the pumps to the filters, and fill in any remaining details on the spreadsheet and in the lab notebook.

11. Measure background particle sizes with the Aerodynamic Particle Sizer (APS) (details on a later page). Save file in Jeff directory as APS2_mmddyy_bkgd.a20.

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Also export file as APS2_mmddyy_bkgd.txt. Backup both files on the floppy and on the lab computer.

12. Connect the particle stream to the mixing box, record the starting time (there is a clock on the mixing box – that is official experimental time) in the lab notebook and in the spreadsheet.

13. Do another APS run. Save file in Jeff directory as APS2_mmddyy_start.a20. Also export file as APS2_mmddyy_start.txt. Backup both files on the floppy and on the lab computer.

14. Backup all files and lock the door.

15. The following need to be done for all experiments either before you start injecting particles, or right after you finish injecting particles, but before you start taking things down.

16. Use the marked pitot tube to measure the velocity in a 4x4 grid pattern in the duct in the marked location just upstream and about 8 ft (2.5m) downstream of the coil. Use the grooves and marks on the pitot tube to help you. Make sure that the pitot tube is level and pointing directly downstream. Record each velocity measurement in the book and then in the spreadsheet. If the bulk velocities in the two locations are more than 1% different, check for coil leakage, note anything in the lab notebook and in the spreadsheet. If no coil leakage is evident, remeasure up and downstream velocities.

187

Using the APS to Determine Particle Size Distribution Jeffrey Siegel 4/16/01

1. The APS determines the aerodynamic particle size distribution for particles from 0.5-20 µm. The purpose of using it is to determine the size of particles being generated by the APS.

2. Make sure the APS is connected to the computer when the computer is turned on. Turn on the APS (switch on back). Run the Aerosol Instrument Manager (AIM) software from the start menu or from the desktop.

3. If measuring in the duct, make sure that the APS is level, secure, and attached to the nozzle.

4. Go to File, New. If the machine gives an error, try reconnecting the APS to the computer and repeating. If that doesn’t work, then exit and restart the AIM software.

5. Go to Start, Instrument Setup and turn on the pump. When you are ready to start, hit the F10 key or go to Start, Start Sample. If you forgot to turn on the pump, or realize some other problem, then go to Start, Abort Sample, correct the problem and repeat this step.

6. After the sample has finished, go to File, Save and save the data as APS2_mmddyy_bkgd, APS2_mmddyy_start, APS2_mmddyy_middle(# if necessary), APS2_mmddyy_end, APS2_mmddyy_bkgdend. Also go to File, Export and export the number concentrations as a space delimited file. With the same name, but with a .txt extension (inserted automatically by AIM software).

7. Go to File, New and then Start, Instrument Setup and turn off the pump. Exit the software and then turn off the APS. Disconnect the nozzle and cap it. Copy the files onto a floppy and then on to the computer in the lab, and then backup onto a computer at LBL. Turn off computer.

8. Add data to APSbig.xls by importing it into Excel. Pick columns for inclusion, do standard deviation analysis and export data to deposition spreadsheet.

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Ending an Experiment Jeffrey Siegel 5/07/01

1. Wear gloves at all times. Dispose of gloves once they have been inside of the duct.

2. Measure the particle concentrations with the APS and the shrouded probe run to get the particle size distribution. When it is finished, remove the particle hose, record the time, and cap the particle entry hole.

3. Start the VOAG shutdown procedure. While waiting for fluids to pump measure and record the centerline velocity pressures, the pump flow rates, and the static pressures at all nozzle locations. If everything looks reasonable, turn off all pumps. Otherwise, try and do some measurements to determine why flows have changed (such as examining the filters to check for tears, looking for blocked hoses/nozzles, checking for power interruption by looking at the lunchbox file). Finish VOAG shutdown procedure and leave the pump pumping alcohol.

4. Do an APS (Aerodynamic Particle Sizer) run to get the background particle size distribution. Save and backup all APS files.

5. Turn off the fan.

6. Break the duct seam seals at the break upstream of the coil and the break at the reducer to the HEPA filter at the end. Remove the coil.

7. Attach the coil bottom plate. Start with the middle screws on each side. Tighten it up as much as you can, examine the sides to see how much of a gap you have and try to eliminate it.

8. Remove the nozzles and wipe them with paper towels to remove any fluorescein that has deposits on the outside. Dispose of any gloves that have been inside of the duct as soon as you are done.

