cfd simulation of flow heat and mass transfer

Chapter 6: CFD Simulation of Flow, Heat and Mass Transfer �

92

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6.1 Introduction

A one dimensional mathematical model was developed (chapter 5) for predicting heat

exchanger performance. However, the shortcoming of this model is that it cannot model

complicated changes in the heat exchanger design parameters such as changing the

number of flow ribs. In addition, the mathematical model does not provide the flow,

temperature and moisture distribution in the heat exchanger. To provide detailed

information on both sensible and latent characteristics, a detailed model of the heat and

mass transfer distribution in the heat exchanger is needed.

To obtain the detailed information on the temperature, flow and moisture distribution in

the heat exchanger, Computational Fluid Dynamics (CFD) simulation is used.

Computational modelling has advantages over experimental techniques in the

investigation of flow, temperature and moisture distribution in the heat exchanger where

the introduction of instrumentation into the flow paths would influence the flow structure

and the heat and moisture transfer behaviour. With numerical simulation, it is possible to

obtain information on temperature, velocity, moisture and flow rate that sometimes

cannot be measured using conventional instrumentation. The effect of various parameters

on the heat and moisture transfer and fluid flow can be investigated in a parametric study

once a simulation model has been developed and validated against experimental data.


93

In this study, a computational fluid dynamics package, FLUENT, is used to simulate the

heat and moisture transfer in the membrane heat exchanger.

The literature review in chapter 2 shows that previous researchers have developed CFD

models for simple geometry heat exchangers such as square and rectangular shapes.

However, it is difficult for these codes to model more complicated heat exchanger

geometries. Therefore, to perform such modelling, this chapter is focused on the use of a

commercial Computational Fluid Dynamics (CFD) model which is able to model more

complicated heat exchanger geometry similar to the Z shape flow configuration heat

exchanger used in this research.

In this chapter the CFD modelling of a Z type flow enthalpy heat exchanger is presented

and the performance of the heat exchanger is determined numerically. The experimental

results obtained from the heat exchanger experimental test rig (chapter 4) were used as

benchmark cases to validate the CFD simulation results. The CFD package (FLUENT) is

also used to model Niu and Zhang’s (2001) square shaped membrane heat exchanger and

the results were validated against Niu’s and Zhang’s (2001) published results.

6.2 Computational fluid dynamics

Computational Fluid Dynamics (CFD) is the analysis of systems involving fluid flow,

heat transfer and associated phenomena such as chemical reactions, by means of

computer-based simulation. CFD is a powerful technique and can be used in a wide range

of applications, both industrial and non-industrial.

Computer based simulations work out the consequences of a mathematical model, rather

than those of an actual physical model. The mathematical models consist of a set of

differential equations. Analytical solutions for the equations governing many phenomena

of practical interest are seldom possible. Computer based simulations can offer an


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alternative solution of a problem in place of oversimplified analytic solution of the

problem.

The physical aspects of fluid flow are governed by the three fundamental principles: mass

conservation, momentum conservation and energy conservation. These equations are

usually so complicated that an analytic solution is unavailable and it is necessary to seek

a computational solution. Thus, CFD is the art of replacing the integral or the partial

derivatives in these equations with discretised algebraic forms, which in turn are solved

to obtain solutions for the flow field at discrete points in time and/or space (Anderson

1995). Currently, most of the commercial CFD codes such as FLUENT are structured

around numerical algorithms that can deal with fluid flow and heat transfer problems. A

common feature among all these codes is the existence of three main stages: a pre-

processor, a solver and a postprocessor. The process of determining practical information

about problems involving fluid motion can be presented schematically in more detail in

Fig 6.1.


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Fig 6.1 Overview of computational fluid dynamics (Fletcher, 1997)


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6.3 Pre-processor

At the pre-processor stage, most of the known data about the problem under investigation

is entered into the CFD code. The steps involved in this stage are presented schematically

in Fig 6.2. The main goal of the pre-processor stage is the transformation of a flow

problem into a form suitable for use by the solver. The solution to a flow problem is

defined at the node inside each cell. Therefore, the number of cells in the grid has a major

effect on the accuracy of a CFD solution. In general, the larger the number of cells the

more accurate is the solution. However, increasing accuracy comes at high computational

cost. Therefore, a compromise needs to be achieved between the number of cells and the

required accuracy of the solution.

Fig 6.2 Steps involved at the pre-processor stage for modelling heat transfer between two flows


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6.4 Solver

The main two stages executed by the solver are discretisation and solution of the Algebric

equations. The two stages are represented schematically in Fig 6.3. Discretisation is

concerned with the conversion of the continuous partial differential equations and

boundary conditions into a discrete system of algebraic equations. There are three distinct

streams of numerical solution techniques: finite difference, finite element and spectral

methods. Finite volume method is another numerical technique that is widely used in

commercial CFD codes such as FLUENT. The main difference between these approaches

is the way in which the flow variables are approximated with the discretisation processes.

The finite volume numerical algorithm consists of the following steps (Versteeg and

Malalasekera, 1999):

• Formal integration of the governing equations of fluid flow over all cells of the

computational domain.

• Substitution of a variety of finite difference type approximations for the terms in the

integrated equations which will convert the integral equations into a system of algebraic

equations.

• Solution of the algebraic equations by an iterative method.

Fig 6.3 Steps involved at the solver stage


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The second stage of the solution process requires an equation solver to provide the

solution of the system of algebraic equations. Systems of algebraic equations typically

arise in solving steady flow problems where the implicit technique is commonly used.

The implicit technique implies the existence of mutual dependence between two points;

that we cannot solve one point without knowing the other one.

6.5 Post-processor

The last stage in the CFD process is the post-processor stage where the output of a

numerical simulation is visualised using external or built-in visualisation programs. In

these programs, the domain geometry and the grid can be displayed, as can the field’s

velocity vectors and pressure contours.

6.6 Governing equation

The fundamental equations of fluid motion are based on three conservation laws: mass,

momentum and energy. Additional equations will also be required if, for example, a fluid

is composed of various chemical species with mass diffusion. The derivation of the

governing equations, which is detailed in Appendix D, is based on the assumption that all

dependent variables of interest obey generalised conservation principles. If the dependent

variable is denoted by �, the general differential equation is

( )+ . ( ) . ( )V S

t φ φ

ρφρφ φ

∂∇ = ∇ Γ ∇ +

∂ (6.1)

where $ is the density, V is the velocity vector, (φ = u, v, w, T, k or �), %� is the diffusion

coefficient and S� is the source term. The four terms in the general differential equation

are the unsteady term (first term) which represent the rate of increase of φ of the fluid

element, the convection term (second term) expresses the net rate of flow of φ out of

fluid element, the diffusion term (third term) represents the rate of increase of φ due to


99

diffusion and the source term (forth term) articulate for the rate of increase of φ due to a

source in the element.

The incompressible steady moist air flow equation is represented as

. ( ) . ( )Vmoist air Sφ φρ φ φ∇ = ∇ Γ ∇ + (6.2)

Where �moist air represent moist air density

6.7 Boundary conditions

In order to obtain a unique solution of the governing equations, a set of supplementary

conditions must be provided to determine the arbitrary functions that result from the

integration of the governing equations. The supplementary conditions are classified as

boundary or initial conditions. A boundary condition is a requirement that the dependent

variable or its derivative must satisfy on the boundary of the domain of a problem.

The various boundary conditions implemented in the current study are those used by the

general-purpose CFD code, FLUENT (2003). Fig 6.2 shows a simplified view of the

different boundaries in use. The following sections will detail the nature of each type and

usage.

6.7.1 Velocity inlet boundary condition

Throughout the current study velocity inlet boundary condition is used where, the

distribution of all flow variables needs to be specified at the inlet boundary. The inputs

into this boundary are the velocity magnitude and direction and the other scalar

properties.


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6.7.2 Outflow boundary condition

Outflow boundary condition is used to model the exit flow where the details of the flow

velocity and pressure are not known prior to a solution of the flow problem. Defining any

conditions at outflow boundaries is not needed in this boundary condition.

6.7.3 Wall boundary condition

A wall boundary condition is used to bound both the fluid and solid regions. The no slip

condition (fluid velocity equal to zero) has been enforced at this boundary.

6.7.4 Symmetry boundary condition

Symmetry boundary conditions are used when the physical geometry of interest, and the

expected pattern of the flow/thermal solution, has mirrored symmetry. It is not necessary

to define boundary conditions at symmetry boundaries. Symmetry boundaries are used to

reduce the extent of the computational model to a symmetric subsection of the overall

physical system.

FLUENT assumes a zero flux of all quantities across a symmetry boundary. There is no

convective flux across a symmetry plane, the normal velocity component at the symmetry

plane is thus zero. There is no diffusion flux across a symmetry plane, the normal

gradients of all flow variables are thus zero at the symmetry plane.


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6.8 CFD modelling of the membrane heat exchanger

In order to model heat and moisture transfer in a Z type flow configuration, the

commercial CFD package (FLUENT) was adopted to obtain the temperature and

moisture distribution in the heat exchanger.

To model the heat exchanger, one flow passage from the hot stream and another flow

passage from the adjacent cold stream passage were used in the CFD model with half of

each flow passage volume modelled on each side of the paper surface. Hence symmetry

boundary conditions are used as shown in Fig 6.4.

��

To study the heat exchanger performance, flow, heat and moisture distribution in the heat

exchanger flow passages have to be investigated. However, available CFD packages

suffer from limitations when it comes to modelling moisture diffusion across a porous

paper similar to the heat exchanger being investigated. The only available porous

boundary option in FLUENT is the porous jump boundary which models a thin

membrane. The porous jump boundary condition considers the flow of air through the

porous surface based on solving the Darcy equation (FLUENT 2003).

This boundary condition does not model the mass transfer phenomena occurring due to

the vapour pressure gradient across the enthalpy heat exchanger, which is the reason

Fig 6.4 Cross section of the heat exchanger flow passage


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behind the moisture transfer from the hot and humid stream to the cold and less humid

stream in the heat exchanger. As a consequence a new method of handling the boundary

condition is needed to describe the nature of moisture transfer from the hot and humid

stream to the cold and less humid stream in order to obtain the air moisture distribution in

the heat exchanger passages.

In this research, two methods were adopted to model the moisture transfer and they are as

follows:

6.8.1 Effectiveness ratio method

To overcome the limitation in moisture transfer modelling, the porous paper is modelled

as a solid thin wall. However, the wall boundary will only allow heat to be transferred.

