Establishing the credibility of computational fluid dynamics (CFD) models for multiphase flow applications is increasingly becoming a mainstream requirement. However, the established verification and validation (V&V) Standards have been primarily demonstrated for single phase flow applications. Studies to address their applicability for multiphase flows have been limited. Hence, their application may not be trivial and require a thorough investigation. We propose to adopt the ASME V&V 20 Standard and explore its applicability for multiphase flows through several extensions by introducing some of the best practices. In the current study, the proposed verification, validation, and uncertainty quantification (VVUQ) framework is presented and its preliminary application is demonstrated using the simulation of granular discharge through a conical hopper commonly employed in several industrial processes. As part of the proposed extensions to the V&V methodology, a detailed survey of subject matter experts including CFD modelers and experimentalists was conducted. The results from the survey highlighted the need for a more quantitative assessment of importance ranking in addition to a sensitivity study before embarking on simulation and experimental campaigns. Hence, a screening study followed by a global sensitivity was performed to identify the most influential parameters for the CFD simulation as the first phase of the process, which is presented in this paper. The results show that particle–particle coefficients of restitution and friction are the most important parameters for the granular discharge flow problem chosen for demonstration of the process. The identification of these parameters is important to determine their effect on the quantities of interest and improve the confidence level in numerical predictions.

References

References
1.
Slezak
,
A.
,
Kuhlman
,
J. M.
,
Shadle
,
L. J.
,
Spenik
,
J.
, and
Shi
,
S.
,
2010
, “
CFD Simulation of Entrained-Flow Coal Gasification: Coal Particle Density/Sizefraction Effects
,”
Powder Technol.
,
203
(
1
), pp.
98
108
.
2.
Abani
,
N.
, and
Ghoniem
,
A. F.
,
2013
, “
Large Eddy Simulations of Coal Gasification in an Entrained Flow Gasifier
,”
Fuel
,
104
, pp.
664
680
.
3.
Brown
,
G.
, and
Fletcher
,
D.
,
2005
, “
CFD Prediction of Odour Dispersion and Plume Visibility for Alumina Refinery Calciner Stacks
,”
Process Saf. Environ. Prot.
,
83
(
3
), pp.
231
241
.
4.
Mikulčić
,
H.
,
Vujanović
,
M.
,
Fidaros
,
D. K.
,
Priesching
,
P.
,
Minić
,
I.
,
Tatschl
,
R.
,
Duić
,
N.
, and
Stefanović
,
G.
,
2012
, “
The Application of CFD Modelling to Support the Reduction of CO2 Emissions in Cement Industry
,”
Energy
,
45
(
1
), pp.
464
473
.
5.
Rosendall
,
B.
,
Barringer
,
C.
,
Wen
,
F.
, and
Knight
,
K. J.
,
2006
, “
Validating CFD Models of Multiphase Mixing in the Waste Treatment Plant at the Hanford Site
,”
ASME
Paper No. ICONE14-89744.
6.
Wells
,
B. E.
,
Bamberger
,
J. A.
,
Recknagle
,
K. P.
,
Enderlin
,
C. W.
,
Minette
,
M. J.
, and
Holton
,
L. K.
,
2015
, “
Applying Hanford Tank Mixing Data to Define Pulse Jet Mixer Operation
,”
ASME
Paper No. IMECE2015-50712
.
7.
AIAA,
1998
, “
Guide for the Verification and Validation of Computational Fluid Dynamics Simulations
,”
AIAA
Paper No. G-077-1998
.https://arc.aiaa.org/doi/book/10.2514/4.472855
8.
Coleman
,
H. W.
, and
Steele
,
W. G.
,
2008
, “
An Overview of ASME V&V 20: Standard for Verification and Validation in Computational Fluid Dynamics and Heat Transfer
,”
Eighth World Congress on Computational Mechanics (WCCM8), Fifth European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008)
, Venice, Italy, June 30–July 5.
9.
ASME Committee PTC-61,
2009
, “
ASME Guide on Verification and Validation in Computational Fluid Dynamics and Heat Transfer
,” ANSI Standard V&V 20.
10.
Sanders
,
P.
,
1996
, “
DoD Modeling and Simulation (M&S) Verification, Validation, and Accreditation (VV&A)
,” Office of the Under Secretary of Defense (Acquisition and Technology), Washington, DC, Standard No.
