The Virtual Environment for Reactor Applications (VERA): Design and architecture☆

VERA, the Virtual Environment for Reactor Applications, is the system of physics capabilities being developed and deployed by the Consortium for Advanced Simulation of Light Water Reactors (CASL). CASL was established for the modeling and simulation of commercial nuclear reactors. VERA consists of integrating and interfacing software together with a suite of physics components adapted and/or refactored to simulate relevant physical phenomena in a coupled manner. VERA also includes the software development environment and computational infrastructure needed for these components to be effectively used. We describe the architecture of VERA from both software and numerical perspectives, along with the goals and constraints that drove major design decisions, and their implications. We explain why VERA is an environment rather than a framework or toolkit, why these distinctions are relevant (particularly for coupled physics applications), and provide an overview of results that demonstrate the use of VERA tools for a variety of challenging applications within the nuclear industry.

[1]  Emil M. Constantinescu,et al.  Multiphysics simulations , 2013, HiPC 2013.

[2]  Noel Belcourt,et al.  A theory manual for multi-physics code coupling in LIME. , 2011 .

[3]  D. Benson An efficient, accurate, simple ALE method for nonlinear finite element programs , 1989 .

[4]  Thomas J. Downar,et al.  CASL multiphysics modeling of crud deposition in PWRS , 2013 .

[5]  Bobby Philip,et al.  A parallel multi-domain solution methodology applied to nonlinear thermal transport problems in nuclear fuel pins , 2014, J. Comput. Phys..

[6]  Tara M. Pandya,et al.  Hot zero power reactor calculations using the Insilico code , 2016, J. Comput. Phys..

[7]  Brendan Kochunas,et al.  Parallel 3-D method of characteristics in MPACT , 2013 .

[8]  Benjamin Collins,et al.  Analysis of the BEAVRS Benchmark using MPACT , 2015 .

[9]  Tara M. Pandya,et al.  Implementation, capabilities, and benchmarking of Shift, a massively parallel Monte Carlo radiation transport code , 2016, J. Comput. Phys..

[10]  Robert D. Falgout,et al.  The Design and Implementation of hypre, a Library of Parallel High Performance Preconditioners , 2006 .

[11]  John N. Shadid,et al.  Stabilized FE simulation of prototype thermal-hydraulics problems with integrated adjoint-based capabilities , 2016, J. Comput. Phys..

[12]  John N. Shadid,et al.  Reactor Core Sub-Assembly Simulations Using a Stabilized Finite Element Method. , 2011 .

[13]  Rodney Cannon Schmidt,et al.  An approach for coupled-code multiphysics core simulations from a common input , 2015 .

[14]  J. Hyvärinen,et al.  An Arbitrary Lagrangian-Eulerian finite element method , 1998 .

[15]  Ted Belytschko,et al.  An arbitrary Lagrangian-Eulerian finite element method for path-dependent materials , 1986 .

[16]  David Andrs,et al.  Multidimensional multiphysics simulation of nuclear fuel behavior , 2012 .

[17]  Alan K. Stagg,et al.  A hybrid incremental projection method for thermal-hydraulics applications , 2016, J. Comput. Phys..

[18]  Anders Logg,et al.  Automated Solution of Differential Equations by the Finite Element Method: The FEniCS Book , 2012 .

[19]  Tara M. Pandya,et al.  Shift: A Massively Parallel Monte Carlo Radiation Transport Package , 2015 .

[20]  Roger P. Pawlowski,et al.  THE DATA TRANSFER KIT: A GEOMETRIC RENDEZVOUS-BASED TOOL FOR MULTIPHYSICS DATA TRANSFER. , 2013 .

[21]  Rodney Cannon Schmidt,et al.  An introduction to LIME 1.0 and its use in coupling codes for multiphysics simulations. , 2011 .

[22]  Timothy J. Tautges,et al.  MOAB : a mesh-oriented database. , 2004 .

[23]  Donald G. M. Anderson Iterative Procedures for Nonlinear Integral Equations , 1965, JACM.