Moisture transfer is modelled based on introducing a non-dimensional ratio that relates

the air temperature to the air moisture content. This ratio is the sensible-latent

effectiveness ratio (ER) and is expressed as

( ) ( )

( ) ( )p hi h fg hi Cis

L p hi Ci fg hi h

mC T T mhER

mC T T mh

ω ωε

ε ω ω

− −= = ×

− −

� �

� � (6.3)

( ) ( )

( ) ( )p C Ci fg hi Cis

L p hi Ci fg C Ci

mC T T mhER

mC T T mh

ω ωε

ε ω ω

− −= = ×

− −

� �

� � (6.4)


103

��

��&'��(��

��&'��

)��*��+�&�

��

�� )�!��!��'�&&�'

)��*��+�&�

,��'�� -� #��!��-�

*��!��"��.��'��/��'�0��'�'�!��.��

Where Th, TC, ωh and ωc represent the air temperature and moisture content at each grid

point on the membrane surface in the hot and cold streams (Fig 6.5). Fig 6.5 depicts the

process of modelling the moisture transfer of a simplified square shaped heat exchanger

with structured grid. To obtain the air moisture distribution in the hot stream, equation

(6.3) is solved, where the simplified mathematical model (chapter 5) is used to calculate

the sensible-latent effectiveness ratio, ER. The air inlet temperature and moisture content

(Thi, TCi, ωhi, and ωci) were determined by the operating conditions and the CFD code is

used to obtain Th values at each grid point on the membrane surface boundary by solving

equation (6.1), hence the air moisture content (ωh) at each grid point on the membrane

surface in the hot stream is obtained from equation 6.2. In a similar way equation 6.4 is

used in the cold stream to obtain the air moisture content (ωc) at each grid point on the

Fig 6.5 Numerical domain and boundary conditions utilising effectiveness ratio method


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membrane surface in this stream. By determining the moisture content on the membrane

surface in the hot and cold streams, the moisture will be transferred from the hot and

humid stream inlet to the membrane surface due to the air moisture content difference

between the hot air inlet stream and the membrane surface causing a decrease in air

moisture content at the heat exchanger hot stream outlet. In the cold and less humid

stream the moisture will be transferred from the membrane surface to the cold inlet

stream due to the moisture difference, where the moisture content at the membrane

surface is higher than the air moisture content at the cold stream inlet, consequently the

air moisture content increases at the heat exchanger cold stream outlet. Hence moisture

distribution in both hot and cold stream flow passages is obtained (details of the

effectiveness ratio user define function code are shown in Appendix D 7.1).

The effectiveness ratio can be used to determine the air moisture distribution profile in

the heat exchanger; however, this modelling requires using the mathematical model

detailed in chapter 5 to obtain the value of the effectiveness ratio. From the effectiveness

values obtained from the mathematical model, the effectiveness ratio for 45gsm paper at

air face velocity of 2.9m/s was found to be 1.9 and for the 60gsm paper it was 1.3. In

chapter 5, Figs 5.8 and 5.9 show the sensible effectiveness for both 45 and 60gsm paper

were same. However, the latent values for 60gsm paper were higher due to the lower

moisture transfer resistance of 60gsm Kraft paper; as a result the effectiveness ratio value

was lower for the 60gsm paper.

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105

6.8.1.1 Effectiveness ratio simulation conditions

A three-dimensional model of the heat exchanger is developed to study the velocity,

temperature and moisture distribution in the heat exchanger using Finite-volume

differencing scheme segregated solver with implicit technique to solve the algebraic

equations forming the discritisation of equation 6.1. The semi implicit method for

pressure linked equation-consistent (SIMPLEC) algorithm is employed for the

calculation of the pressure and thus the velocity field. Second order upwind discretisation

scheme is used to discritise the steady state version of equation 6.1.

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The Reynolds number in a flow passage ranges (for the 45gsm paper experimental

measurement) from 2300 to 5500 for typical application conditions. Therefore, the

turbulent k-� renormalisation group (k-� RNG) turbulence model is utilised.

The velocity inlet boundary condition is used to define the velocity of the moist air inlet

to each flow path in the heat exchanger. Outflow boundary condition is used for the heat

exchanger outlets to model the flow exits the heat exchanger.

6.8.1.2 Validation of CFD results using effectiveness ratio method

Although CFD is an effective tool, and has been used in many applications for many

years, code validation is always necessary. In some fields, the use of CFD has become

common practice and CFD has been tested and trusted by engineers. Nevertheless, in

most areas, CFD still needs to be validated.

The method of measuring the accuracy of the representation is achieved by comparing

CFD simulations with experimental data and previous research performed. Experimental

data can be obtained from measurements and the accuracy of the measurement must be

high enough to give an accurate representation of the modelled system. In addition, the

experimental data can be obtained from the published work of other researchers. Code


106

validation, in the current study, relies on both the published work found in the literature

and experimental measurements performed during this project.

To validate the code against previous research results, the heat exchanger investigated by

Niu and Zhang (2001), presented in the literature review (chapter 2), is modelled using

FLUENT correlated with the effectiveness ratio method. As mentioned in chapter 2, Niu

and Zhang modelled a squared shaped heat exchanger (Fig 6.6) using in-house code due

to the limitations of available commercial CFD packages when it comes to modelling

moisture diffusion across a porous boundary.

As a result Niu and Zhang developed their in-house CFD code to study the temperature

and moisture distribution in simple heat exchanger geometry such as square and

rectangular shapes.

The square heat exchanger modelled by Niu and Zhang has a total heat and moisture

transfer area of 0.25m2 and consists of 15 square shaped inlet flow path frames on each

stream. The membrane thickness is 20m and the flow path width is 5mm. This heat

exchanger is modelled using the effectiveness ratio method. Fig 6.7 shows that the

effectiveness obtained using the effectiveness ratio method is in agreement with Niu and

Zhang’s effectiveness results.

Fig 6.6 Niu and Zhang square shaped membrane heat exchanger (2001)


107

Further, the temperature and moisture contours in the hot and cold streams are in

reasonable agreement with Niu’s and Zhang’s contours (Fig 6.8). However, there were

minor qualitative differences between the present CFD model temperature and moisture

contours and Niu’s and Zhang’s contours, the reason for the differences maybe explained

as follows:

The finite differencing numerical solution technique used by Niu and Zhang, is less

accurate than the finite volume method used in this research (Versteeg and Malalasekera,

1999).

Another reason for the differences could be the discretisation scheme used, as Niu and

Zhang used the upwind scheme at the exchanger air streams and central-difference

scheme at the membrane, whereas in the present research a second order upwind scheme

is used. It is well known that the central-difference scheme is not as accurate as the

second order upwind and may cause the solution to be unstable (Versteeg and

Malalasekera, 1999).

It should also be noted that Niu and Zhang did not present mesh sensitivity analysis and

therefore it is not possible to ascertain that their solution is mesh independent.

Fig 6.7 Comparison of Niu and Zhang (2001) effectiveness and CFD effectiveness ratio method results


108

The accuracy of the flow, temperature and moisture fields obtained in this research is

further examined by a mesh sensitivity analysis presented in the next section.

Fig 6.8 Comparison of CFD solutions from effectiveness ratio method and Niu and Zhang (2001) CFD solutions (temperature in Celsius and moisture content in kg/kg)

Modelled heat exchanger mesh


109

6.8.1.3 Mesh sensitivity study

CFD solutions to fluid dynamics and heat transfer problems always contain errors due to

the evaluation of continuous problems using discrete analysis. In general, these errors can

be minimised by discretising the flow domain into a large number of mesh points (cells).

In practice, there is a trade off between the accuracy of the solution and the computing

time; hence an optimum number of grid points have to be used for the simulation domain.

In this study mesh refinement investigation has been carried out to optimise the number

of cells used. It is apparent that the more cells used in the model the more time consumed

to complete the simulation. Different numbers of cells were tested to optimise the number

of cells to be used in the final modelling of the heat exchanger. Fig 6.9 shows that when

200,000 cells were used the effectiveness was higher than the measured effectiveness.

However, by increasing the number of cells to 250,000, the predicted CFD effectiveness

was the same as the measured effectiveness. By increasing the number of cells to 300,000

and 350,000, the results show no difference from the 250,000 cells model. Hence,

250,000 cells was selected to be the optimum number of cells that can be used to obtain

reliable and accurate results and consume less time than other models.

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

150,000 200,000 250,000 300,000 350,000 400,000Number of Cells

Eff

ecti

ven

ess

Sensible effectiveness

Measured Sensible effectiveness

Latent effectiveness

Measured Latent effectiveness

Fig 6.9 Mesh sensitivity study at air face velocity of 2.93m/s


110

6.8.1.4 Effectiveness ratio method validation against measurements

The Z type heat exchanger used in this study is modelled to validate the numerical

simulation results against the experimental results. Fig 6.10 shows that the numerical

CFD predictions of sensible, latent and total effectiveness are in reasonable agreement

with the measured results. Therefore, this model can be used to study the detailed flow,

temperature and moisture content distribution in the heat exchanger.

0

0.1

0.2

0.3

0.4

0.5

0.6

1 1.5 2 2.5 3 3.5

Face velocity (m/s)

Eff

ecti

ven

ess

Measured performance

CFD model

Latent

Sensible

Total

6.63m/s 5.33m/s

3.33m/s

7.3m/s

To study the temperature and moisture distribution in 45gsm paper heat exchanger, the

hot and humid stream temperature distribution contours (Fig 6.11) show when the hot and

moist air enters the heat exchanger a flow circulation zone occurs at the corner of the

flow path ribs (details of flow recirculation is shown in Fig 6.12).

Fig 6.10 CFD and experimental effectiveness results (figures shown represent air velocity at the inlet of heat exchanger flow channels)


111

At these circulation zones the temperature has decreased and this is due to low velocity

and flow circulation occurring in that zone (Fig 6.11, circles represents low velocity and

circulation zone). This circulation is more noticeable and has more effect in flow path 1

where a sharp right angle change in the flow direction towards the outlet has occurred

(Fig 6.11, dotted rectangles at flow path 1 and 6). Fig 6.11 also illustrates that the highest

reduction in temperature occurred along flow path 1 by 4.15K. The reduction of

temperature along paths 2, 3, 4, 5 and 6 was 4, 3.65, 3.3, 3 and 2.78K respectively.

The high decrease in temperature occurred at flow path 1 is attributed to the location of

this flow path, when the air flow enters flow path 1 the flow arrangement at the entrance

is counter flow. As the flow changes its direction (vertical direction) the flow

arrangement at that zone is cross flow and it is located adjacent to the cold air inlet at the

adjacent frame, as a result the temperature gradient between the hot and cold streams in

that zone is the highest and the amount of heat transfer is higher. Therefore the highest

reduction in temperature occurs along flow path 1. At flow path 2 the location of this path

is the second nearest to the cold air inlet at the adjacent frame, therefore the decrease in

temperature was larger than flow profiles 3, 4, 5 and 6 and less than flow path 1. It can

also be seen that the decrease in temperature at the circulation zones located nearest to

the cold inlet stream at the adjacent frame is more noticeable than in other flow

circulation zones.


