Experiments of a shock hitting a curtain of particles were conducted at the multiphase shock tube facility at Sandia National Laboratories. These are studied in this paper for quantifying the epistemic uncertainty in the experimental measurements due to processing via measurement models. Schlieren and X-ray imaging techniques were used to obtain the measurements that characterize the particle curtain with particle volume fraction and curtain edge locations. The epistemic uncertainties in the experimental setup and image processing methods were identified and measured. The effects of these uncertainties on the uncertainty in the extracted experimental measurements were quantified. The influence of the epistemic uncertainty was significantly higher than the experimental variability that has been previously considered as the most important uncertainty of experiments.

References

References
1.
Oberkampf
,
W. L.
, and
Trucano
,
T. G.
,
2002
, “
Verification and Validation in Computational Fluid Dynamics
,”
Prog. Aerosp. Sci.
,
38
(
3
), pp.
209
272
.
2.
Trucano
,
T. G.
,
Swiler
,
L. P.
,
Igusa
,
T.
,
Oberkampf
,
W. L.
, and
Pilch
,
M.
,
2006
, “
Calibration, Validation, and Sensitivity Analysis: What's What
,”
Reliab. Eng. Syst. Saf.
,
91
(
10–11
), pp.
1331
1357
.
3.
Schwer
,
L. E.
,
2006
, “
Guide for Verification and Validation in Computational Solid Mechanics
,”
American Society of Mechanical Engineering
,
New York
, Standard No. PTC 60/V&V 10.
4.
Oberkampf
,
W. L.
,
Trucano
,
T. G.
, and
Hirsch
,
C.
,
2004
, “
Verification, Validation, and Predictive Capability in Computational Engineering and Physics
,”
ASME Appl. Mech. Rev.
,
57
(
5
), pp.
345
384
.
5.
Roy
,
C. J.
, and
Oberkampf
,
W. L.
,
2011
, “
A Comprehensive Framework for Verification, Validation, and Uncertainty Quantification in Scientific Computing
,”
Comput. Methods Appl. Mech. Eng.
,
200
(
25–28
), pp.
2131
2144
.
6.
Oberkampf
,
W. L.
, and
Barone
,
M. F.
,
2006
, “
Measures of Agreement Between Computation and Experiment: Validation Metrics
,”
J. Comput. Phys.
,
217
(
1
), pp.
5
36
.
7.
Li
,
W.
,
Chen
,
W.
,
Jiang
,
Z.
,
Lu
,
Z.
, and
Liu
,
Y.
,
2014
, “
New Validation Metrics for Models With Multiple Correlated Responses
,”
Reliab. Eng. Syst. Saf.
,
127
, pp.
1
11
.
8.
Ferson
,
S.
,
Kreinovich
,
V.
,
Hajagos
,
J.
,
Oberkampf
,
W.
, and
Ginzburg
,
L.
,
2007
, “
Experimental Uncertainty Estimation and Statistics for Data Having Interval Uncertainty
,” Sandia National Laboratories, Albuquerque, NM, Report No. SAND2007-0939.
9.
Beresh
,
S. J.
,
2008
, “
Evaluation of PIV Uncertainties Using Multiple Configurations and Processing Techniques
,”
AIAA
Paper No. 2008-0239.https://www.osti.gov/servlets/purl/1146188
10.
Hughes
,
K. T.
,
Diggs
,
A.
,
Park
,
C.
,
Littrell
,
D.
,
Haftka
,
R. T.
,
Kim
,
N. H.
, and
Balachandar
,
S.
,
2018
, “
Simulation-Driven Experiments of Macroscale Explosive Dispersal of Particles
,”
AIAA
Paper No. 2018-1545.
11.
Thurber
,
M. C.
,
1999
, “
Acetone Laser-Induced Fluorescence for Temperature and Multiparameter Imaging in Gaseous Flows
,” Ph.D. thesis, Stanford University, Stanford, CA, p.
137
.
12.
Adrian
,
R. J.
, and
Westerweel
,
J.
,
2011
, “
Particle Image Velocimetry (No. 30)
,”
Cambridge University Press
,
Cambridge, UK
.
13.
Timmins
,
B. H.
,
Wilson
,
B. W.
,
Smith
,
B. L.
, and
Vlachos
,
P. P.
,
2012
, “
A Method for Automatic Estimation of Instantaneous Local Uncertainty in Particle Image Velocimetry Measurements
,”
Exp. Fluids
,
53
(
4
), pp.
1133
1147
.
14.
Hughes
,
K.
,
Park
,
C.
,
Haftka
,
R.
, and
Kim
,
N. H.
,
2017
, “
Forensic Uncertainty Quantification of Explosive Dispersal of Particles
,”
AIP Conference Proceedings 1979
, St. Louis, MI, July 9–14, p. 140001.