[24]  Bahman Zohuri,et al.  Thermal-Hydraulic Analysis of Nuclear Reactors , 2015 .

[25]  W. Bangerth,et al.  deal.II—A general-purpose object-oriented finite element library , 2007, TOMS.

[26]  M. Christon Hydra-TH Theory Manual , 2011 .

[27]  Derek Gaston,et al.  MOOSE: A parallel computational framework for coupled systems of nonlinear equations , 2009 .

[28]  Michael A. Heroux,et al.  Overview of the TriBITS lifecycle model: A Lean/Agile software lifecycle model for research-based computational science and engineering software , 2012, 2012 IEEE 8th International Conference on E-Science.

[29]  Alan B. Williams,et al.  SIERRA Toolkit Computational Mesh Conceptual Model , 2010 .

[30]  R. Baker,et al.  An Sn algorithm for the massively parallel CM-200 computer , 1998 .

[31]  Tamara G. Kolda,et al.  An overview of the Trilinos project , 2005, TOMS.

[32]  G. I. Maldonado,et al.  Verification of the shift Monte Carlo code with the C5G7 reactor benchmark , 2012 .

[33]  Benjamin S. Kirk,et al.  Library for Parallel Adaptive Mesh Refinement / Coarsening Simulations , 2006 .

[34]  Stuart R. Slattery,et al.  Mesh-free data transfer algorithms for partitioned multiphysics problems: Conservation, accuracy, and parallelism , 2016, J. Comput. Phys..

[35]  Charbel Farhat,et al.  Modeling and Simulation of Multiphysics Systems , 2005, J. Comput. Inf. Sci. Eng..

[36]  Robert K. Wysocki,et al.  Effective Project Management: Traditional, Adaptive, Extreme , 2000 .

[37]  Benoit Forget,et al.  Benchmark for evaluation and validation of reactor simulations (BEAVRS) , 2013 .

[38]  April A. Lewis,et al.  Virtual Office, Community, and Computing (VOCC): Designing an Energy Science Hub Collaboration System , 2011, HCI.

[39]  James R. Stewart,et al.  The SIERRA Framework for Developing Advanced Parallel Mechanics Applications , 2003 .

[40]  M. Avramova,et al.  Evaluation and enhancement of COBRA-TF efficiency for LWR calculations , 2006 .

[41]  Kevin T. Clarno,et al.  Simulation of CRUD Induced Power Shift using the VERA Core Simulator and MAMBA , 2016 .

[42]  William A. Wieselquist,et al.  VERA Benchmarking Results for Watts Bar Nuclear Plant Unit 1 Cycles 1-12 , 2016 .

[43]  Brendan Kochunas,et al.  High fidelity modeling of Pellet-CLAD interaction using the CASL virtual environment for reactor applications , 2015 .

[44]  Esma Senturk Gel,et al.  Comparison of frameworks for a next‐generation multiphase flow solver, MFIX: a group decision‐making exercise , 2007, Concurr. Comput. Pract. Exp..

[45]  Roger P. Pawlowski,et al.  DESIGN OF A HIGH FIDELITY CORE SIMULATOR FOR ANALYSIS OF PELLET CLAD INTERACTION. , 2015 .

[46]  Paul J. Turinsky,et al.  Modeling and simulation challenges pursued by the Consortium for Advanced Simulation of Light Water Reactors (CASL) , 2016, J. Comput. Phys..

[47]  Hank Childs,et al.  VisIt: An End-User Tool for Visualizing and Analyzing Very Large Data , 2011 .

[48]  Esma S. Gel,et al.  Comparison of frameworks for a next-generation multiphase flow solver, MFIX: a group decision-making exercise: Research Articles , 2007 .

[49]  Jack J. Dongarra,et al.  A set of level 3 basic linear algebra subprograms , 1990, TOMS.

[50]  Roger P. Pawlowski,et al.  An assessment of coupling algorithms for nuclear reactor core physics simulations , 2016, J. Comput. Phys..

[51]  D. Keyes,et al.  Jacobian-free Newton-Krylov methods: a survey of approaches and applications , 2004 .