112

Fig 6.11 Temperature contours in the hot and humid stream of 45gsm paper heat exchanger at air face velocity of 2.93 m/s (temperature in Kelvin)

Z shaped heat exchanger mesh


113

Fig 6.12 Velocity vectors showing recirculation zones in the hot and humid stream of 45gsm paper heat exchanger at air

face velocity of 2.93 m/s


114

Similar to the hot stream, at the cold stream, the increase in temperature is higher for flow

path 1 as the temperature increased by 4.2K. In streams 2, 3, 4, 5 and 6 the increase in

temperature recorded was 4, 3.7, 3.4, 3and 2.9K respectively (Fig 6.13)

Fig 6.13 Temperature contours in the cold stream of 45gsm paper heat exchanger at air face velocity of 2.93 m/s (temperature in Kelvin and

moisture content in kg/kg)


115

The location of the flow paths has a similar effect on moisture transfer. The hot flow

moisture distribution contours for 45gsm paper (Fig 6.14) show that when the air passes

the last bend a flow circulation zone occurs at the corner of the flow paths ribs (Fig 6.14

circles represent low velocity and circulation zone nearest to the adjacent cold and less

humid stream). Here, the moisture content recorded its lowest values. This is attributed to

the low velocity and flow circulation occurring in that zone. Similar to the temperature

contour, the flow circulation is more noticeable in flow path 1 where a sharp right angle

change in the flow direction towards the outlet has occurred (Fig 6.14, dotted rectangle).

The moisture distribution contour indicates that the location of flow paths have a

significant effect on the moisture distribution in the heat exchanger. The highest

reduction in the air moisture content occurred in flow path 1 as it is located adjacent to

the cold and less humid stream inlet, where the moisture content gradient is the highest;

hence the highest decrease in the moisture content recorded is 0.000573 kg/kg. The

reduction in the air moisture content in stream 2, 3, 4, 5 and 6 was 0.000553, 0.000503,

0.000453, 0.000403 and 0.000353 kg/kg respectively.

�� !

�� !

�� !

�� !

�� !

�� !

�� !

��!��"

��!��#

Fig 6.14 moisture content contour in the hot and humid stream of 45gsm paper heat exchanger at air face velocity of 2.93 m/s

(moisture content in kg/kg)


116

In the cold and less humid stream the increase in the moisture transfer follows the same

trend as the heat transfer. As shown in Fig 6.15 the highest increase in moisture transfer

recorded was in flow path 1 where 0.00058kg/kg increase is recorded and is attributed to

the location of this flow path which is nearest to the hot and humid air inlet at the

adjacent stream.

� ��

��$��

��%��

� ��

� �� !��"��

#$##%&%

#$##'#$##'#"#$##'#&#$##'�!#$##'�(

#$##%%

��

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6.8.2 Lewis number method

As mentioned previously, the shortcoming in using the effectiveness ratio method is that

it relies on the mathematical model to obtain the effectiveness ratio value. Therefore an

alternative method is developed which can predict the heat exchanger performance if the

design parameters are changed without the need of using the mathematical model

effectiveness approach.

The new method of modelling the moisture transfer in the heat exchanger is to utilise the

Lewis number to obtain the moisture boundary conditions at the paper heat exchanger

surface. The Lewis number is represented as

Fig 6.15 moisture content contour in the cold and less humid stream of 45gsm paper heat exchanger at air face velocity of 2.93 m/s

(moisture content in kg/kg)


117

�

Air thermal conductivity (�air) and water in air diffusivity (Dwater-air) were obtained from

air property tables and plotted versus temperature. Plotting this data versus temperature, a

line of best fit is found, as illustrated in Fig 6.16. The equation for these lines of best fit is

then used in the calculation of air thermal conductivity and water in air diffusivity for

different values of temperature by incorporating them in the code, where the temperature

at the paper boundary is obtained from FLUENT by solving equation 6.1.

K = 7E-05T + 0.0042

0.024

0.0245

0.025

0.0255

0.026

0.0265

0.027

0.0275

0.028

275 280 285 290 295 300 305 310 315 320 325

Temperature (K)

Air

th

erm

al c

on

duct

ivit

y K

(kW

/m.C

) D = 2E-07T - 3E-05

1.50E-05

1.70E-05

1.90E-05

2.10E-05

2.30E-05

2.50E-05

2.70E-05

2.90E-05

275 280 285 290 295 300 305 310 315

Temperature (K)

Diff

usi

vity

of w

ater

in a

ir D

(m^2

/s)

��

To simplify the modelling, it was assumed that Cp moist air value is 1.0273 kJ/kg K. For

Lewis number of 0.81, moist air density at the paper surface boundary in the hot and

moist stream is obtained. The vapour density in the air is represented as

�

The dry air density was obtained from air property tables and plotted versus temperature.

Similar to the air thermal conductivity, dry air density was obtained.

air

p moist air water air moist air

LeC D

λ

ρ−

= (6.5)

vapour moist air dry airρ ρ ρ= − (6.6)

Fig 6.16 Air thermal conductivity and water diffusivity in air versus temperature


118

��

)�*��

��*

�+,�-./

0

��

The dry air density is a function of air temperature at the paper boundary in the hot air

stream. FLUENT provides the air temperature at the paper boundary, thus the density of

the dry air is obtained from the equation for the line of best fit (Fig 6.17)

The air moisture content per kilogram of moist air at the paper surface boundary is

represented as

�

Substituting $vap from equation 6.6 and $moist air obtained from Lewis correlation into

equation 6.7, the moisture content per kilogram of moist air at the paper surface boundary

in the hot stream is obtained (details of the Lewis number user define function code are

shown in Appendix D 7.2).

Fig 6.18 depicts the moisture transfer method using Lewis correlation in a simple square

shaped geometry heat exchanger. As can be seen in the cold stream, the amount of

moisture at the paper surface boundary is obtained from the moist air mass flow rate at

each cell in the CFD model on the paper surface boundary, and is calculated as follows:

vapourhot stream

moist air

ρω

ρ= (6.7)

Fig 6.17 Dry air density versus temperature


119

��

The amount of moisture transferred from the paper surface boundary in the hot stream to

the paper boundary at the cold stream is represented as

��

The air moisture content at the paper boundary in the cold stream is represented as

�

where moist airm� represent the moist air mass flow rate through the cell at the cold stream

paper boundary surface in the CFD model.

Substituting equation 6.9 into equation 6.8 and rearranging gives

tan

( )paper hot stream paper cold streammoisture

moisture resis ce

mR

ω ω−=� (6.8)

moistur cell moist air paper cold streamm m ω=� � (6.9)

Fig 6.18 Moisture transfer simulation using Lewis correlation method


120

��

Hence the air moisture content at the paper surface boundary in the cold stream is

obtained.

Using the same simulation conditions in the effectiveness ratio method, the Lewis

correlation method is used to model Niu and Zhang’s (2001) membrane heat exchanger.

This heat exchanger has been previously modelled using the effectiveness ratio method to

obtain the moisture distribution in the heat exchanger and it will be used as a benchmark

to validate the Lewis correlation method. For Lewis number of 0.81 the temperature and

moisture distribution contours in the heat exchanger hot and cold stream shows

reasonable agreement with Niu and Zhang’s contours (Fig 6.19).

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tan

paper hot streampaper cold stream

cell moist air moisture resis cem R

ωω =

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121

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��Fig 6.19 Comparison of CFD model with Lewis correlation and Niu and Zhang

(2001) CFD model (temperature in Celsius and moisture content in kg/kg)


122

After validating the Lewis correlation method against Niu and Zhang’s results, this

method is also used to model the existing Z type heat exchanger that utilises 45gsm paper

in order to compare the results with the effectiveness ratio method.

For Lewis number of 0.81, Fig 6.20 shows that the moisture contours were similar for

both models. The effectiveness ratio method contour shows an overall decrease in the

moisture content in the hot and humid stream of 0.000474 kg/kg and Lewis correlation

contour recorded a decrease of 0.00048.

�� Fig 6.20 Moisture transfer contours using Lewis correlation and

effectiveness ratio methods (temperature in Kelvin and moisture content in kg/kg)


123

Fig 6.21 shows that the effectiveness values determined when the Lewis correlation

method is used are in reasonable agreement with the measured effectiveness values.

Since this method has been validated with experimental and previous researchers work, it

can now be used to model different heat exchanger configurations and to study

temperature and moisture distribution throughout the heat exchanger.

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Fig 6.21 CFD effectiveness results using Lewis correlation and experimental effectiveness results

Chapter 7: CFD Simulation Results �

124

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7.1 Introduction

In chapter 6, effectiveness ratio and Lewis correlation simulation methods were

developed to model moisture transfer in the membrane heat exchanger using the

FLUENT CFD package. These methods were validated against experimental

measurements and previous research results. In this chapter the design parameters of the

heat exchanger are varied and the above methods are used to predict the temperature,

flow and moisture distribution in the modified heat exchangers.

CFD simulation using the effectiveness ratio method is used to model the effect of

changing the heat exchanger grade of paper on the heat exchanger performance. The

Lewis correlation method is used to predict temperature, flow, and moisture distribution

when the number of flow divider ribs in the heat exchanger is varied. This method is also

used to model different flow configurations such as L shaped heat exchangers and predict

their performance.

Temperature, flow and moisture distribution contours of the modified heat exchangers are

presented in this chapter together with the heat exchanger predicted effectiveness.

��


125

7.2 Effect of changing the grade of paper

When 60gsm paper is used as the heat and moisture transfer surface, Fig 4.11 in chapter 4

shows the sensible effectiveness values for both 45 and 60gsm papers were the same

under the same operating conditions. Hence, the heat exchanger temperature distribution

contours for both 45 and 60gsm paper are similar. However, the moisture distribution

contours shown in Fig 7.1 show a significant difference with higher moisture transfer

recorded when 60gsm paper is used due to the considerable reduction of paper moisture

transfer resistance (Rpaper).

Similar to the 45gsm paper heat exchanger, the highest decrease in the moisture content

occurred in flow path 1 as the moisture content decreased by 0.0009 kg/kg. The reduction

in the air moisture content at flow paths 2, 3, 4, 5 and 6 was 0.00084, 0.00077, 0.00069

0.00062, and 0.00055 kg/kg respectively.

