TO: Mr Mitch Cottrell, Instr ME240 7 MAY 2010

Mr. Steven Rodgers, TA ME240

FR: Max Trueblood

David LeBlanc

RE: ME240 Semester Project

Controlling a Gas Flow in the ALGR using LV

INTRODUCTION

Several industries utilize condensation nucleus counters (CNC) to measure the

concentration of nanometer sized airborne particulates. With the heightened awareness

of how very small particles can adversely affect human health, more emphasis in recent

years has been placed on monitoring sources of these particles, e.g. aircraft engines.

Clearly to arrive at trustworthy data one needs a reliable instrument to measure the

concentration of aerosol particles, or at least a measure of the detection efficiency of

these instruments with respect to particle diameter. The alternating gradient diffusion

cloud chamber (ALGR) can be trusted to measure all particles down to approximately 3

nm diameter. Thus it can be used to calibrate CNCs.

The objective of this project was to build a Labview program to control one of the gas

flows in the alternating gradient diffusion cloud chamber (ALGR) so that data taking

was more reliable.

EXPERIMENTAL APPARATUS

The basic setup for calibrating the CNC is shown in Figure 1. An aerosol source, such as

a nebulizer provides a polydisperse aerosol source. This aerosol is classified or cut into a

very narrow slice (wrt diameter) of particles by the differential mobility analyzer (DMA)

(Figure 2). A clean flow of approximately 20 L/m called the sheath air flow surrounds

the central rod. A polydisperse aerosol is allowed in near the top (approximately 2 L/m)

and the two flows are both very laminar. The charged particles are pulled inward toward

the central rod by an electric field and particles of a very narrow diameter range would hit

the rod near the bottom, but leave the DMA in the monodisperse flow. This flow is now

directed to both the ALGR and the CNC under test.

A schematic of the CNC is shown in Figure 3. A schematic of the ALGR is shown in

Figure 4. Figure 5 directs the reader’s attention to some of the flow and pressure

considerations about the ALGR. Please note that the pressure drop across the SMT could

very easily be disturbed by the other much larger flows and pressure drops. A typical

calibration of the SMT is shown in Figure 6. A calibration curve for a typical CNC is

shown in Figure 7.

Simultaneous measurements of the concentration are made by both the CNC and the

ALGR. The efficiency of the CNC is then given by

EFF = Ccnc / Calgr

=[(Ncnc / min)/ (Qcnc)] / [(Nalgr/min) / ( Qsmt )] * [ 1 / PEN ] (1)

where the flow through the SMT is a function of the pressure drop across it:

Qsmt = F(dPsmt) (2)

and where Ncnc/min is the number of particles counted / min by the CNC, Qcnc is the

flow rate into the CNC, Nalgr/min is the number of particles counted / min by the ALGR,

Qsmt is the flow into the ALGR through the sample metering tube (SMT), and PEN is

the penetration of particles through the SMT. The second expression shows that the

Qsmt is a function of the pressure drop across this tube.

The PEN can be computed from a theoretical expression that takes into account the

diameter of the particles, the length of the SMT, and flow rate through the SMT. Clearly

the main source of error here will be the Qsmt, since this flow is approximately 0.010

L/m and all the other flows are approximately 3.0 L/m.

This Qsmt is computed from knowing the pressure drop across the SMT; this relationship

is determined from calibrating the Qsmt against the dPsmt using a soap bubble in a

chemistry burette and a stop watch, as shown in Figure 6. This pressure drop is only

about 1 inch of water. Clearly such a small flow rate can easily be upset by the much

larger flows in the ALGR, and it is very desirable to try to keep all the other flows

constant. One way to keep the dPsmt constant is to set all but one of the ALGR flows

constant using mass flow controllers and control the last one using a feedback loop based

on a set point and the measured value of the dPsmt. This was the purpose of the present

project.

It was also desired to have the ALGR controlled in 3 separate ways:

(1) controlling the MFCs with a manually controlled potentiometer,

(2) controlling the MFCs with a programming signal generated in the Labview

program, but set manually, and

(3) controlling the MFC with a programming signal generated in the Labview

program that is based on a feedback loop that is designed at keeping the dPsmt constant.

TRANSDUCER CHOICES

The three MFCs were Tylans, of various model numbers one of the experimenters

obtained from eBay over the past several years. They all three take + / - 15 VDC for

power, 0-5VDC as control signals, and send out 0-5VDC as output signals. The Tylan

company is no longer in business and this experimenter did not receive any manuals with

the MFCs. The pressure transducer was also bought off eBay and has no manual

accompanying it. It requires 24 VDC for excitation and outputs a 0 – 6.7 VDC signal.

Thus, there really were no choices to be made.

ERROR ANALYSIS

The present experimenters understand that one of the goals of this project is to utilize the

skills learned previously concerning perturbation. However, inspection of Eq (1) shows

that none of the flows Q1, Q2 or Q3 enter into the calculation for the EFF. That is, the

number counted by the CNC (Ncnc/min) is done internally and we have no way to deal

with that. The flow rate into the CNC is calibrated with a Gilibrator, a commercially

available device that measures the time it takes a soap bubble to pass between two points

along an acrylic tube, where the volume between these two points is very well known.

