An assessment of coupling algorithms for nuclear reactor core physics simulations

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• 作者：Steven Hamilton^a ; ^{hamiltonsp@ornl.gov" class="auth_mail" title="E-mail the corresponding author} ; Mark Berrill^a ; ^{berrillma@ornl.gov" class="auth_mail" title="E-mail the corresponding author} ; Kevin Clarno^a ; ^{clarnokt@ornl.gov" class="auth_mail" title="E-mail the corresponding author} ; Roger Pawlowski^b ; ^{rppawlo@sandia.gov" class="auth_mail" title="E-mail the corresponding author} ; Alex Toth^c ; ^{artoth@ncsu.edu" class="auth_mail" title="E-mail the corresponding author} ; C.T. Kelley^c ; ^{tim_kelley@ncsu.edu" class="auth_mail" title="E-mail the corresponding author} ; Thomas Evans^a ; ^{evanstm@ornl.gov" class="auth_mail" title="E-mail the corresponding author} ; Bobby Philip^a ; ^{philipb@ornl.gov" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Multiphysics ; Jacobian-free Newton&ndash ; Krylov ; Anderson acceleration ; Nuclear reactor analysis
• 刊名：Journal of Computational Physics
• 出版年：2016
• 出版时间：15 April 2016
• 年：2016
• 卷：311
• 期：Complete
• 页码：241-257
• 全文大小：713 K

文摘

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Numerical simulations demonstrating the efficiency of JFNK and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.