At the cold and less humid stream, analogous to the hot stream the highest increase in the

moisture content was in flow path 1, where 0.00088kg/kg increase is recorded. The

increase in flow path 2, 3, and 4 was 0.00082, 0.00075 and 0.00067kg/kg respectively,

and the increase in flow path 5 and 6 were 0.0006 and 0.00054kg/kg respectively.

In general the over all moisture transfer analysis of the hot and cold contours shows a

higher moisture transfer rate occurred when 60gsm paper was used, resulting in higher

latent effectiveness values. This is due to the lower moisture transfer resistance of 60gsm

paper in comparison with 45gsm paper.

��


126

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Fig 7.1 Moisture content contour in the hot and cold streams of 60gsm paper heat exchanger at air face velocity 2.93 m/s (moisture content in kg/kg)


127

7.3 Effect of changing the number of flow divider ribs

As previously mentioned, the existing heat exchanger consists of five flow divider ribs.

The Lewis correlation method of modelling the moisture transfer is used to study the

effect of varying the number of ribs on the heat exchanger temperature and moisture

distribution and effectiveness. For Lewis number of 0.81 at air face velocity of 2.93m/s,

the FLUENT model incorporating the Lewis correlation is used to model the heat

exchanger without flow divider ribs, with one rib, two ribs, three ribs, five ribs (existing

heat exchanger) and eleven ribs.

Fig 7.2 shows the temperature, moisture and velocity distribution contours of the heat

exchanger without the flow dividers (ribs) at duct face velocity of 2.93 m/s. The hot and

humid stream contour shows that low velocity zones have been generated due to the flow

recirculation in zones A and B due to the sharp corners. The temperature and moisture

content recorded its lowest values in zone A, as the flow remains circulating at zone A

which is located adjacent to the cold air inlet where the gradient in temperature and

moisture content is high. As a result the temperature and moisture content recoded in

zone A is lower than in zone B.

��


128

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Similarly at the cold and less humid stream, the air temperature and moisture content at

zone A recorded its highest values in comparison with zone B, as the air circulating at

zone A is adjacent to the air hot inlet stream where the gradient in air temperature and

moisture content is high (Fig 7.3).

Fig 7.2 Hot and humid stream temperature, moisture and velocity distribution contours for heat exchanger without ribs (temperature in Kelvin moisture

content in kg/kg and velocity in m/s)

Recirculation zone


129

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When the heat exchanger is modelled with a single rib, the air circulation is divided into

three zones (zones A, B and C). As can be seen in Figs 7.4 and 7.5, the recirculation flow

zones at A and B became smaller in comparison with the heat exchanger with no ribs and

the flow distribution became more uniform. Nevertheless, the lowest temperature and

moisture content recorded at zone A and the temperature and moisture content at zone C

were less than zone B, which is attributed to the location of the circulation zone, as zone

Fig 7.3 Cold and less humid stream temperature, moisture and velocity distribution contours for heat exchanger without ribs (temperature in

Kelvin, moisture content in kg/kg and velocity in m/s)


130

A is located adjacent to the cold air stream inlet, and zone C located nearer to the cold

inlet stream�than zone B, therefore the temperature and moisture content recorded at zone

A were lower than zone B and C.

It can also be seen that the decease in air temperature and moisture content in flow path 1

was higher than flow path 2, where 3.54K and 0.00051 kg/kg decrease in temperature and

moisture content is recorded in flow path 1, in comparison with 2.7K and 0.0004 kg/kg

decrease recorded in temperature and moisture content in flow path 2, which is attributed

to the location of flow path 1, as the gradient in temperature and moisture content is high,

thereby the highest decrease is temperature and moisture content has occurred in flow

path 1.

��

Fig 7.4 Hot and humid stream temperature, moisture and velocity distribution contours for single rib heat exchanger (temperature in

Kelvin moisture content in kg/kg and velocity in m/s)


131

Colored By Velocity Magnitude (m/s)FLUENT 6.1 (3d, segregated, rngke)

Jan 13, 2008

Z

Y

X

Fig 7.5 Hot and humid stream velocity distribution vectors showing recirculation zones for single rib heat exchanger (velocity in m/s)


132

The cold stream follows the same trend as in the hot and humid stream. Fig 7.6 shows the

highest temperature and moisture content recorded at zone A which is located adjacent to

the hot and humid steam inlet, hence the air circulating at zone A was heated and the

moisture content has increased. Whereas, the air temperature and moisture content at

zone C were higher than zone B due to the location of zone C nearer to the hot inlet

stream than zones B. Similar to the hot stream, the highest increase in temperature and

moisture content is recorded in flow path 1 in the cold stream, where 3.55K and 0.00048

kg/kg increase in temperature and moisture content is recorded which is higher than the

increase in temperature and moisture content at flow path 2.

��

Fig 7.6 Cold and less humid stream temperature, moisture and velocity distribution contours for single rib heat exchanger (temperature in Kelvin,

moisture content in kg/kg and velocity in m/s)


133

By increasing the number of flow dividing ribs to two, Figs 7.7 and 7.8 show that the

flow, temperature and moisture content distribution became more uniform and the

recirculation zones size has decreased, especially zone A. From Fig 7.7, it can be seen

that zone A recorded the lowest temperature and moisture content in comparison with

zone B, C and D. As zone A is located nearer to the cold air inlet at the adjacent cold

stream flow path. Therefore, the temperature and moisture content is lower.

Analogous to the heat exchanger with single flow divider, the highest heat and moisture

transfer has occurred in flow path 1, as it is located nearest to the cold air inlet in the

adjacent cold stream. Where 3.73K and 0.00067 kg/kg decrease in temperature and

moisture content is recorded in flow path 1, which is 13% higher than flow path 2 and

28% higher than flow path 3. The decrease in temperature and moisture content at flow

path 1 is 6% higher than the decrease recorded in the single rib heat exchanger. This

shows as the flow becomes more uniform by increasing the number of ribs the heat and

moisture transfer will improve.


134

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Fig 7.7 Hot and humid stream temperature, moisture and velocity distribution contours for two ribs heat exchanger (temperature in



135

Fig 7.8 Hot and humid stream temperature, velocity distribution vectors showing recirculation zones for two ribs heat exchanger

(velocity in m/s)


136

The cold stream in 2 ribs heat exchanger follow the same trend as in the hot stream as

shown in Fig 7.9.

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Fig 7.9 Cold and less humid stream temperature, moisture and velocity distribution contours for two ribs heat exchanger (temperature in Kelvin,



137

Subsequent to the increase in the number of flow dividers to 2, increasing the flow

dividers ribs to 3 caused the flow, temperature and moisture distribution to be more

uniform and the flow recirculation zones became smaller in comparison with single and

double ribs heat exchangers.

Figs 7.10 and 7.11 show that the size of the circulation zone A has decreased and a

similar reduction has occurred in other flow circulation zones. Fig 7.10, also illustrates

that the reduction in temperature and moisture content were higher in flow path 1, where

3.74K and 0.00054 kg/kg decrease in the temperature and moisture content has occurred

in flow path 1 which is 7.5% higher than flow path 2, 18% higher than flow path 3, and

25.6% higher than flow 4 in the heat transfer and 13%, 24% and 38% higher than flow

paths 2, 3, and 4 respectively in the moisture transfer.

It can be seen that the temperature and moisture content difference at the flow path

outlets became less substantial than single and double rib heat exchangers indicating that

as the flow distribution became more uniform the temperature and moisture content

variation between the flow paths became less.

By comparing the amount of heat and moisture transferred at flow path 1, we can see that

the temperature has decreased by 3.54K, 3.73K, and 3.75K in single, double and 3 ribs

heat exchangers respectively. On the moisture content the decrease recoded is 0.00051

kg/kg, 0.00067 kg/kg, and 0.00077 kg/kg in single, double and 3 ribs heat exchanger

respectively. This shows that improving the uniformity in flow distribution would

improve the heat and moisture transfer.

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138

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Fig 7.10 Hot and humid stream temperature, moisture and velocity distribution contours for three ribs heat exchanger (temperature in



139

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Fig 7.11 Hot and humid stream velocity distribution vectors showing recirculation zones for three ribs heat exchanger (velocity in m/s)


140

The improvement in the flow, temperature and moisture content distribution can also be

seen in the cold stream (Fig 7.12). Where, the cold stream follows similar trend as in the

hot stream; as the circulation zones sizes has decreased and the highest increase in

temperature and moisture content recorded is at flow path 1 in comparison with flow path

2, 3 and 4.

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Fig 7.12 Cold and less humid stream temperature, moisture and velocity distribution contours for three ribs heat exchanger (temperature in



141

The study on the effect of changing the number of ribs has been extended to the existing

heat exchanger with 5 ribs (the detail analysis of the heat and moisture transfer has been

discussed in chapter 5).� �� temperature and moisture contours for both hot and cold

streams shows the highest heat and moisture transfer has occurred in flow path 1 similar

to the previous modelled heat exchangers (single, double, and 3 rib heat exchangers). The

flow, temperature and moisture distribution became more uniform and the circulation

zones became smaller (Fig 7.13).�

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Fig 7.14 shows that when the number of ribs in the heat exchanger has been increased to

11. The heat exchanger temperature and moisture contours illustrates that the

recirculation zones (red dotted circles and rectangles) became smaller and similar to the

Fig 7.13 Hot and cold streams temperature, and moisture contours for five ribs heat exchanger (existing heat exchanger, (temperature in

Kelvin and moisture content in kg/kg)


142

previous heat exchangers the lowest decrease in temperature is recorded at flow path 1.

However, the temperature and moisture variation between the flow paths 12 outlets were

smaller.

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Fig 7.15 shows that analogous to the hot stream, the 11 ribs heat exchanger cold stream

follows the same trend as in the hot stream

Fig 7.14 Hot and humid stream temperature, moisture, and velocity contours for eleven ribs heat exchanger (temperature in Kelvin,



143

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Fig 7.15 Cold and less humid stream temperature, moisture, and velocity contours for eleven ribs heat exchanger (temperature

in Kelvin, moisture content in kg/kg and velocity in m/s)


144

The effect of varying the number of ribs on the overall effectiveness is shown in Figs

7.16 and 7.17. As can be seen the effectiveness increased rapidly when one rib is used.

The sensible and latent effectiveness increased by 9% relative to the heat exchanger

without ribs. However, when the number of ribs was increased to two, both sensible and

latent effectiveness increased by about 4% relative to the single rib heat�exchanger. The

effectiveness, values increased further by approximately 7% when the number of ribs

increased to three relative to the 2 ribs heat exchanger and by 5% when 5 ribs were used.