5000.61
.
11.
Shi
,
P.
,
Liu
,
F.
, and
Yang
,
M.
,
2009
, “
Quantify Simulation Verification and Validation
,”
11th IEEE International Conference on Computer Modelling and Simulation
(
UKSIM'09
), Cambridge, UK, Mar. 25–27, pp.
123
128
.
12.
Schwer
,
L. E.
,
2007
, “
An Overview of the PTC 60/V&V 10: Guide for Verification and Validation in Computational Solid Mechanics
,”
Eng. Comput.
,
23
(
4
), pp.
245
252
.
13.
ASME
,
2006
, “
Guide for Verification and Validation in Computational Solid Mechanics
,” American Society of Mechanical Engineers, New York, Standard No. ASME V&V 10-2006.
14.
NASA
,
2006
, “
Standard for Models and Simulations
,” National Aeronautics and Space Administration (NASA), Washington, DC, Standard No.
NASA-STD-7009
.https://standards.nasa.gov/standard/nasa/nasa-std-7009
15.
Harvego
,
E. A.
,
Schultz
,
R. R.
, and
Crane
,
R. L.
,
2010
, “
Development of a Standard for Verification and Validation of Software Used to Calculate Nuclear System Thermal Fluids Behavior
,”
ASME
Paper No. ICONE18-30243.
16.
Pace
,
D. K.
,
2004
, “
Modeling and Simulation Verification and Validation Challenges
,”
Johns Hopkins APL Tech. Dig.
,
25
(
2
), pp.
163
172
.http://www.jhuapl.edu/techdigest/TD/td2502/Pace.pdf
17.
ASME
,
2016
, “
Subject Matter Experts Wanted for ASME's Advanced Manufacturing Standards Committee
,” American Society of Mechanical Engineers, New York, accessed Oct. 29, 2018, https://www.asme.org/about-asme/standards/standards-certification-update/subject-matter-experts-wanted-for-asme%E2%80%99s-advanced
18.
ASME
,
2016
, “
Ongoing Development of Standards for Advanced Manufacturing
,” American Society of Mechanical Engineers, New York, accessed Oct. 29, 2018, https://www.asme.org/about-asme/standards/standards-certification-update/ongoing-development-standards-advanced
19.
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
.
20.
Veluri
,
S. P.
,
Roy
,
C. J.
, and
Luke
,
E. A.
,
2012
, “
Comprehensive Code Verification Techniques for Finite Volume CFD Codes
,”
Comput. Fluids
,
70
, pp.
59
72
.
21.
Grace
,
J. R.
, and
Taghipour
,
F.
,
2004
, “
Verification and Validation of CFD Models and Dynamic Similarity for Fluidized Beds
,”
Powder Technol.
,
139
(
2
), pp.
99
110
.
22.
Gel
,
A.
,
Li
,
T.
,
Gopalan
,
B.
,
Shahnam
,
M.
, and
Syamlal
,
M.
,
2013
, “
Validation and Uncertainty Quantification of a Multiphase Computational Fluid Dynamics Model
,”
Ind. Eng. Chem. Res.
,
52
(
33
), pp.
11424
11435
.
23.
NETL Multiphase Flow Science
,
2016
, “
MFIX Software Suite
,” National Energy Technology Laboratory of U.S. Department of Energy, Morgantown, WV, accessed Oct. 29, 2018, http://mfix.netl.doe.gov
24.
Gel
,
A.
,
Shahnam
,
M.
, and
Subramaniyan
,
A. K.
,
2017
, “
Quantifying Uncertainty of a Reacting Multiphase Flow in a Bench-Scale Fluidized Bed Gasifier: A Bayesian Approach
,”
Powder Technol.
,
311
, pp.
484
495
.
25.
Gel
,
A.
,
Shahnam
,
M.
,
Musser
,
J.
,
Subramaniyan
,
A. K.
, and
Dietiker
,
J.-F.
,
2016
, “
Non-Intrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized Bed Gasifier
,”
Ind. Eng. Chem. Res.
,
55
(48), pp. 12477–12490.
26.
Shahnam
,
M.
,
Gel
,
A.
,
Dietiker
,
J.-F.
,
Subramaniyan
,
A. K.
, and
Musser
,
J.
