1. ME 322: Instrumentation Lecture 41
April 29, 2016
Professor Miles Greiner
Review Labs 11 and 12

2. Announcements/Reminders
Cancel HW 14
Supervised Open-Lab Periods
Saturday, Sunday 1-6 PM
Please pick up old homework during the open lab times
Lab-in-a-box (DeLaMare Library)
Lab Practicum Finals Start Monday
Guidelines, Schedule
Monday
Answer questions
Reviewing course objectives and asking for feedback
Allow time to complete course evaluation at

3. Opportunities
Summer position at the Nevada National Security Site (NNSS)
ME 322 Lab assistant
Please let me know if you’re interested

4. Lab 11 Unsteady Speed in a Karman Vortex Street
Nomenclature
U = Air speed, VCTA = Constant temperature anemometer voltage
Two steps
Statically-calibrate hot film CTA using a Pitot probe
Find frequency, fP with largest URMS downstream from a cylinder of diameter D for a range of air speeds U
Compare to expectations (StD = DfP /U = )

5. Setup Measure PATM, TATM, and cylinder D Find air m from text
myDAQ
Variable Speed
Blower
Hot Film
Probe
VCTA
Barometer
PATM
TATM
Plexiglas
Tube
CTA
DTube
Cylinder, D
Pitot-Static Probe
Static
Total PP - +
3 in WC IP
Measure PATM, TATM, and cylinder D
Find air m from text
A.J. Wheeler and A. R. Ganji, Introduction to Engineering Experimentation, 2nd Edition, Pearson Prentice Hall, 2004, p. 430
Tunnel Air Density
𝜌= 𝑃 𝐴𝑇𝑀 + 𝑃 𝐺𝑎𝑔𝑒 𝑅 𝐴𝑖𝑟 𝑇 𝐴𝑇𝑀 =𝑐𝑜𝑛𝑠𝑡𝑎𝑛𝑡
𝑅 𝐴𝑖𝑟 =0.287 𝑘𝑃𝑎 𝑚 3 𝑘𝑔 𝐾

6. Hints When calibrating, Do not center probe behind cylinder
Read IP visually while clicking Run on VI to get simultaneous measurement of VCTA
Some people are using DVM to measure VCTA
Do not center probe behind cylinder
Use 1/8 inch cylinder (closer to hot film)
May help to not use auto-scale for URMS.
Low frequency signals can be large and swamp the Karman Vortex oscillatory amplitude

7. Calibration Calculations
𝑆 𝑈 , 𝑉 𝐶𝑇𝐴 2
Based on analysis we expect
𝑉 𝐶𝑇𝐴 2 =𝑎 𝑈 +𝑏
𝑈=𝐶 2 𝑃 𝑃 𝜌 𝐴𝑖𝑟 =1 2 𝜌 𝑊 𝑔𝐹𝑆 𝐼 𝑃 −4𝑚𝐴 16𝑚𝐴 𝜌 𝐴𝑖𝑟
Need to adjust transmitter current to be 4 mA when blower is off, or use actual current with no wind (don’t adjust span)
𝜌 𝑊 =998.7 𝑘𝑔 𝑚 3
𝐹𝑆= 3 𝑖𝑛𝑐ℎ 𝑊𝐶 𝑐𝑚 𝑖𝑛𝑐ℎ 1 𝑚 100 𝑐𝑚
For: 𝑉 𝐶𝑇𝐴 2 =𝑎 𝑈 +𝑏, find:
a and b
𝑠 𝑉 𝐶𝑇𝐴 2 , 𝑈 = 𝑎 𝑈 𝑖 +𝑏 − 𝑉 𝐶𝑇𝐴 2 𝑖 𝑛−2
𝑠 𝑈 , 𝑉 𝐶𝑇𝐴 2 = 𝑠 𝑉 𝐶𝑇𝐴 2 , 𝑈 𝑎
𝑤 𝑈 =2 𝑈 𝑠 𝑈 , 𝑉 𝐶𝑇𝐴 (68%)
𝑆 𝑉 𝐶𝑇𝐴 2 , 𝑈

8. Hot Film System Calibration
The fit equation 𝑉 𝐶𝑇𝐴 2 =𝑎 𝑈 +𝑏 appears to be appropriate for these data.
To use calibration : 𝑈= 𝑉 𝐶𝑇𝐴 2 −𝑏 𝑎 2 (program into labview)

9. Need mean voltage for calibration
Fig. 2 VI Block Diagram
Mean Voltage
Starting point VI
Need mean voltage for calibration
Need mean speed for Strouhal and Reynolds numbers

10. Fig. 1 VI Front Panel Don’t use frequency of Maximum
Use “eyeball” technique

11. Unsteady Speed Downstream of a Cylinder
When the cylinder is removed the speed is relatively constant
Downstream of the cylinder
The average speed is lower compared to no cylinder
There are oscillations with a broadband of frequencies
You don’t need to plot this in the report

12. Fig. 4 Spectral Content in Wake for Highest and Lowest Wind Speed
(a) Lowest Speed
URMS
[m/s]
fp = 751 Hz
(b) Highest Speed
URMS
[m/s]
fp = 2600 Hz
Hint: Don’t use auto-scale for URMS
The sampling frequency and period are fS = 48,000 Hz and TT = 1 sec.
The minimum and maximum detectable finite frequencies are 1 and 24,000 Hz
don’t show the highest frequencies.
It is not “straightforward” to distinguish fP from this data. Its uncertainty is wfp ~ 50 Hz.