However, the increase in the effectiveness values became marginal when an 11-rib heat

exchanger is used as the effectiveness value increased by only 0.8% relative to the 5 ribs

design.

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.55

1 1.5 2 2.5 3 3.5

Face velocity (m/s)

Eff

ective

nes

s

Sensible without ribs

Sensible 1 rib

Sensible 2 ribs

Sensible 3 ribs

Sensible 5 ribs (existing heat exchanger)

Sensible 11 ribs

�� Fig 7.16 Sensible effectiveness for 45gsm paper heat exchanger

using different number of ribs


145

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

1 1.5 2 2.5 3 3.5

Face velocity (m/s)

Eff

ecti

ven

ess

Latent without ribs

Latent 1 rib

Latent 2 ribs

Latent 3 ribs

Latent 5 ribs (existing heat exchanger)

Latent 11 ribs

��

From the contour analysis and Figs 7.16 and 7.17 for sensible and latent effectiveness we

can conclude that increasing the number of ribs will make the temperature, flow and

moisture distribution throughout the heat exchanger more uniform. The recirculation

zones will be smaller hence heat and moisture transfer have improved. However,

increasing the number of ribs from 5 to 11 has only a minor effect on effectiveness as the

flow, temperature and moisture distribution are already uniform. Therefore, no significant

improvement is noticed when the number of ribs is increased to 11.

�

7.4 Effect of using L shape flow configuration heat exchanger

The effect of changing the heat exchanger flow profile on the heat exchanger

performance is investigated for an L shape flow configuration shown in Fig 7.18 using

Lewis correlation method. As can be seen with this new flow configuration the heat and

moisture transfer area consists of 50% counter flow and 50% cross flow. Consequently it

is expected that the effectiveness would increase relative to the Z shape heat exchanger.

Fig 7.17 Latent effectiveness for 45gsm paper heat exchanger using different number of ribs


146

��

The temperature and moisture distribution contours shown in Fig 7.19 indicate that the

highest heat and moisture transfer occurred in flow path 1. Obviously it is due to the large

heat and moisture transfer area of this flow path in comparison with other flow paths. As

flow path 1 is longer than other paths (2, 3, 4, 5, and 6). In addition when the flow

changes direction from vertical flow to horizontal towards the outlet, that zone is located

adjacent to the cold air inlet in the adjacent frame and gradient in temperature and

moisture�content is highest. Hence the amount of heat and moisture transfer is higher in

comparison with other flow path. As a result the temperature and moisture content

recorded were the lowest compared with flow paths 2, 3, 4, 5, and 6.�

Fig 7.18 L shape heat exchanger


147

��

Fig 7.19 Hot and humid stream temperature, and moisture contours for L shape heat exchanger (temperature in Kelvin,

and moisture content in kg/kg)


148

Similarly, the cold and less humid contours shown in Fig 7.20 shows the highest heat and

moisture transfer recorded at flow path 1.

�

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Fig 7.20 Cold and less humid stream temperature, and moisture contours for L shape heat exchanger (temperature in Kelvin and

moisture content in kg/kg)


149

Fig 7.21 shows that the sensible and latent effectiveness are both 4% higher for the L

shaped heat exchanger than the Z shape flow heat exchanger. That is attributed to the

increase in the counter flow area in comparison with the Z shape heat exchanger.

0

0.1

0.2

0.3

0.4

0.5

0.6

1 1.5 2 2.5 3 3.5

Face velocity (m/s)

Eff

ecti

ven

ess

Sensible L shape heat exchanger

Latent Lshape heat exchanger

Latent Z shape heat exchanger

Sensible Z shape heat exchanger

��

7.5 Pressure drop

As mentioned in chapter 4, the pressure drop across the Z shape heat exchanger was

measured. FLUENT was also used to predict the pressure drop through the different heat

exchangers. Fig 7.22 shows that the CFD predicted and measured pressure drop are in

reasonable agreement. Hence the CFD code (FLUENT) is used to predict the pressure

drop that applies when the number of ribs is varied.

��

Fig 7.21 Sensible and latent effectiveness for L shape and Z shape heat exchangers


150

��

0

50

100

150

200

250

300

350

400

450

500

1 1.5 2 2.5 3 3.5

Face Velocity (m/s)

Pre

ssu

re D

rop

(P

a)

Measured pressure drop

Predicted pressure drop (CFD)

��

As can be seen in Fig 7.23 the heat exchanger with no ribs has the lowest pressure drop,

and the pressure drop increases as the number of ribs increased and the highest pressure

drop was predicted when 11 ribs are used.

��

0

50

100

150

200

250

300

350

400

450

500

1 1.5 2 2.5 3 3.5

Face velocity (m/s)

Pre

ssu

re d

rop

(P

a)

Zero rib Press DropSingle rib Press Drop2 ribs Press Drop3 ribs Press Drop5 ribs Press Drop11 ribs Press Drop

Fig 7.22 Measured and CFD predicted pressure drop through Z shape existing heat exchanger

Fig 7.23 Predicted pressure drop through Z shape heat exchanger with different number of ribs


151

�In conclusion, although increasing the number of ribs increase the heat exchanger

sensible and latent effectiveness (Figs 7.16 and 7.17); the increase in the number of ribs

results in an increase in pressure drop. Figs 7.17 and 7.18 show that increasing the

number of ribs from 5 to 11 results in only minor increase�in the effectiveness. However,

the increase in pressure drop was significant (30 Pa). The value of the increase in

effectiveness with increasing number of ribs depends on the relative cost of the heat and

moisture transfer and the cost of increasing the frames. From the results presented here it

is clear that increasing the number of ribs above 5 would result in a nil benefit.��

��

Chapter 8: Annual Energy Analysis �

152

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8.1 Introduction

The research presented in this chapter is directed at the investigation of annual

performance for an air conditioner coupled with an enthalpy heat exchanger which

supplies 100% fresh air. The combined air conditioner and enthalpy heat exchanger is

compared to a conventional air conditioning system that operates based on mixing of

fresh air with the room exhaust air.

The most accurate way to determine the performance of an air conditioner is to use a

calorimeter measurement. However, these measurements are costly and time consuming

(Morrison, 2004). Therefore, research on heat pumps is often based on computer

simulation programs based on energy and thermodynamic equations of the refrigeration

and air cycles and performing energy balance for the system. Most of the previous

research has been based on fixing the air set point conditions in order to simplify the

computer simulation (Niu and Zhang (2001), Zhang et al. (2005) and Zhang (2006)).

However, in real air conditioning cycles the air conditions exiting the evaporator and

condenser change according to the ambient air conditions. For the above research when

an enthalpy heat exchanger was incorporated into a performance modelling programme,

sensible effectiveness of 0.9 is used for the heat exchanger (Zhang 2006). In fact for

enthalpy heat exchangers, achieving an effectiveness of 0.9 requires the use of a very low

air velocity which means the heat exchanger face area has to be very large.

Unfortunately, Zhang (2006) did not give the size of the heat exchanger used in his

simulation.


153

From their computer simulation they obtained the energy consumption by assuming the

compressor efficiency. To determine the efficiency of an air conditioner that incorporates

an enthalpy heat exchanger, Zhang (2006) performed a similar simulation for an air

conditioning system which uses 100% fresh air. Their energy analysis shows that a

system that incorporates an enthalpy heat exchanger consumes less energy than a system

that uses 100% fresh air without an energy recovery device. Unfortunately, no attempt

was made to model a conventional air conditioning system that operates based on mixing

of fresh air with room exhaust air which is widely used in air conditioning.

Therefore, the need arises for a method for assessing the performance of various

combinations of energy recovery devices with a standard air conditioner under varying

operating conditions throughout the year. Australian standard AS 3823.3 specifies a

method of performance evaluation using a computer simulation tool such as HPRate.

HPRate is a performance rating tool that evaluates the performance of vapour

compression air conditioning cycles (Morrison 2004). The HPRate simulation package is

a graphical interface to the ORNL MarkV heat pump model developed by the Oak Ridge

National Laboratory Tennessee for the USA Department of Energy. The program predicts

the steady state performance of electrically driven, vapour compression, air to air heat

pumps in both heating and cooling modes. It consists of FORTRAN model of the heat

pump components.

The model is based on underlying physical principles and generalised correlations in

order to make the program applicable to a wide range of equipment configurations. The

basic model does not incorporate empirical correlations derived for particular products. A

first principles thermodynamic model of the heat transfer processes in the coils and

analysis of the refrigerant states around the circuit are combined with psychometric

analysis of the air side of the coils to determine the operating state and provide an

assessment of equipment performance.


154

Transient (cyclic or frosting/defrosting) effects are not considered and the program has

physically based heat transfer models for single and two phase refrigerant regions of fin –

and-tube air to refrigerant heat exchangers. Parallel and series refrigerant circuiting is

evaluated and air-side dehumidification and evaporator sensible heat supply are

calculated.

The features of the model adopted within the HPRATE graphical front end allow the user

to specify system operating conditions such as indoor and outdoor air wet and dry bulb

temperatures and the arrangement of the compressor and fans in the air flow stream.

Compressor characteristics, refrigerant flow control devices, specified refrigerant sub-

cooling at the condenser exit, capillary tube or TX valve, fin and tube heat exchangers,

tube size, spacing, number of rows and parallel circuits, fin pitch, thickness, material,

type of fin (smooth, wavy or louvered), air flow rates, refrigerant lines, lengths, diameters

of interconnecting pipes, and heat losses from suction and discharge liquid lines are

modelled in HPRate.

The main restriction in the current model is that the user cannot specify the refrigerant

charge; instead it is assumed that the system is charged with the correct amount of

refrigerant for the specified operating conditions.

The HPRate code was modified to model an air conditioner which includes the effect of

adding a sensible and latent heat recovery heat exchanger to a conventional air

conditioning system. HPRate was combined with a model of an office space in order to

determine the transient operating states of the heat exchanger/air conditioner throughout

the year. HPRate was used to evaluate the cooling capacity, power consumption and

energy efficiency ratio on a 5 minute time step throughout the year. The HPRate model

was used to simulate off design performance so that the annual performance of a

combined cooling/heating system could be determined.

This chapter outlines the modifications that were made to HPRate to evaluate the annual

energy consumption of an air conditioner that utilises an enthalpy heat exchanger to


155

cool/heat an office space. HPRate was modified to read hourly weather data for ambient

temperature and humidity. By using the enthalpy heat exchanger effectiveness equations

the condition of air that exits the heat exchanger and then enters the air conditioning unit

is obtained and HPRate is used to compute the air-off conditions that leaves the

evaporator coil and enters the office space. The new model calculates the exhaust air

condition that exits the office space before the air enters the enthalpy heat exchanger

through using energy balance equations for the room; HPRate also computes the energy

consumed by the air conditioner. HPRate is also used to model a conventional air

conditioner which operates based on mixing of 65% room exhaust air with 35% of fresh

air. The details of HPRate modelling and code development are presented in this chapter.