,
2016
, “
The Effect of Grid Resolution and Reaction Models in Simulation of a Fluidized Bed Gasifier Through Non-intrusive Uncertainty Quantification Techniques
,”
ASME J. Verif. Valid. Uncertainty Quantif.
,
1
(4), p. 041004.
27.
Syamlal
,
M.
,
Celik
,
I.
, and
Benyahia
,
S.
,
2017
, “
Quantifying the Uncertainty Introduced by Discretization and Time-Averaging in Two-Fluid Model Predictions
,”
AIChE J.
,
63
(12), pp. 5343–5360.
28.
Zou
,
L.
,
Zhao
,
H.
, and
Zhang
,
H.
,
2017
, “
Numerical Uncertainties vs. Model Uncertainties in Two-Phase Flow Simulations
,”
ANS Annual Meeting
, San Francisco, CA.
29.
Vaidheeswaran
,
A.
,
Gel
,
A.
,
Musser
,
J.
,
Rogers
,
W. A.
, and
Shahnam
,
M.
,
2017
, “
Development of Verification, Validation and Uncertainty Quantification Roadmap With Systematic Set of Validation Experiments and Simulation Campaign
,”
ASME Verification and Validation Symposium
, May 3–5.
30.
Roache
,
P. J.
,
1997
, “
Quantification of Uncertainty in Computational Fluid Dynamics
,”
Annu. Rev. Fluid Mech.
,
29
(
1
), pp.
123
160
.
31.
Choudhary
,
A.
,
Roy
,
C. J.
,
Dietiker
,
J.-F.
,
Shahnam
,
M.
,
Garg
,
R.
, and
Musser
,
J.
,
2016
, “
Code Verification for Multiphase Flows Using the Method of Manufactured Solutions
,”
Int. J. Multiphase Flow
,
80
, pp.
150
163
.
32.
Musser
,
J.
,
Vaidheeswaran
,
A.
, and
Clarke
,
M. A.
, eds.,
MFIX Documentation Volume 3: Verification and Validation Manual
(NETL Technical Report Series), 2nd ed., U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV.
33.
Trucano
,
T. G.
, and
Moya
,
J. L.
,
1999
, “
Guidelines for Sandia ASCI Verification and Validation Plans-Content and Format: Version 1.0
,” Sandia National Labs, Albuquerque, NM, Report No. SAND2000-3101.
34.
Wilson
,
G. E.
, and
Boyack
,
B. E.
,
1998
, “
The Role of the PIRT Process in Experiments, Code Development and Code Applications Associated With Reactor Safety Analysis
,”
Nucl. Eng. Des.
,
186
(
1–2
), pp.
23
37
.
35.
Nowlen
,
S. P.
,
Olivier
,
T. J.
,
Dreisbach
,
J.
, and
Salley
,
M. H.
,
2008
, “
A Phenomena Identification and Ranking Table (PIRT) Exercise for Nuclear Power Plant Fire Model Applications
,” Sandia National Laboratory (SNL-NM), Albuquerque, NM, Report No. NUREG/CR-6978.
36.
Evans
,
J. R.
, and
Lindsay
,
W. M.
,
1992
,
An Introduction to Six Sigma and Process Improvement
,
Cengage Learning
, Boston, MA.
37.
Drescher
,
A.
,
1992
, “
On the Criteria for Mass Flow in Hoppers
,”
Powder Technol.
,
73
(
3
), pp.
251
260
.
38.
Nedderman
,
R.
,
1982
,
Statics and Kinematics of Granular Materials
,
Cambridge University Press
, Cambridge, UK.
39.
Morris
,
M. D.
,
1991
, “
Factorial Sampling Plans for Preliminary Computational Experiments
,”
Technometrics
,
21
(
2
), pp.
239
245
.
40.
Tong
,
C.
,
2015
, “
PSUADE Reference Manual (Version 1.7)
,” Lawrence Livermore National Laboratory, Livermore, CA.
41.
NETL, 2018, “
MFiX User Manual 2018
,” National Energy Technology Laboratory, Morgantown, WV, accessed Aug. 13, 2018, https://mfix.netl.doe.gov/doc/mfix/18.1.1/user_manual/index.html
42.
Ba
,
S.
,
Myers
,
W. R.
, and
Brenneman
,
W. A.
,
2015
, “
Optimal Sliced Latin Hypercube Designs
,”
Technometrics
,
57
(
4
), pp.
479
487
.
You do not currently have access to this content.