13. Dimensionless Frequency and Uncertainty
UA from LabVIEW VI
𝑤 𝑈 =2 𝑈 𝑠 𝑈 , 𝑉 𝐶𝑇𝐴 (68%)
fP from LabVIEW VI plot
𝑤 𝑓 𝑃 = ½(1/tT) or eyeball uncertainty
Re = UADr/m (power product)
𝑤 𝑅𝑒 𝑅𝑒 2 = 𝑤 𝑈 𝐴 𝑈 𝐴 𝑤 𝐷 𝐷 𝑤 𝜌 𝜌 𝑤 𝜇 𝜇 2
StD = DfP/UA (power product)
𝑤 StD StD 2 = − 𝑤 𝑈 𝐴 𝑈 𝐴 𝑤 𝐷 𝐷 𝑤 𝑓 𝑃 𝑓 𝑃 2

14. Fig. 5 Strouhal versus Reynolds
The reference value is from A.J. Wheeler and A.R. Ganji, Introduction to Engineering Experimentation, 2nd Edition, Pearson Prentice Hall, 2004, p. 337.
Four of the six Strouhal numbers are within the expected range.

15. Process Sample Data

16. Lab 12 Setup
Measure beaker water temperature using a thermocouple/conditioner/myDAQ/VI
Use myDAQ analog output (AO) connected to a digital relay to turn heater on/off, and control the water temperature
Use Fraction-of-Time-On (FTO) to control heater power

17. Lab 12 Integral Control Block Diagram

18. Figure 1 VI Front Panel
Plots help the user monitor the time-dependent measured and set-point temperatures T and TSP, temperature error T–TSP, and control parameters

19. Hint
Use Control-U to make wiring easier

20. VI Components Display using slide indicators
Input tCycle, fSampling, TSP, DT, and DTi
Measure and display temperature T
Plot T, T-TSP (error), TSP, TSP-DT, and log(DTi)
Increase chart history length, auto-scale-x-axis
Write to Excel file (next available file name, one time column, no headers)
Calculate
𝐹𝑇𝑂𝑝= 𝑇 𝑆𝑃 −𝑇 𝐷𝑇 and
𝐹𝑇𝑂𝑖= 𝑖 𝑡 𝑇 𝑆𝑃 −𝑇 𝐷𝑇𝑖 (shift register),
Limit FTO = FTOp + FTOi to >0 and <1
Display using slide indicators
Write data to analog output within a stacked-sequence loop (millisecond wait)

21. Figure 3 Measured, Set-Point, Lower-Control Temperatures and DTi versus Time
Data was acquired for 40 minutes with a set-point temperature of 85°C.
The time-dependent thermocouple temperature is shown with different values of the control parameters DT and DTi.
Proportional control is off when DT = 0
Integral control is effectively off when DTi = 107 [10log(DTI) = 70]

22. Figure 4 Temperature Error, DT and DTi versus Time
The temperature oscillates for DT = 0, 5, and 15°C, but was nearly steady for DT = 20°C.
DTi was set to 100 from roughly t = 25 to 30 minutes, but the system was overly responsive, so it was increased to 1000.
The controlled-system behavior depends on the relative locations of the heater, thermocouple, and side of the beaker, and the amount of water in the beaker. These parameters were not controlled during the experiment.

23. Table 1 Controller Performance Parameters
This table summarize the time periods when the system exhibits steady state behaviors for each DT and DTi.
During each steady state period
TA is the average temperature
TA – TSP is an indication of the average controller error.
The Root-Mean-Squared temperature TRMS is an indication of controller unsteadiness

24. TRMS is and indication of thermocouple temperature unsteadiness
Figure 5 Controller Unsteadiness versus Proportionality Increment and Set-Point Temperature
TRMS is and indication of thermocouple temperature unsteadiness
Unsteadiness decreases as DT increases, and is not strongly affected by DTi.

25. The average temperature error
Figure 6 Average Temperature Error versus Set-Point Temperature and Proportionality Increment
The average temperature error
Is positive for DT = 0, but decreases and becomes negative as DT increases.
Is significantly improved by Integral control.

26. Process Sample Data Add time scale in minutes Figure 3 Figure 4
Add time scale in minutes
Calculate difference, general format, times 24*60
Figure 3
Plot T, TSP, DT and 10log(DTi) versus time
Figure 4
Plot T-TSP, -DT, 10log(DTi) and 0 versus time
Table 1
Determine time periods when behavior reaches “steady state,” and find 𝑇 𝐴 = 𝑇 and 𝑇 𝑅𝑀𝑆 = 𝜎 𝑇 during those times
Figure 5
Plot 𝑇 𝑅𝑀𝑆 versus DT and DTi
Figure 6
Plot 𝑇 𝐴 − 𝑇 𝑆𝑃 versus DT and DTi

28. VI Block Diagram Modify proportional VI

29. Figure 1 VI Front Panel
Plots help the user monitor the measure and set-point temperatures T and TSP, temperature error T–TSP, and control parameters