8.2 HPRate flow chart and subroutines

The Mark V Oakridge model adopted by HPRate consists of a series of FORTRAN

subroutines that have been compiled into an executable file known as oakunsw.exe. The

simulation process starts by reading system specifications from the input file (simfile.in)

and outputs its results to two files: simfile.ou and simfile.gr (Fig 8.1), where simfile.gr

allows the visual basic front end of HPRate to display the conditions around the heat

pump refrigerant circuit including pressure, temperature, saturation temperature and

enthalpy.

The executable file of oakunsw.exe contains the subroutines shown in Fig 8.2

HPRate Simfile.in

oakunsw

Simfile.o

Simfile.g

Created

Fig 8.1 Relationship between HPRate and oakunsw


156

The program CONDRV is responsible for getting the air conditioner data from simfile.in

which is represented by the block HPDATA in Fig 8.2, calling appropriate subroutines to

convert values into imperial units and performing calculations on the compressor,

evaporator and the condenser iteratively. The following subroutines are the major

components of CONDRV (Morrison, 2002):

8.2.1 DATAIN

In DATAIN, the information contained in simfile.in is read into the subroutine and

subsequently printed on the output file simfile.ou.

8.2.2 TABLES

In TABLES, the transport and thermodynamic properties of R22 refrigerant are

developed. Similarly, these values are stored in BLOCKDATA for use in evaporator and

condenser routines.

CONDRV

SUMRPT

SSDRV CALC TABLES DATAIN

OUTPUT

BLOCK DATA MOGEDN

HPDATA

HX

DISPLAY

Fig 8.2 Flow chart of oakunsw


157

8.2.3 HX

Based on the dry bulb and wet bulb temperatures and flow rates of air entering the

condenser and evaporator, various properties such as the overall heat transfer coefficient

(U) are determined.

8.2.4 CALC

In CALC, the geometry related data of the evaporator and condenser are being computed.

This data includes the total heat transfer surface for air and refrigerant, frontal area and

length of the heat exchanger tubing.

8.2.5 SSDRV

SSDRV stands for the steady state driver where the majority of the calculations are

performed. Data such as the evaporator and condenser air-off conditions are determined.

Furthermore, the performance related data such as the cooling capacity, total input power

of the system and energy efficiency ratio (EER) are also determined in this subroutine.

The subroutine DISPLAY is also included in SSDRV to create the output file as simfile.gr.

The function of simfile.gr is to allow the visual basic front end of HPRate to artificially

display the conditions around the heat pump refrigerant circuit including pressure,

temperature, saturation temperature and enthalpy.

8.3 Accuracy assessment

Several studies have been conducted on air conditioners to assess the accuracy of HPRate

in term of its cooling capacity, power consumption and energy efficient ratio prediction

(Morrison 2004).

For standard air conditioner operation, the prediction of air conditioner operation were

found to have deviations from measured conditions of 2.6% in cooling capacity, 1.7% in

power consumption and 2.8% for EER (Morrison 2004).


158

In general, the predictions generated by HPRate are in close agreement with the measured

values. Therefore, HPRate is used in conjunction with the FORTRAN code model

developed by the author to evaluate the combination of an enthalpy energy heat

exchanger and an air conditioner used for cooling/heating of an office space.

Two systems were studied, the first is an air conditioning system coupled with an

enthalpy heat exchanger. The second system is a conventional air conditioning system

which operates based on mixing of 35% of fresh air mixed with 65% room exhaust air

(Fig 8.3). For both systems 1000L/s air flow is supplied to the evaporator and 1500L/s is

supplied to the condenser, However, for the enthalpy heat exchanger system 1000L/s

room exhaust air is mixed with 500L/s ambient fresh and supplied to the condenser coil.

For the conventional system 350L/s room exhaust air is mixed with 1150L/s ambient

fresh air and supplied to the condenser.

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159

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8.4 Code development

HPRate is used to study the annual performance of an air conditioner that incorporates an

enthalpy heat exchanger. As mentioned previously HPRate is designed to predict the

cooling and heating performance of a standard air conditioner and in this study the

HPRate model is modified to include the membrane heat exchanger in the system. The

original HPRate code was designed to quantify the performance of air conditioner at

standard AS 38523 rating point conditions. In the code developed here, HPRate has been

extended to model air conditioner performance throughout a year for variable operating

Fig 8.3 Schematic diagrams of enthalpy heat exchanger and conventional air conditioning systems


160

conditions specified by ambient temperature and humidity in standard typical

meteorological year weather files for the location of interest (Morrison and Litvak, 1988).

The new code reads the hourly weather data (dry and wet bulb temperature) for any city

around the globe presented in the typical meteorological year (TMY) format for

evaluation of an air conditioner coupled with enthalpy energy recovery system.

FORTRAN was selected as the platform of code development due to the fact that

oakunsw model was written in FORTRAN and its computational power is fast. A

FORTRAN model will allow the communication link between this code and Mark V

Oakridge model to be established easily.

The modelled HPRate code reads the hourly weather data and interpolates for shorter

time steps to achieve high sensitivity in the system modelling. Under this simulation, the

modelled HPRate code loops through 8760 hours of the weather data and at each hour the

weather data was interpolated into 5 minute time steps. As the energy recovered is

significantly affected by the heat exchanger effectiveness, the heat exchanger

effectiveness determined from the mathematical model to obtain the air-on conditions

supplied to the condenser and evaporator. For given outdoor conditions, the annual

energy consumed by the air conditioner to cool/ heat any room can be determined.

In situations when the temperature of the supplied air to the air conditioner is between

24°C and 18°C, the air conditioner compressor is turned off and the heat exchanger acts

as a passive cooling or heating device for the room. Since the air conditioner compressor

is not operating under these conditions, the simulated result in terms of energy

consumption will be the energy consumed to operate the fans only. If the air conditioner

is turned off most of the time, then the energy recovered will be high. This is because

cooling and heating can be achieved without operating the compressor which consumes a

large amount of energy.

To enable HPRate to execute the above tasks, the following subroutines and

modifications were developed and included in the simulation package:


161

8.4.1 GETDAT subroutine

Annual weather data presented in typical meteorological year (TMY) format is used in

this simulation. The GETDAT subroutine, the dry and wet bulb temperatures of the

outside air are read and stored in the real variables Ta and Twet respectively.

Subsequently, these variables are passed as arguments to the rest of the program.

8.4.2 INTERP subroutine

�

As the weather data is available in the hourly format, the data must be interpolated for

shorter time step analysis. The analysis of the operation of the heat exchanger and air

conditioner is carried out at 5 minutes intervals in order to follow the time averaging

operating conditions and to model air conditioner ON/OFF cycling. The air conditioner is

turned OFF when the air temperature that enters the evaporator coil is in the range 18-

24°C.

8.4.3 ERV subroutine

�

To incorporate energy recovery devices such as enthalpy heat exchanger in the program

algorithm of HPRate, a subroutine known as ERV was written to incorporate the enthalpy

heat exchanger effectiveness. The hourly weather temperature is read in GEDAT and

interpolated into 5 minute time steps in INTERP subroutine. The temperature is then read

into the ERV subroutine and the air conditions exiting the heat exchanger are determined

from the following equations 8.1 to 8.4 as shown in Fig 8.4.

( )evap a s a roomT T T Tε= − − (8.1)

( )cond room s a roomT T T Tε= + − (8.2)

( )evap a L a roomω ω ε ω ω= − − (8.3)


162

From the above equations, the air conditioner inlet air conditions to the coils are obtained.

( )evap a s a roomT T T Tε= − −

( )evap a L a roomω ω ε ω ω= − −

ω

ωroomω ( )cond room s a roomT T T Tε= + −

( )cond room L a roomω ω ε ω ω= + −

aω

In order to model a conventional air conditioner that operates based on mixing of 35%

fresh air with 65% room exhaust air, the ERV subroutine will calculate the air

conditioner air-on conditions from the following equations

air on room ambient=(0.65 )+(0.35 )ω ω ω (8.5)

room room room roomh =(1.005T )+( (2501+(1.83T )))ω (8.6)

ambient ambient ambient ambienth =(1.005T )+( (2501+(1.83T )))ω (8.7)

air on room ambient=(0.65 )+(0.35 )h h h (8.8)

hence the air conditioner air-on temperature is obtained as follows

air on air on air on air onT =(h -(2501 ))/(1.005+(1.83 ))ω ω (8.9)

If the air-on temperature entering the air conditioner is less than 18oC, the operation

mode of the heat pump will be changed to heating mode. However, if the air-on

temperature is higher than 240C, the operation mode is switched to cooling mode.

As mentioned earlier the subroutine CONDRV reads equipment input data from

simfile.in which is represented by the block HPDATA in Fig 8.2, calls the appropriate

( )cond room L a roomω ω ε ω ω= + − (8.4)

Fig 8.4 Data flow of ERV.for


163

subroutines to convert values into imperial units and performs calculations of the

compressor, evaporator and the condenser performance iteratively. A subroutine called

MODSIM was written to perform the function of a real time updating mechanism which

the air-on air conditions leaving the enthalpy heat exchanger or the air mixing zone and

entering the air conditioner will be transferred through the MODSIM subroutine and

modify the file simfile.in as per the hourly weather data air conditions and update the

operating mode (heating or cooling mode).

The operation of the modified HPRate code is represented in the flow chart shown in Fig

8.6. The rectangular box represents process, the parallelogram represents data input and

the rhombus represents decision making. Each process is executed by a subroutine shown

in oval shape box adjacent to the process box.

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164

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Fig 8.5 Flow chart of FORTRAN model


165

After modifying simefile.in, HPRate performs the simulation based on the supplied air

conditions (air-on conditions). This analysis is continued throughout the year using the

five minute time step weather data.

Room temperature is calculated from energy balance on the space as follows:

The cooling/heating provided by air conditioner

cooling/heatingQ = ( )air pair room evapm C T T− (8.10)

The heat transfer through the walls is

heatQ = ( )office ambient roomAU T T− (8.11)

By equating the above equations and adding the sensible load in the room the temperature

is obtained as follows

heat coolingQ =Q loadQ+ (8.12)

substituting 8.10 and 8.11 into 8.12, the space temperature is given by

ambient air p air evap Loadroom

air p air

AUT m C T QT =

m C AU

+ +

+ (8.13)

To enable the FORTRAN code to perform the first calculation where the room air

conditions are unknown, it was assumed that for the first 5 minutes the room temperature

and relative humidity are 24 °C and 50% respectively. The hourly ambient dry and wet

bulb temperature is read in GETDAT subroutine and interpolated into 5 minute time

steps in INTERP subroutine. From psychometric calculation, the ambient moisture

content is obtained. The ambient air temperature and moisture content is then read in the

ERV subroutine. When the enthalpy heat exchanger is used, the heat exchanger

effectiveness equations are incorporated in the subroutine (equations 8.1 to 8.4). In the

case where air mixing process is used (35% fresh air mixed with 65% room exhaust air)

the air mixing equations are incorporated into the subroutine (equations 8.5 to 8.9).

