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Research Papers

Toward the Development of a Verification, Validation, and Uncertainty Quantification Framework for Granular and Multiphase Flows—Part 1: Screening Study and Sensitivity Analysis

[+] Author and Article Information
Aytekin Gel

National Energy Technology Laboratory (NETL),
Morgantown, WV 26507;
ALPEMI Consulting, L.L.C.,
Phoenix, AZ 85284
e-mail: aike@alpemi.com

Avinash Vaidheeswaran

National Energy Technology Laboratory (NETL),
Morgantown, WV 26507;
West Virginia University Research Corporation,
Morgantown, WV 26506
e-mail: avinash.vaidheeswaran@netl.doe.gov

Jordan Musser

National Energy Technology Laboratory (NETL),
Morgantown, WV 26507
e-mail: jordan.musser@netl.doe.gov

Charles H. Tong

Center for Applied Scientific Computing (CASC),
Lawrence Livermore National Laboratory (LLNL),
Livermore, CA 94550
e-mail: tong10@llnl.gov

1Corresponding author.

Manuscript received October 3, 2017; final manuscript received October 12, 2018; published online November 22, 2018. Assoc. Editor: Ashley F. Emery. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited.

J. Verif. Valid. Uncert 3(3), 031001 (Nov 22, 2018) (12 pages) Paper No: VVUQ-17-1032; doi: 10.1115/1.4041745 History: Received October 03, 2017; Revised October 12, 2018

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.

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References

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. [CrossRef]
Abani, N. , and Ghoniem, A. F. , 2013, “ Large Eddy Simulations of Coal Gasification in an Entrained Flow Gasifier,” Fuel, 104, pp. 664–680. [CrossRef]
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. [CrossRef]
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. [CrossRef]
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.
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.
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
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.
ASME Committee PTC-61, 2009, “ ASME Guide on Verification and Validation in Computational Fluid Dynamics and Heat Transfer,” ANSI Standard V&V 20.
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.
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.
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. [CrossRef]
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.
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
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.
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
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
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
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. [CrossRef]
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. [CrossRef]
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. [CrossRef]
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. [CrossRef]
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
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. [CrossRef]
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.
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.
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.
Zou, L. , Zhao, H. , and Zhang, H. , 2017, “ Numerical Uncertainties vs. Model Uncertainties in Two-Phase Flow Simulations,” ANS Annual Meeting, San Francisco, CA.
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.
Roache, P. J. , 1997, “ Quantification of Uncertainty in Computational Fluid Dynamics,” Annu. Rev. Fluid Mech., 29(1), pp. 123–160. [CrossRef]
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. [CrossRef]
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.
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.
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. [CrossRef]
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.
Evans, J. R. , and Lindsay, W. M. , 1992, An Introduction to Six Sigma and Process Improvement, Cengage Learning, Boston, MA.
Drescher, A. , 1992, “ On the Criteria for Mass Flow in Hoppers,” Powder Technol., 73(3), pp. 251–260. [CrossRef]
Nedderman, R. , 1982, Statics and Kinematics of Granular Materials, Cambridge University Press, Cambridge, UK.
Morris, M. D. , 1991, “ Factorial Sampling Plans for Preliminary Computational Experiments,” Technometrics, 21(2), pp. 239–245.
Tong, C. , 2015, “ PSUADE Reference Manual (Version 1.7),” Lawrence Livermore National Laboratory, Livermore, CA.
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
Ba, S. , Myers, W. R. , and Brenneman, W. A. , 2015, “ Optimal Sliced Latin Hypercube Designs,” Technometrics, 57(4), pp. 479–487. [CrossRef]

Figures

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Fig. 6

Results of subject matter expert survey in identifying control variables (N/R implies no response)

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Fig. 7

Results of subject matter expert survey in identifying held-constant factors

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Fig. 5

Results of subject matter expert survey in identifying control variables

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Fig. 4

Results of subject matter expert survey in identifying response variables (quantities of interest)

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Fig. 2

Phase 2(b) VVUQ flow chart

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Fig. 1

Verification, validation, and uncertainty quantification flow chart phases 1 and 2 (a)

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Fig. 8

Scatter plot for screening study

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Fig. 9

Method of Morris-based analysis results from the screening study simulations as number of samples increased from 44 to 110: (a) using the first 44 samples (N = 44), (b) using the first 55 samples (N = 55), (c) using the first 77 samples (N = 77), and (d) using all 110 samples (N = 110)

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Fig. 10

Results of OLH sampling based simulations: (a) OLH with n = 40 samples and (b) OLH with n = 80 samples

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Fig. 11

Contour plot of the surrogate model constructed from 40 samples for the discharge flow rate shown as a function of particle–particle coefficient of friction and particle–particle coefficient of restitution, where the remaining input parameters are set at their nominal values

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Fig. 12

Cross-validation error assessment plots: (a) histogram of errors and (b) comparison of predictions from the surrogate model and actual MFIX-DEM results with 40 samples

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Fig. 13

Global sensitivity results based on n = 40 samples for first quantity of interest, discharge rate: (a) Sobol' main effect sensitivities, (b) Sobol' total indices, and (c) Sobol' two-way sensitivities for interaction of input parameters

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Fig. 14

Global sensitivity results based on n = 40 samples for second quantity of interest, angle of repose: (a) Sobol' main effect sensitivities, (b) Sobol' total indices, and (c) Sobol' two-way sensitivities for interaction of input parameters

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