Research Papers

A Framework for Test-to-Test Averaging and Representation of Asynchronous Spatial Measurements

[+] Author and Article Information
Anthony M. Ferrar

B and E Applied Research and Science
Nuclear Engineering Program,
University of Florida,
Gainesville, FL 32611
e-mail: ferrar@ufl.edu

Manuscript received November 17, 2015; final manuscript received June 21, 2016; published online July 15, 2016. Assoc. Editor: Luis Eca.

J. Verif. Valid. Uncert 1(3), 031003 (Jul 15, 2016) (7 pages) Paper No: VVUQ-15-1054; doi: 10.1115/1.4033993 History: Received November 17, 2015; Revised June 21, 2016

Many experimental programs utilize traversing probes to measure spatial profiles of a variable. These measurements are taken asynchronously because the probe measures one location at a time. During an experiment of this nature, the test conditions are held constant by experimental controls. However, all control systems operate within limits rather than maintaining a truly constant condition. Results of these tests can be contaminated by variations in test conditions depending on the sensitivity of the dependent variable. In addition, spatial trends can be altered by probe positioning uncertainty. This paper discusses these two error sources and develops an experimental framework that alleviates their impact on results. The goals are to assess the effects of measurement position uncertainty and to obtain scientifically useful results in experiments whose control systems allow test condition variations that result in measurable changes in the dependent variables.

Copyright © 2016 by ASME
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Ferrar, A. M. , 2015, “ Measurement and Uncertainty Analysis of Transonic Fan Response to Total Pressure Inlet Distortion,” Ph.D. thesis, Virginia Polytechnic Institute and State University, Blacksburg, VA. https://vtechworks.lib.vt.edu/handle/10919/51747
Gunn, E. , Tooze, S. , Hall, C. , and Colin, Y. , 2013, “ An Experimental Study of Loss Sources in a Fan Operating With Continuous Inlet Station Pressure Distortion,” ASME J. Turbomach., 135(5), p. 051002. [CrossRef]
Coleman, H. , and Steele, G. , 2009, Experimentation, Validation, and Uncertainty Analysis for Engineers, 3rd ed., Wiley, Hoboken, NJ.
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Brodlie, K. , Osorio, R. A. , and Lopes, A. , 2010, “ A Review of Uncertainty in Data Visualization,” Expanding the Frontiers of Visual Analytics and Visualization, Springer, New York.
Ferrar, A. , 2016, “ Examining Sample Rate, Sample Time, and Test Replication for Reducing Uncertainty in Steady Timewise Experiments,” ASCE-ASME J. Risk Uncertainty Eng. Syst., Part B (accepted).


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Fig. 4

Inlet and outlet total pressure profiles from the case study (a) fan inlet total pressure profile, measured by a fixed rake and (b) fan rotor outlet total pressure profile, measured by a traversing total pressure probe

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Fig. 3

Cutaway view of the Virginia Tech TurboLab Engine Distortion Test Facility. Flow from left to right.

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Fig. 2

Effects of probe position uncertainty on spatial trends. The probe position is known within limits. Depending on the true probe position, a different value from the spatial trend may be measured and assigned to the intended probe position (a) the range of possible measured values within the range of probe position uncertainty. The dashed lines represent the limits of possible probe positions. Any value between these limits may be measured and assigned to the intended probe position and (b) changes in spatial trends caused by probe position variations. The dashed lines represent the trends corresponding to the probe position limits from Fig. 2(a).

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Fig. 1

Comparison of asynchronous plunged measurements and simultaneous rake measurements

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Fig. 5

Fan speed variations from the case study. These variations were caused by the precision limits of the fan speed control system. (a) Fan speed for each test replication at each measurement location. Fan speed was a controlled independent variable of the case study. (b) Populations of test conditions from replications at two selected spatial locations of the case study. These are the points in Fig. 5(a) from two (R, Θ) combinations. (c) Local test-to-test average fan speed deviation computed by Eq. (4). These values are the differences between the “Average for Location” (RPM¯i,j) and “Overall Average” (RPM¯) illustrated in Fig. 5(b). These deviations are represented with error bars corresponding to the uncertainty associated with the speed measurements and control, which were dominated by the test-to-test scatter in average fan speed illustrated in Fig. 5(a).

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Fig. 6

Total pressure as a function of fan speed at each measurement radius

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Fig. 7

Uncertainty contributions for the total pressure results from the case study. Each component corresponds to a term in Eq. (7). When the local test speed deviation (ΔRPM)i,j is large, it contributes a significant portion of the overall uncertainty.

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Fig. 8

Total pressure results at a fixed measurement radius, with uncertainty compared to speed deviation. When the speed deviation for a location is large, the uncertainty increases.



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