15.
Ling
,
Y.
,
Wagner
,
J. L.
,
Beresh
,
S. J.
,
Kearney
,
S. P.
, and
Balachandar
,
S.
,
2012
, “
Interaction of a Planar Shock Wave With a Dense Particle Curtain: Modeling and Experiments
,”
Phys. Fluids
,
24
(
11
), p.
113301
.
16.
Wagner
,
J. L.
,
Beresh
,
S. J.
,
Kearney
,
S. P.
,
Trott
,
W. M.
,
Castaneda
,
J. N.
,
Pruett
,
B. O.
, and
Baer
,
M. R.
,
2012
, “
A Multiphase Shock Tube for Shock Wave Interactions With Dense Particle Fields
,”
Exp. Fluids
,
52
(
6
), pp.
1507
1517
.
17.
Wagner
,
J. L.
,
Beresh
,
S. J.
,
Kearney
,
S. P.
,
Pruett
,
B. O.
, and
Wright
,
E. K.
,
2012
, “
Shock Tube Investigation of Quasi-Steady Drag in Shock-Particle Interactions
,”
Phys. Fluids
,
24
(
12
), p.
123301
.
18.
DeMauro
,
E. P.
,
Wagner
,
J. L.
,
Beresh
,
S. J.
, and
Farias
,
P. A.
,
2017
, “
Unsteady Drag Following Shock Wave Impingement on a Particle Curtain Measured Using Pulse-Burst PIV
,”
Phys. Rev. Fluids
,
2
(
6
), p.
064301
.
19.
Parmar
,
M.
,
Haselbacher
,
A.
, and
Balachandar
,
S.
,
2009
, “
Modeling of the Unsteady Force in Shock-Particle Interaction
,”
Shock Waves
,
19
(
4
), pp.
317
329
.
20.
Park
,
C.
,
Fernández-Godino
,
M. G.
,
Kim
,
N. H.
, and
Haftka
,
R. T.
,
2016
, “
Validation, Uncertainty Quantification and Uncertainty Reduction for a Shock Tube Simulation
,”
AIAA
Paper No. 2016-1192.
21.
Wagner
,
J. L.
,
Kearney
,
S. P.
,
Beresh
,
S. J.
,
DeMauro
,
E. P.
, and
Pruett
,
B. O.
,
2015
, “
Flash X-Ray Measurements on the Shock-Induced Dispersal of a Dense Particle Curtain
,”
Exp. Fluids
,
52
(
12
), p.
213
.https://www.osti.gov/pages/servlets/purl/1237675
22.
Linne
,
M.
,
2013
, “
Imaging in the Optically Dense Regions of a Spray: A Review of Developing Techniques
,”
Prog. Energy Combust. Sci.
,
39
(
5
), pp.
403
440
.
23.
Busch
,
K. W.
, and
Busch
,
M. A.
,
1999
, “
Introduction to Cavity-Ringdown Spectroscopy
,”
Cavity-Ringdown Spectroscopy—An Ultratrace-Absorption Measurement Technique
,
K. W.
Busch
, and
M. A.
Busch
, eds.,
ACS Publications
,
Washington, DC
, pp.
7
19
.
24.
MacPhee
,
A. G.
,
Tate
,
M. W.
,
Powell
,
C. F.
,
Yue
,
Y.
,
Renzi
,
M. J.
,
Ercan
,
A.
,
Narayanan
,
S.
,
Fontes
,
E.
,
Walther
,
J.
,
Schaller
,
J.
, and
Wang
,
J.
,
2002
, “
X-Ray Imaging of Shock Waves Generated by High-Pressure Fuel Sprays
,”
Science
,
295
(
5558
), pp.
1261
1263
.
25.
Park
,
C.
,
Nili
,
S.
,
Mathew
,
J. T.
,
Kim
,
N. H.
, and
Haftka
,
R. T.
,
2018
, “
Uncertainty Investigation for Shock Tube Simulation Error Quantification
,”
AIAA
Paper No. 2018-1662.
26.
Matsumura
,
T.
,
Haftka
,
R. T.
, and
Kim
,
N. H.
,
2015
, “
Accurate Predictions From Noisy Data: Replication Versus Exploration With Applications to Structural Failure
,”
Struct. Multidiscip. Optim.
,
51
(
1
), pp.
23
40
.
27.
Kennedy
,
M. C.
, and
O'Hagan
,
A.
,
2001
, “
Bayesian Calibration of Computer Models
,”
J. R. Stat. Soc.: Ser. B, Stat. Methodol.
,
63
(
3
), pp.
425
464
.
28.
Rasmussen
,
C. E.
,
2004
, “
Gaussian Processes in Machine Learning
,”
Advanced Lectures on Machine Learning
,
Springer
,
Berlin
, pp.
63
71
.
You do not currently have access to this content.