9. Switch the VOAG to water, make sure that there is enough water in the container to last overnight.

10. Bring the drill, the lab notebook, the nozzles and filter holders, and the coil upstairs to the wet lab.

Don’t forget to turn off the VOAG pump after ~24 hours.

189

Extractions Jeffrey Siegel 5/07/01

1. The purpose of this step is to determine the mass of fluorescein on the coil, filters, filter holders and nozzles. This is the most exact part of the experiment. Wear gloves at all times and change them when they become contaminated. Try not to spill from any of the beakers, and do not cross-contaminate solutions.

2. Turn on the fluorometer. It needs 10 minutes to warm up.

3. You will need to mix buffer as needed. Weight 26.8 grams of sodium phosphate. Fill a 2L volumetric flask ~3/4 of the way full with distilled water. Start the flask mixing on the electric stirrer, and dump in the sodium phosphate. Stop the mixer, fill the flask to the mark with distilled water, and then continue mixing with the electric mixer until there is no suspended material (usually around 20 minutes).

4. Measure out 650ml of buffer and slowly inject it into the bottom of the coil with the syringes. Take care not to spill and also to keep the coil level while filling it. When finished, place it on the large glass tray as some will leak out over the course of the extraction.

5. Measure out 10ml of buffer into 10 clean and dry 250ml beakers. Use a transfer pipette for each beaker and a clean cuvette to measure the background fluorescence of each beaker.

6. Place a filter in the first 5 beakers. Use the same upstream-downstream order as for earlier steps (3-2-1-5-6). Gently agitate each beaker for ~2 minutes. Measure the fluorescence of each solution and dilute as necessary to have the concentration be on scale for the fluorometer.

7. Prepare 5 additional beakers with 10ml of buffer. Use the transfer pipettes to shoot water 5 times in each direction through each nozzle into a beaker. Measure the fluorescence of each solution and dilute as necessary to have the concentration be on scale for the fluorometer. Repeat this process for the top (translucent) portion of the filter holder.

8. Drain the coil (through the bottom) and measure the fluorescence of the solution three times. Dilute as necessary. If there is more than 0.5 ng/ml of variation between measurements, complete additional measurements.

9. Repeat steps 6-8.

10. Add 1500 ml of buffer to the coil (by pouring buffer in over the top of the coil). Agitate for a minute every five minutes. After 30 minutes, drain the coil and measure the fluorescence of the solution three times. Dilute as necessary. If there is more than 0.5 ng/ml of variation between measurements, complete additional measurements.

11. Repeat step 10 until there is an undetectable amount of fluorescein remaining on the coil.

12. Repeat step 6.

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Additions to protocol for cooled and condensing coil experiments Jeffrey Siegel 8/03/01

1. The purpose of this experiment is to measure deposition with a cooled or a cooled and

condensing coil. The protocol is the same as that described above with a few additions

2. The general strategy is to use the insulate cooler and ice water to lower the temperature of the coil. There is no formal temperature control, so you will have to pay attention to the readout on the lunchbox.

3. Fifteen minutes before you start an experiment, start water pumping through the coil. Priming the water pump is a little challenging – the most effective strategy is to either prime it by siphoning it, or by prefilling the coil with water and capping it and then opening it to start it draining. Once started, make sure that the inlet and outlet hose are placed completely under the water in the insulate container.

4. If the experimental goal is to have a condensing surface, the water in the insulated container should be mostly ice. For cooling, it should be about ½ ice and ½ water. You will need to add ice (and potentially remove water) to maintain a constant temperature by checking the conditions every 10 minutes and acting accordingly.

191

Protocol for pressure drop project Jeffrey Siegel 8/03/01

1. The purpose of this experiment is to measure pressure drop across the coil as a function of deposited dust. The dust that we use is SAE course calibrated dust. It is carbonaceous and pretty dirty to work with. Take all appropriate precautions to not spill it. Leave adequate time at the end of experiments to clean everything up. Take particular care to not get the dust on electronic equipment, measurement devices, work surfaces, and any of Mark's apparatus. Also, the fans and pumps are quite loud, so make sure that you wear ear protection (extra ear plugs can be found in the workbench at the apparatus as well as in a paper towel cabinet in the wet lab).