Hence the conditions of air entering the evaporator and condenser are obtained.

The MODSIM subroutine functions as a real time updating mechanism and transfers the

air-on conditions leaving the enthalpy heat exchanger or the air mixing zone and entering


166

the air conditioner to the file simfile.in together with the hourly weather data air

conditions and operating modes (heating or cooling mode). The CONDRV subroutine

then reads data from simfile.in and performs calculations of the compressor, evaporator

and the condenser performance iteratively.

From CONDRV, the air temperature and moisture content at the condenser and

evaporator outlets are obtained. Using equation 8.13 which is incorporated in CONDRV,

the room temperature and moisture content is calculated for the next 5 minute time step.

��

Chapter 9: System Energy Analysis Results �

167

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9.1 Introduction

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The details of HPRate modelling of an air conditioner that utilises an enthalpy heat

exchanger and an air conditioner that operates based on air mixing were presented in

chapter 8. The aim of this chapter is to study the annual energy consumption for these

systems and to perform a comparison on the annual energy use for cooling and heating of

each system in different locations. The last part of this study is extended to evaluate the

energy consumption of an air conditioner for a range of enthalpy heat exchanger face

areas.

9.2 Simulation performance of air conditioner and enthalpy heat exchanger

�

HPRate simulation was performed for Sydney and Kuala Lumpur weather conditions.

The weather in Sydney is moderate, while the weather in Kuala Lumpur is hot and

humid. The simulation was performed for an air conditioning system coupled with an

enthalpy heat exchanger and a conventional air conditioning system based on air mixing.

In cases where the air temperature entering the evaporator is between 24 and 18°C, the

compressor is switched off and the heat exchanger or the air mixing zone will then act as

a passive cooling or heating device for the room. Under these conditions when the air

conditioner compressor is not operating, the simulated result in terms of energy

consumption will be the energy used to operate the evaporator and condenser fans only.

The analysis is conducted for an office space of 300 m2 area for operating hours from 9

am till 6pm and for an internal load of 1kW. The AU value of the building envelope used

was 2kW/K.

In this simulation the air volumetric flow rate supplied to the evaporator is 1000 L/s and

1500L/s is supplied to the condenser (chapter 8 Fig 8.3) and the refrigerant used by


168

HPRate is R22. Enthalpy heat exchanger inlet stream face area is 3.3m2 and air face

velocity of the heat exchanger is 0.3m/s. The enthalpy heat exchanger sensible, total and

latent effectiveness for an air face velocity of 0.3m/s were 0.71, 0.66 and 0.61

respectively. The effectiveness was obtained from the 60gsm paper heat exchanger

effectiveness curves shown in chapter 5, Fig 5.9.

The evaporator and condenser specification are shown in Fig 9.1

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The compressor specifications are shown in Fig 9.2

Fig 9.1 Evaporator and condenser size and components


169

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The simulation results are presented as follows:

9.3 Annual energy analysis of an air conditioner for Sydney

HPRate simulation of an air conditioner coupled with an enthalpy heat exchanger and

conventional air recirculation air conditioner is performed using Sydney hourly weather

data. Energy consumption of the air conditioner obtained from the above simulation is

presented in Fig 9.3 and shows that the air conditioning system that utilises an enthalpy

heat exchanger consumes less energy than the conventional air conditioning system that

operates based on air mixing. The enthalpy air conditioner has achieved lower operating

cost while simultaneously providing 100% fresh air.

Fig 9.3 shows that when the weather is hot and humid in summer and the sensible and

latent cooling load is high, the amount of energy consumed by enthalpy heat exchanger

system was 5%, 8.3% and 4.6% less in December, January and February respectively

than a conventional air conditioning system.

Fig 9.2 Compressor details and capacity


170

Similarly in March the air conditioning system coupled with an enthalpy heat exchanger

consumes less energy than the conventional system. Whereas in April, the amount of

energy consumed recorded its lowest values, the energy consumption for both systems

was almost the same and that is due to the moderate weather.

Fig 9.3 also shows that the energy consumption started to increase in winter season (from

May till July) as the weather became colder and heating load becomes higher.

Nonetheless, the system coupled with enthalpy exchanger system consumes 6.4% less

energy than the conventional reverse cycle air conditioning system.

When spring season began, the energy consumption decreases and the air conditioning

system coupled with enthalpy heat exchanger continue to consume less energy. However,

the energy consumption difference between both systems was less in the winter heating

season than in the summer cooling season.

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month

En

erg

y co

nsu

mp

tio

n b

y an

air

co

nd

itio

ner

(G

J)

Air mixing (conventional system)

Membrane heat exchanger

8.3%

4.6%7.1%

0.2%

5%

3.7%

6.4%

3.5%

1.7% 0.1%

0.1%

5%

Seasonal energy analysis shows that the energy saving recorded by an air conditioning system

coupled with an enthalpy heat exchanger in winter season was 4.7% less than

conventional air conditioning system (Fig 9.4). In summer the humidity and temperature

Fig 9.3 Sydney monthly energy consumption for reverse cycle air conditioner (figures show difference in energy used by the two systems)


171

increase in Sydney, hence, the heat exchanger acts as both an energy recovery and

dehumidifying tool which will reduce the latent load. Consequently, in summer, energy

consumption of an air conditioning system coupled with enthalpy heat exchanger was

6.2% less than the conventional system.

This shows the importance of utilising the enthalpy heat exchanger in an air conditioning

system as an energy recovery and dehumidifying tool to reduce the latent load while

simultaneously providing 100% fresh air.

�

0

2

4

6

8

10

12

Winter Spring Summer Autumn

Season

En

erg

y co

nsu

mp

tio

n b

y an

air

co

nd

itio

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(G

J)

Air mixing (conventional system)Membrane heat exchanger

4.7%

1%

6.2%

4.7%

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9.4 Annual energy analysis of an air conditioner for Kuala Lumpur

In a tropical climate like Kuala Lumpur, the weather is hot and humid throughout the

year and the latent load is high. Fig 9.5 shows the annual monthly energy consumption is

almost the same throughout the year. However, it can be seen that the air conditioning

system coupled with an enthalpy heat exchanger consumes less energy than the

conventional air conditioning system. The enthalpy exchanger system consumes between

5.7 to 9% less energy than the conventional system resulting in energy saving throughout

Fig 9.4 Sydney seasonal energy consumption for reverse cycle air conditioning systems


172

the whole year. This is due to the hot and humid climate in Kuala Lumpur throughout the

year, where the amount of energy required to dehumidify the air by an air conditioner is

large. Hence, utilising an enthalpy heat exchanger to dehumidify the air before it enters

the air conditioning system will contribute significantly in reducing the latent load,

resulting in energy saving.

��

0

1

2

3

4

5

6

7

8

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month

Ene

rgy

con

sum

pti

on

by

an a

ir c

ond

itio

ner

(GJ)

Air mixing (conventional)


7.3% 6.3%

6.9%6.8%

5.7%

6% 7% 6.8%8.8%

7.3%9%

7.6%

HPRate simulation and energy analysis were then performed on different cities such as

London, Miami, Tokyo and Dubai (the detailed monthly and seasonal energy

consumption for these cities are presented in appendix E).

The summary of the total annual energy analysis shown in Fig 9.6 illustrates that the

highest annual energy consumption recorded was in Kuala Lumpur. Where, using

enthalpy heat exchanger system resulted in 4.9GJ energy saving in comparison with the

conventional air conditioning system.

In Miami, utilising enthalpy heat exchanger in an air conditioning system has recorded

4.23GJ energy saving. In Dubai, due to the hot and humid climate in spring, summer and

Fig 9.5 Kuala Lumpur monthly energy consumption for reverse cycle air conditioner


173

autumn, enthalpy heat exchanger system annual energy consumption was 3.12GJ less

than the conventional system.

In Tokyo, the annual energy saving was 1.61GJ. Although the annual energy

consumption in Sydney was the lowest in comparison with other cities, however air

conditioning system coupled with enthalpy heat exchanger consumes 1.36GJ less than the

conventional air conditioning system.

In London, the annual energy consumption was relatively high due to the cold climate.

Nevertheless, an air conditioning system coupled with an enthalpy exchanger consumes

1.16GJ less than the conventional air conditioning system.

0

10

20

30

40

50

60

70

80

Sydney London Miami Kuala Lumpur Dubai Tokyo

En

erg

y co

nsu

mp

tio

n b

y an

air

co

nd

itio

ner

(G

J)

Air mixing (conventional system)


1.36 GJ

1.16 GJ

4.23 GJ

4.9 GJ3.12 GJ

1.61 GJ

��

The above energy analysis shows that an air conditioning system coupled with an

enthalpy heat exchanger performed well in terms of energy consumption in comparison

with conventional air conditioning system in all locations investigated.

Fig 9.6 Annual energy consumption for reverse cycle air conditioner (figures show the energy difference between the two systems)


174

In addition to the sensible energy recovered, the enthalpy heat exchanger also decreases

energy consumption in hot and humid climate by reducing the latent load where the heat

exchanger dehumidifies the air before it enters the air conditioning system, causing a

decrease in energy consumption. Hence, the decrease in energy consumption was higher

in hot and humid climates like Miami, Kuala Lumpur and Dubai. This shows the

importance of reducing the latent load to achieve lower energy consumption.

To study the effect of varying the heat exchanger face area on energy consumption,

Kuala Lumpur weather data was used as a bench mark to perform this investigation since

enthalpy heat exchanger performs well and consumes less energy in a hot and humid

climate.

In this study the energy saving is calculated as the difference between the energy

consumption of an air conditioner that incorporates an enthalpy heat exchanger and a

conventional air conditioner that operates based on air mixing

saving = Enthalpy exchanger system conventional systemE E E− (9.1)

The area ratio (Aratio) shown in Fig 9.7 represents the ratio of the enthalpy heat exchanger

face area to the face area of the evaporator coil (0.5m2). Fig 9.7 shows as the enthalpy

heat exchanger face area increases, the amount of energy saved increases. As increasing

the heat exchanger face area will decrease the air velocity and subsequently the heat

exchanger effectiveness has increased.