We might just arbitrarily assume a 1% accuracy on this number. However, for the

purposes of this project where we are concerned with how well our LV approach to

gathering data works, and we will not consider this contribution into the error in Qsmt.

The number counted / min by the ALGR (Nalgr/min), done by a Pulse Height Analyzer

(purchased from MET ONE, Grants Pass, OR), is also done internally and we have no

way to deal with that either. The PEN is a theoretical expression and we have no way to

deal with that. The only other variable is the flow rate through the SMT, which we can

deal with using the perturbation method taught in class.

Using the soap bubble in a burette and stop watch technique, the calibration equation for

the SMT is approximately

Qsmt = 15 (cc/min * inWC)* dPsmt (inWC) = 15 (cc/min*inWC) (3)

The CAL equation for the pressure transducer is

dPsmt = 1 (inWC/6.7V) = 0.149 inWC/V (4)

Although the present experimenters do not have the specs on this transducer, a similar

one was found on the web. It is an Ashcroft, MN CXLdp, for $238. It states an

uncertainty of 0.8% FS. We assume ours is a little worse, i.e., 1% FS. This would give

dQsmt = 0.01* (0.149inWC/1V) = 0.00149 inWC (5)

Thus the uncertainty in the Qsmt due to the pressure transducer itself is

dQsmt-tdcr = 15 (cc/min*inWC) * 0.00149 (inWC) = 0.0224 cc/min (6)

The USB-6009 has an absolute accuracy of 14.7 mV. Thus the uncertainty in Qsmt-6009

would be

dQsmt-6009 = 3.788(cc/min*V) * 0.014V = 0.053 cc/min (7)

By inserting these two values into the spreadsheet that was used in the homework on

perturbation, the total uncertainty in the Qsmt is 0.0575 cc/min. The percent error then is

DELQsmt = (0.0575 cc/min) / (15 cc/min) * 100 % = 0.384% (8)

LABVIEW PROGRAM

The Labview program reads in four signals, the dPsmt from a 0-1 inch WC transducer,

the MFC 1, the MFC 2, and the MFC 3. Figure 8 shows a circuit built to allow the

experimenter to change how MFC1 is controlled. By setting switch S1 to the left, a

potentiometer that is manually controlled sets the set point for MFC1. By throwing S1 to

the right, this programming signal is set by the computer.

The screen print of the basic program is shown in Figure 9 (no feedback loop in this

version). Figure 10 shows the corresponding front panel. Four channels of the 6009 are

used, with AI0 reading the pressure transducer, AI1 reading the MFC1, AI2 reading the

MFC2, and AI3 reading the MFC3. Fifty samples are taken in each batch. Four

INDEXARRAY VI's are used to separate the four signals and their averages are

computed with the MEAN.vi. These mean values are displayed on the Front Panel and

also sent to a BUILDARRAY vi, and then sent on to a WRITE TO SPREADSHEET vi.

Meanwhile a CONCATENATE STRINGS vi builds the column headings from individual

string inputs. A SECONDS TO DATE / TIME vi sends it output into an UNBUNDLE

BY NAME vi to pull out the hours, minutes and seconds. The output of this goes into a

formula node to compute the seconds after midnight (SAM) which is the first column of

the output file. A TIME DELAY function was installed in the Block Diagram to keep the

CPU from going nuts.

There are two POWER switches that allow shutting the outer loop and the inner loop

down so that one does not have to use the ABORT button if one does not want to. We

know that in LV, when the program starts, everything in the outermost loop must

complete or be ok before the next inner loop can begin its processing. When the program

tries to quit, the innermost loop must have completed all its activities or at least be told to

stop by a power button before the next outer loop may stop.

The measured values of dPsmt, Q1, Q2, and Q3 are charted on the front panel. Also

shown on the Front panel are the number of elements in dimension 0 and dimension 1 of

the incoming data. These were installed as a diagnostic tool during the writing of the

program and were just left in.

On the Front Panel, ones sees places to choose what physical channels to use for the four

AIs and what channels to use for the two AOs. This is best done using the BROWSE

feature. Also shown is control for specifying where the data should be written to. The

four measured values of dPsmt, Q1, Q2, and Q3 are shown beneath that. Below that are

controls to set the set point values of the desired value of the pressure drop across the

SMT (dPsp), Q1sp, and Q2sp.

In Figure 11 is shown the block diagram for the fully automated version of the program.

On the front panel of this version (Figure 12), to the right of the two vertical slide

controls is a Boolean switch that determines what case the program is in on the block

diagram. In the TRUE case, the program uses a closed loop feed back to read and

compare the measured dPsmt to the desired value dPsp and generate a correction to the

Q1 value. In order to avoid oscillation a GAIN factor is inserted. In the FALSE case, the

operator simply slides the Q1sp slide pot up and down to manually set the value desired.

The block diagram for this FALSE case is not shown.