2. Bring coil, lab notebook, dust, and scale downstairs to 136D Davis Hall.

3. Check the mass balance is level.

4. Attach coil using the screws, c-clamps, and binder clips to tighten the sides.

5. Put filters in filter holders (use clean gloves).

6. Make a note of which pressure transducers and recording devices you're using for each pressure. Also, make a note of which pumps you are using at each location.

7. Measure flow rate on pumps using APT. Use the dustexpt Teclog configuration and make sure that you save the data file. Also beware of the fact that Teclog will crash if you tab to another window for too long.

8. Measure and calculate isokinetic velocity using spreadsheet.

9. Turn on fan and add tape and sheet metal or wooden board to get isokinetic velocity at nozzles. Make sure that you secure fan blockage in place so that it does not move.

10. Add valve to pump outlet if needed.

11. Thoroughly leak check all seams, joints, dampers, etc with the smoke stick or your hand and seal any leaks with foil tape. Any leaks can lead to intrusion of ambient particles or lead to inflated estimates of deposition.

12. Recheck isokinetic velocity at nozzles.

13. Measure duct velocity in two places (upstream and downstream of the coil). And verify that there is less than 1% difference between them

14. Weigh about 25g grams of dust, record exact mass, and put in sifter. Cover sifter with plastic bag to capture dust.

15. Tare weighing dish, weigh and record filter weights, and put in new filters and make sure doors are sealed.

16. Record initial coil pressure drop.

17. Put dust in air stream.

18. Stop the air flow. Open doors and weigh filters. Also weigh mass of dust remaining in sifter. Also weigh dust in plastic bag.

19. Repeat steps 13-17 until coil pressure drop doubles.

192

20. Every six dust insertions remeasure the isokinetic velocity. Every 10 insertions measure the duct velocity.

21. The experiment is finished when the coil pressure drop doubles. However, if you have time keep adding dust until the pressure drop is very large.

22. After experiment, take lots of pictures with digital camera (to assess uniformity of mixing). Weigh dust that has fallen to the floor of each duct section (resolved by 6” length if possible). Weigh dust that has accumulated in front of each nozzle and in the mound directly underneath sifter.

23. Clean everything up.

24. Remove the coil. Bring the lab notebook and the coil upstairs to the wet lab. Wash the coil.

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APPENDIX B: TABULATED EXPERIMENTAL DATA

Table B.1: Data from isothermal and non-isothermal deposition fraction experiments

Date

Duct Air Bulk

Velocity Aerodynamic Diameter Deposition Fraction

U da uncertainty η uncertainty Notes (m/s) (µm) (µm) (%) (%)

Isothermal – 1.5 m/s air velocity 2/14/2001 1.5 4.9 0.3 5.1 0.1 2/16/2001 1.5 1.1 0.1 0.2 0.1 11/6/2000 1.4 2.3 0.2 5.9 0.2 11/14/2000 1.5 3.7 0.2 8.3 0.2 4/24/2001 1.5 2.9 0.2 8.6 0.2 4/26/2001 1.5 3.0 0.3 8.4 0.2 repetition 4/30/2001 1.5 3.1 0.3 8.3 0.2 repetition 5/7/2001 1.5 8.6 1.0 10.2 0.3 5/23/2001 1.5 5.7 0.6 6.2 0.2 8/29/2001 1.5 13.1 1.1 14.2 0.0 11/1/2001 1.5 2.8 0.6 7.0 0.5

Non-isothermal – 1.5 m/s air velocity 9/15/2001 1.5 7.6 1.2 13.3 0.3 c3 9/19/2001 1.5 11.9 1.0 14.8 0.4 c2 11/13/2001 1.5 2.7 0.5 8.1 0.2 c1 9/27/2001 1.5 9.1 1.8 49.7 4.1 cc6 9/25/2001 1.5 9.0 1.6 27.4 1.8 cc5 11/9/2001 1.5 2.3 0.4 20.7 0.5 cc4

Isothermal – 2.2 m/s air velocity 2/28/2001 2.2 1.1 0.1 0.3 0.1 11/19/2000 2.2 2.4 0.2 7.5 0.3 11/21/2000 2.2 4.1 0.3 9.7 0.3 5/8/2001 2.2 8.6 0.5 12.0 0.3 9/1/2001 2.2 13.4 0.8 20.1 0.4

Isothermal – 5.1 m/s air velocity 2/10/2001 5.0 1.0 0.1 3.3 2.2 3/4/2001 5.1 2.2 0.1 5.0 1.2

