An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing

This paper develops a multi-physics interface code MC-FLUENT to couple the Monte Carlo code OpenMC with the commercial computational fluid dynamics code ANSYS FLUENT. The implementations and parallel performances of block Gauss–Seidel-type and block Jacobi-type Picard iterative algorithms have been...

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Main Authors: Qingyang Zhang, Tianji Peng, Guangchun Zhang, Jie Liu, Xiaowei Guo, Chunye Gong, Bo Yang, Xukai Fan
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Science and Technology of Nuclear Installations
Online Access:http://dx.doi.org/10.1155/2021/5549602
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author Qingyang Zhang
Tianji Peng
Guangchun Zhang
Jie Liu
Xiaowei Guo
Chunye Gong
Bo Yang
Xukai Fan
author_facet Qingyang Zhang
Tianji Peng
Guangchun Zhang
Jie Liu
Xiaowei Guo
Chunye Gong
Bo Yang
Xukai Fan
author_sort Qingyang Zhang
collection DOAJ
description This paper develops a multi-physics interface code MC-FLUENT to couple the Monte Carlo code OpenMC with the commercial computational fluid dynamics code ANSYS FLUENT. The implementations and parallel performances of block Gauss–Seidel-type and block Jacobi-type Picard iterative algorithms have been investigated. In addition, this paper introduces two adaptive load-balancing algorithms into the neutronics and thermal-hydraulics coupled simulation to reduce the time cost of computation. Considering that the different scalability of OpenMC and FLUENT limits the performance of block Gauss–Seidel algorithm, an adaptive load-balancing algorithm that can increase the number of nodes dynamically is proposed to improve its efficiency. Moreover, with the natural parallelism of block Jacobi algorithm, another adaptive load-balancing algorithm is proposed to improve its performance. A 3 x 3 PWR fuel pin model and a 1000 MWt ABR metallic benchmark core were used to compare the performances of the two algorithms and verify the effectiveness of the two adaptive load-balancing algorithms. The results show that the adaptive load-balancing algorithms proposed in this paper can greatly improve the computing efficiency of block Jacobi algorithm and improve the performance of block Gauss–Seidel algorithm when the number of nodes is large. In addition, the adaptive load-balancing algorithms are especially effective when a case demands different computational power of OpenMC and FLUENT.
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spelling doaj-art-d6927df1e22d4b06913fda18606c4e4a2025-08-20T02:19:33ZengWileyScience and Technology of Nuclear Installations1687-60751687-60832021-01-01202110.1155/2021/55496025549602An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load BalancingQingyang Zhang0Tianji Peng1Guangchun Zhang2Jie Liu3Xiaowei Guo4Chunye Gong5Bo Yang6Xukai Fan7National University of Defense Technology, Science and Technology on Parallel and Distributed Processing Laboratory, Changsha 410073, ChinaChinese Academy of Sciences, Institute of Modern Physics, Lanzhou 730030, ChinaNational University of Defense Technology, Science and Technology on Parallel and Distributed Processing Laboratory, Changsha 410073, ChinaNational University of Defense Technology, Science and Technology on Parallel and Distributed Processing Laboratory, Changsha 410073, ChinaNational University of Defense Technology, Science and Technology on Parallel and Distributed Processing Laboratory, Changsha 410073, ChinaNational University of Defense Technology, Science and Technology on Parallel and Distributed Processing Laboratory, Changsha 410073, ChinaNational University of Defense Technology, Science and Technology on Parallel and Distributed Processing Laboratory, Changsha 410073, ChinaChinese Academy of Sciences, Institute of Modern Physics, Lanzhou 730030, ChinaThis paper develops a multi-physics interface code MC-FLUENT to couple the Monte Carlo code OpenMC with the commercial computational fluid dynamics code ANSYS FLUENT. The implementations and parallel performances of block Gauss–Seidel-type and block Jacobi-type Picard iterative algorithms have been investigated. In addition, this paper introduces two adaptive load-balancing algorithms into the neutronics and thermal-hydraulics coupled simulation to reduce the time cost of computation. Considering that the different scalability of OpenMC and FLUENT limits the performance of block Gauss–Seidel algorithm, an adaptive load-balancing algorithm that can increase the number of nodes dynamically is proposed to improve its efficiency. Moreover, with the natural parallelism of block Jacobi algorithm, another adaptive load-balancing algorithm is proposed to improve its performance. A 3 x 3 PWR fuel pin model and a 1000 MWt ABR metallic benchmark core were used to compare the performances of the two algorithms and verify the effectiveness of the two adaptive load-balancing algorithms. The results show that the adaptive load-balancing algorithms proposed in this paper can greatly improve the computing efficiency of block Jacobi algorithm and improve the performance of block Gauss–Seidel algorithm when the number of nodes is large. In addition, the adaptive load-balancing algorithms are especially effective when a case demands different computational power of OpenMC and FLUENT.http://dx.doi.org/10.1155/2021/5549602
spellingShingle Qingyang Zhang
Tianji Peng
Guangchun Zhang
Jie Liu
Xiaowei Guo
Chunye Gong
Bo Yang
Xukai Fan
An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing
Science and Technology of Nuclear Installations
title An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing
title_full An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing
title_fullStr An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing
title_full_unstemmed An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing
title_short An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing
title_sort efficient scheme for coupling openmc and fluent with adaptive load balancing
url http://dx.doi.org/10.1155/2021/5549602
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