175

0

1

2

3

4

5

6

0 1 2 3 4 5 6 7 8

A ratio

E s

avin

g (G

J)

Air face velocity 1.5 m/s



Air face velocity 1 m/s

It can be seen that a substantial amount of energy is saved when the enthalpy heat

exchanger is incorporated in an air conditioner especially in tropical climates. In addition

to the energy saving, an air conditioner coupled with an enthalpy heat exchanger also has

the advantage of providing 100% fresh air which significantly improves indoor air

quality.

Fig 9.7 Effect of changing enthalpy heat exchanger face area on annual energy saving in Kuala Lumpur (air face velocity indicated on top of each point)

Chapter 10: Conclusions and Recommendations �

176

��1��

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10.1 Conclusion This thesis evaluated the performance of an enthalpy Z type flow fixed-plate air-to-air

heat exchanger used to recover both sensible and latent heat in HVAC systems. The heat

exchanger performance was evaluated experimentally and numerically.

It was found that the heat exchanger performance was significantly influenced by the heat

exchanger configuration (cross flow and counter flow), flow profile, heat and moisture

transfer area, inlet area, inlet air velocity, heat and moisture transfer material

characteristics and inlet air conditions (air moisture content).

To study the above parameters on the enthalpy heat exchanger performance, experimental

investigations were carried out using laboratory scale test rig to determine the

effectiveness of the heat exchanger with various air velocities. Several materials were

used in this investigation, including thin 45gsm and 60gsm porous paper.

It was found that sensible effectiveness was the same for both papers. This is attributed to

the small effect of the conduction thermal resistance of the heat transfer surfaces due to

the small thickness of the paper surfaces. However, the latent effectiveness was different

where up to 28% increase in the latent effectiveness was achieved when 60gsm paper was

used. This is attributed to the significant effect of the moisture resistance of the paper

which has a considerable effect on the moisture transfer and consequently latent heat

transferred.


177

It was also found that reducing air velocity will cause an increase in the enthalpy heat

exchanger effectiveness. Which is due to the air resident time in the heat exchanger, the

more resident time the air is given, the more heat and moisture transfer is allowed to take

place. It was observed that as the velocity of the air flow decreases, higher effectiveness

values were recorded.

The use of experiments to study the effects of varying the design and operating

parameters on the performance of the enthalpy heat exchanger is expensive and time

consuming. Therefore, numerical studies were undertaken to develop mathematical

models using effectiveness-NTU method and Nusselt and Sherwood number correlations

to be used as a design aid to predict the heat exchanger performance when the heat

exchanger design parameters are changed. The outcomes from the experimental

measurements were used as benchmark cases to validate the results from numerical

simulations.

Due to the substantial effect of moisture transfer resistance of the paper on the heat

exchanger latent performance, permeability measurements were undertaken according to

the ASTM standard E 96-00 requirements.

The experimental permeability measurements show that unlike the conduction thermal

resistance which remain constant under different conditions, the membrane moisture

transfer resistance is influenced by the membrane material and operating conditions. The

measurements also show that moisture transfer resistance of 45gsm paper was around

50% higher than the 60gsm paper. Hence higher latent effectiveness values were

achieved when 60gsm paper was utilised.

The mathematical model was then used to study the effect of decreasing the heat

exchanger flow path hydraulic diameter on the heat exchanger performance. It was found

that reducing the heat exchanger flow path width by 30% has boosted the latent and

sensible effectiveness by around 20%. Decreasing the flow path width decreases the air

mass flow rate and this increases the Number of Transfer Units (NTU) which resulted in


178

an increase of effectiveness. However, this increase was achieved at the expenses of

increasing pressure drop through the heat exchanger.

The mathematical model was also used to predict the effectiveness of another Z shape

heat exchanger which has 13% less counter flow heat and moisture transfer area than the

existing Z type heat exchanger. The result shows that the sensible and latent effectiveness

decreased by around 6% in comparison with the existing Z type flow heat exchanger.

Understanding the performance of the enthalpy heat exchanger requires in depth

knowledge the temperature and moisture distribution in the heat exchanger. Therefore,

this research was extended to perform numerical simulation modelling study using a

Computational Fluid Dynamics (CFD) package, FLUENT. However, the available CFD

packages such as FLUENT suffer from limitations when it comes to modelling moisture

diffusion across a porous boundary. The shortcoming of this software is that it cannot

model the moisture diffusion through porous materials. Therefore, two methods have

been introduced to model the moisture transfer in the heat exchanger. Firstly, a non-

dimensional sensible-latent effectiveness ratio was used to determine the moisture

content at the paper boundary. The second method in modelling the moisture transfer in

the heat exchanger is to utilise Lewis number correlation to obtain the moisture boundary

conditions at the paper heat exchanger surface. Both methods were validated against the

experimental results and reasonable agreement was achieved.

The existing Z shape heat exchanger flow paths consists of 5 flow dividers ribs which

provide more uniform flow distribution in the heat exchanger The developed CFD

methods were used to study the effect of varying the number of flow dividers ribs on the

heat exchanger performance.

It was found that a 21% increase in the effectiveness was achieved when the number of

ribs was increased from no ribs to 5 ribs. Increasing the number of ribs contributed

significantly to making temperature, flow and moisture distribution more uniform

throughout the heat exchanger. However, increasing the number of ribs from 5 to 11 have


179

only minor effect on effectiveness as the flow, temperature and moisture distribution are

already uniform. Therefore, no significant improvement is noticed when the number of

ribs is increased beyond 5.

The effect of changing the heat exchanger flow profile on the heat exchanger

performance was also investigated. The L shape flow configuration heat exchanger was

modelled which has a larger counter flow area than the Z flow heat exchanger. The result

shows a 4% increase in the sensible and latent effectiveness is achieved in comparison

with the existing Z shape flow heat exchanger.

The effective utilisation and annual performance of an air conditioner coupled with

enthalpy heat exchanger was investigated in relation to a conventional air conditioning

system that operates based on mixing of fresh air with the room exhaust air. Performing

annual experimental investigation on a real air conditioner to study the annual energy

consumption for both enthalpy heat exchanger and conventional system is expensive and

time consuming. Therefore, HPRate software which is performance rating software that

is able to predict the steady state heating and cooling performance of a vapour

compression, electrically driven, air to air reverse cycle heat pumps was used to carry out

the investigation. The annual performance investigation was achieved by developing a

modelled version of HPRate which reads the yearly weather data of different cities

around the globe, and incorporates the enthalpy heat exchanger effectiveness functions.

Energy analysis shows that an air conditioning system coupled with an enthalpy heat

exchanger performed well in hot and humid climates and contributed significantly in

reducing the latent load where systems coupled with enthalpy exchangers consumed 8%

(4.9GJ) less energy throughout the year than the conventional air conditioning system in

Kuala Lumpur. Similarly for Miami and Dubai, energy analysis shows that an air

conditioning system coupled with enthalpy heat exchanger consumes 8% (4.23GJ) and

5% (3.12GJ) less energy than the conventional air conditioning system. Whereas, in a

moderate climate like Sydney, systems coupled with enthalpy heat exchanger consumed

4% (1.36GJ) less energy than the conventional air conditioning system.


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It can be seen that the membrane heat exchanger provides more energy saving in humid

climates as it reduces the latent load. In dry climates the energy saving was less,

indicating the significant effect of the latent load on energy consumption in humid

climates. The membrane heat exchanger is recommended for humid climates as it can

reduce both sensible and latent loads rather than using sensible heat exchanger that can

only reduce the sensible load.

The effect of varying the heat exchanger face area on the enthalpy heat exchanger

performance and the air conditioner annual energy consumptions was also studied in a

humid climate. It was found that energy consumption was significantly reduced when the

heat exchanger face area increased. Where increasing the heat exchanger face area

reduces the annual energy consumption by 4.9GJ.

These results show the significant contribution of the enthalpy heat exchanger in reducing

the latent load in hot and humid climates and the substantial energy saving achieved in

comparison with conventional air conditioning systems. In addition to that, enthalpy heat

exchanger has the advantage of providing 100% fresh air. This will lead to reductions in

energy consumption in buildings and corresponding reductions in greenhouse gas

generation and enormously improves indoor air quality. However, installing the heat

exchanger requires providing additional space and may require additional ducting.

10.2 Recommendations

We can conclude that the performance of a membrane fixed-plate energy recovery heat

exchanger was influenced by many parameters such as heat exchanger flow profile and

configuration, heat exchanger operating conditions and membrane material

characteristics.

In this study the effect of varying the above parameters is investigated. However, further

research is required to examine other membrane material that provides higher moisture

transfer leading to higher latent effectiveness values. The results presented show


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promising technique in determining membrane moisture transfer resistant through

performing permeability measurements. This measurement could be performed on other

membrane materials in order to achieve higher latent effectiveness values. The

permeability measurement could be extended to investigate the effect of temperature and

moisture content on the membrane material characteristics.

In this research, two methods were developed to model moisture transfer using

commercial CFD package, FLUENT. This approach can be used to perform further study

through varying the heat exchanger design parameters such as studying the effect of

utilising turbulent promoters in the heat exchanger in order to achieve higher

effectiveness values. However, pressure drop effect has to be investigated using CFD

modelling.

CFD modelling can also be used to study the effect of different boundary conditions on

the heat exchanger performance, including varying the membrane material and varying

the operating conditions such as the moisture content gradient between the two inlet

streams.

Further investigation and research needs to be conducted on gas diffusion through

membrane surface such as Carbon Dioxide which has a great effect on indoor air quality.

This study could be performed based on measurements and could be extended to

numerical modelling using CFD packages to study gases distribution and transfer in the

heat exchanger.

System energy analysis study shows the importance of utilising membrane fixed-plate

heat exchanger in HVAC systems, especially in humid climates. However, further energy

analysis investigation is needed to model different types of buildings, such as hospitals,

residential units, swimming pools and gymnasiums using the modelled HPRate software

to predict the energy consumption of an air conditioning system. Further research is also

needed to investigate the effect of using the heat exchanger on energy consumption and


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air conditioner performance when different evaporator and condenser sizes and types are

used.

More development could be performed on HPRate model through including ducting

system, glazing and room thermal mass into the model.

HPRate energy analysis could also be used to perform further energy analysis on climates

other than those modelled in the present research and to study the effect of varying the

refrigeration cycle components (evaporator, condenser) on energy consumption. In

addition, further investigation is needed to study the effect of varying the latent load in

the modelled room on energy consumption of the air conditioning system.

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cfd simulation of flow heat and mass transfer

Engineering