10/16/2000 5.2 2.3 0.2 5.1 1.1 5/15/2001 5.1 5.3 0.2 15.3 1.4 5/17/2001 5.1 5.3 0.3 16.5 1.4 repetition 5/21/2001 5.2 8.3 0.5 31.6 2.4 5/22/2001 5.1 5.6 0.5 18.4 1.4 repetition

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Table B.2: Leading edge fraction for isothermal experiments

Date

Duct Air Bulk

Velocity Aerodynamic

Diameter Deposition Fraction

Fraction on Leading edge and first 5 mm

U da η (m/s) (µm) (%) (-)

2/14/2001 1.5 4.9 5.1 0.35 2/16/2001 1.5 1.1 0.2 0.39 11/6/2000 1.4 2.3 5.9 0.49 11/14/2000 1.5 3.7 8.3 0.55 4/24/2001 1.5 2.9 8.6 0.59 4/26/2001 1.5 3.0 8.4 N/A 4/30/2001 1.5 3.1 8.3 0.48 5/7/2001 1.5 8.6 10.2 0.72 5/23/2001 1.5 5.7 6.2 0.64 8/29/2001 1.5 13.1 14.2 0.66 11/1/2001 1.5 2.8 7.0 0.52 2/28/2001 2.2 1.1 0.3 0.52 11/19/2000 2.2 2.4 7.5 0.44 11/21/2000 2.2 4.1 9.7 0.58 5/8/2001 2.2 8.6 12.0 0.69 9/1/2001 2.2 13.4 20.1 0.74 2/10/2001 5.0 1.0 3.3 0.48 3/4/2001 5.1 2.2 5.0 N/A

10/16/2000 5.2 2.3 5.1 0.39 5/15/2001 5.1 5.3 15.3 0.51 5/17/2001 5.1 5.3 16.5 0.53 5/21/2001 5.2 8.3 31.6 0.45 5/22/2001 5.1 5.6 18.4 0.55

195

Table B.3: Data from pressure drop experiment

Relative Pressure

Drop Normalized Mass Deposited ∆P/∆Pinitial Mcoil/Ac Uncertainty

(mg/m2) (mg/m2)

0.9851 3.3365 0.3550 0.9440 6.8282 0.5408 0.9627 14.1413 0.9298 0.9664 20.6316 1.2751 1.0784 25.4936 1.5338 1.1343 33.6468 1.9675 1.1493 39.4601 2.2768 1.1866 46.3465 2.6431 1.2313 53.8884 3.0444 1.2612 59.8776 3.3630 1.2910 67.4416 3.7654 1.3955 80.4359 4.4567 1.4403 87.2216 4.8177 1.4813 95.6828 5.2678 1.6082 102.0346 5.6057 1.6791 109.1526 5.9844 1.8657 123.7653 6.7618 1.8881 129.3933 7.0612 1.9776 133.9091 7.3015 2.0560 139.2738 7.5869 2.1418 143.8872 7.8323 2.1493 147.3727 8.0177 2.2351 152.8662 8.3100

196

APPENDIX C: MICROSCOPY ON FOULED COILS

In this appendix, the results of examining the fouling agents on two coils are

presented. Very little is know about the history of the coils, but they both are about 10

years of age and came from homes in Northern, California. Three basic techniques were

used fiber counting, optical microscopy, and scanning electric microscopy (SEM)

C.1 Optical Microscopy

Several pictures were taken using an optical microscope. Although depth-of-field

issues and resolution issues prevented strong quantitative results, the images showed a

mixture of animal and human hair, textile fibers, and other spherical supermicron

particles. An example of an image from an optical microscope is shown in Figure C.1.

Figure C.1: Optical Microscopy on Coil 1. Figure is approximately 150 µm in width.

197

C.2 SEM Microscopy

An example of an SEM image appears in Figure C.2. It suggests similar results

as does optical microscopy. The larger depth of field of an SEM also suggests that fibers

capture additional particles once they deposit.

50 µm

Figure C.2: SEM image from Coil 2. Figure is approximately 200 µm in width.

C.3 Fiber Counting

Ten dust fibers were selected at random from a 4 cm2 area on each coil from each

coil. Their widths were measured (with optical microscopy)and their lengths were

measured with a ruler. Care was taken to not break fibers, but because of the mat of

material that had developed on Coil 1, some of the fibers might actually be pieces of

larger fibers. The results appear in Table C.1.