Both the manual setting of the flows and the closed loop setting of dPsp (and thus setting

of Q1sp) worked quite well. Figure 13 shows tabulated data for the manual setting of Q1

from about 0.8 to 0.55 to 0.95 and the corresponding changes in dPsmt. Note that Q2 did

not change, as it should not since it was being controlled by its own set point. Note also

that Q3 shows a reading of zero. Evidently Q3 will not send out its signal. However, it

is actually being controlled by the manual potentiometer, since there is a rotameter in

series with it and that shows variation in flow.

Figure 14 shows the response of dPsmt and Q1 for a manual change in Q1 with the pot.

Figure 15 shows the response of the dPsmt and Q2 for a manual change in Q2 with the

pot. Figure 16 shows the response dPsmt and Q1 for when a new value of dPsp was set

in the LV program with the slide pot on the Front Panel.

CONCLUSIONS

A Labview program was written that reads dPsmt, Q1, Q2, and Q3. It has the options to

(1) control Q1 and Q2 with a slide pot on the Front Panel, and

(2) control dPsmt by stating a desired value for it as dPsp. This dPsp is compared

to the measured value dPsmt and a correction to Q1 is applied that brings dPsmt to at or

near the desired value dPsp.

Also achieved was a totally separate control box that uses switches and potentiometers to

choose between controlling the MFCs manually with the pots or controlling them with

the LV program (which again can control them manually or with a feedback loop).

Appendix A

Figure 1. Overall schematic of calibrating a CNC

.

Figure 2. Differential mobility analyzer.

Figure 3. Schematic of the condensation nucleus counter (CNC).

Figure 4. Schematic of the ALGR

Three pumps:

AP1 Laser Ptle Counter loop

AP2 Filtered air at top

AP3 Excess air at bottom

Eight flows:

Q1 Excess at bottom

Q2 Filtered at top

Q3 LPC loop out

Q4 LPC loop

Q5 AP2 make up

Q6 LPC loop in

Q9 LPC annular in

Qsmt sample metering tube

Q1 – Q9 ~ 1 to 4 L/m

Qsmt ~ 0.010 L/m

Qsmt = 3.55 * dPsmt – 5.42

dPsmt ~ 1 inch H2O

Figure 5. Flow and pressure considerations for the ALGR.

MFC 1

MFC 2

Qsmt dPsmt

Figure 6. Example CAL of the SMT.

Figure 7. Calibration curve for a typical CNC.

y = 2.953x - 3.14129N02, Bef Clng,

Diamonds

y = 3.261x - 4.92029N02 After Clng

Squares

y = 3.1716x - 4.3511

8

9

10

11

12

13

14

15

16

17

4.0 4.5 5.0 5.5 6.0 6.5

Qsm

t (

cc/m

in)

dPsmt (Volts)

Qsmt vs. dPsmt ALGR 02o16 CNC EFF 020305 007.xls

Triangles, 8FEB03

0.0

0.1

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0.8

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1.0

1.1

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1 10 100 1000

DE

TE

CT

ION

E

FF

Particle Diameter, Dp (nm)

DET EFF v. Dp, Q = 0.05CFM (1.4 L/m) LASEA AEROSOL SVCS, 07705--1535 EFF - Dp CNC2 MT.xls

[1-exp[-LN(2)*(X-3.8)/(6.0-3.8)]] Unity STD FUR STD NEB

Figure 8. Wiring diagram showing ability to control the MFC with either a potentiometer

or a computer generated programming signal.

Figure 9. Block diagram for no feedback version of the program.

Figure 10. Front panel of the non feed back version of the program.

Figure 11. Block diagram of the feed back version of the program.

Figure 12. Front panel of the feed back version of the program.

Figure 13. Sample data for the no feedback version.

Figure 14. Effects from manually changing Q1 through the LV program. Q1 was given a

short duration change and returned manually to its original value with the pot.

0

1

2

3

4

5

6

0

0.2

0.4

0.6

0.8

1

1.2

77720 77740 77760 77780 77800 77820 77840 77860

dP

smt

(V

olt

s)

Q1

(L/

m)

Time (SAM)

Q1 and dPsmt vs. Time Cptr controlled change in Q1 10505--2134 Data ALGR Illustr Eff.xlsx

Q1 dPsmt

Figure 15. Effects from giving Q2 a short duration change and then returning it to its

original value with the pot.

Figure 16. Response of system for computer control, with a feedback loop in the

program. The dPsp was given a step change and the Q1 changed accordingly to bring

dPsmt to close to the new dPsp.

FN: 10507 510—0825 Sem Proj ME240 YES.doc

-1.5

-1

-0.5

0

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78050 78100 78150 78200 78250 78300 78350

dP

smt

(V

olt

s)

Q2

(L/

m)

Time (SAM)

Q2 and dPsmt vs. Time Manually controlled change in Q2 10505--2134 Data ALGR Illustr Eff.xlsx

Q2 dPsmt

Q1 and dPsmt vs. Time

10506--2005 Var Par Cptr Ctrl.xls

0.0

0.2

0.4

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0.8

1.0

1.2

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71200 71250 71300 71350 71400 71450 71500 71550

Time (SAM)

Q1 (

L/m

) &

dP

sm

t (V

)

Q1 dPsmt