198

Table C.1: Fiber diameter and lengths from two residential coils.

Diameter (µm)

Length (mm)

Notes

Coil 1

1-1 2 0.5

1-2 5 2

1-3 10 5

1-4 20 1.5 agglomeration of ~10um particles on it

1-5 3 40 Blue

1-6 3 1

1-7 6 6 Red carpet?

1-8 50 1 Very irregular

1-9 15 1.5

1-10 40 1

Average 15 6

Coil 2

2-1 70 10

2-2 3 3

2-3 80 0.5 lots of smaller particles (5-10 µm) on it

2-4 8 2

2-5 6 1

2-6 6 4

2-7 20 3

2-8 2 6 blue?

2-9 50 0.5

2-10 30 1

Average 28 3

199

APPENDIX D: INDOOR PARTICLE NUMBER CONCENTRATION DISTRIBUTION FUNCTIONS

This figures in this Appendix depict the indoor particle number concentration

distributions used to calculate nm,in in Chapter 5. The analysis techniques and inputs used

to determine these concentrations are detailed in Chapter 5. Figures D.1 and D.2 are for

urban locations and Figures D.3 and D.4 are for rural locations. Figures D.1 and D.3 are

for submicron particle sizes and figures D.2 and D.4 are for supermicron particle sizes.

The data used to generate these plots do not include dust fiber concentrations.

Figure D.1: Urban submicron indoor air particle number concentration distributions.

CYCLING OPERATION

CONTINUOUS OPERATION

CL

EA

N

DIR

TY

Particle Diameter, dp (µm)0.01 0.1 1

n° N (l

og d

p) (c

m-3

)

0

2000

4000

6000ContinuousOperation


n° N (l

og d

p) (c

m-3

)

0

20000

40000

60000



n° N (l

og d

p) (c

m-3

)

0

20000

40000

60000

80000DirtyCyclingOperation


n° N (l

og d

p) (c

m-3

)

0

20000

40000

60000

80000DirtyContinuousOperation


n° N (l

og d

p) (c

m-3

)

0

20000

40000

60000

80000

CyclingOperation

MERV 2MERV 6MERV 12

200

Figure D.2: Urban supermicron particle indoor air number concentration distributions.

CYCLING OPERATION CONTINUOUS OPERATION

CL

EA

N

DIR

TY

Particle Diameter, dp (µm)1 10 100

n° N (l

og d

p) (c

m-3

)

0.00

0.25

0.50

0.75

1.00MERV 2MERV 6MERV 12

CyclingOperation


n° N (l

og d

p) (c

m-3

)

0.00

0.25

0.50

0.75

1.00DirtyCyclingOperation


n° N (l

og d

p) (c

m-3

)

0.00

0.25

0.50

0.75

1.00ContinuousOperation


n° N (l

og d

p) (c

m-3

)

0.00

0.25

0.50

0.75

1.00DirtyContinuousOperation

201

Figure D.3: Rural submicron indoor air particle number concentration distributions.

CYCLING OPERATION

CONTINUOUS OPERATION C

LE

AN


n° N (l

og d

p) (c

m-3

)

0

2000

4000

6000MERV 2MERV 6MERV 12CyclingOperation

DIR

TY


n° N (l

og d

p) (c

m-3

)

0

2000

4000

6000DirtyCyclingOperation


n° N (l

og d

p) (c

m-3

)

0

2000

4000

6000DirtyContinuousOperation


n° N (l

og d

p) (c

m-3

)

0

2000

4000


202

Figure D.4: Rural supermicron particle indoor air number concentration distributions.

CYCLING OPERATION

CONTINUOUS OPERATION C

LE

AN


n° N (l

og d

p) (c

m-3

)

0.00

0.25

0.50

0.75

1.00

CyclingOperation

MERV 2MERV 6MERV 12

DIR

TY


n° N (l

og d

p) (c

m-3

)

0

2000

4000



n° N (l

og d

p) (c

m-3

)

0.00

0.25

0.50

0.75

1.00DirtyCyclingOperation


n° N (l

og d

p) (c

m-3

)

0.00

0.25

0.50

0.75

1.00ContinuousOperation


n° N (l

og d

p) (c

m-3

)

0.00

0.25

0.50

0.75

1.00

DirtyContinuousOperation

to my mother, father, and sister - camfil · particulate fouling of hvac heat exchangers by jeffrey...

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