Locally mesh-refined lattice Boltzmann method for fuel debris air cooling analysis on GPU supercomputer

A dry method is one of practical methods for decommissioning the TEPCO's Fukushima Daiichi nuclear power station. Japan Atomic Energy Agency (JAEA) has been evaluating the air cooling performance of the fuel debris by using the JUPITER code based on an incompressible fluid model and the Cit...

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Autores principales:	Naoyuki ONODERA, Yasuhiro IDOMURA, Shinichiro UESAWA, Susumu YAMASHITA, Hiroyuki YOSHIDA
Formato:	article
Lenguaje:	EN
Publicado:	The Japan Society of Mechanical Engineers 2020
Materias:	natural convection air cooling lattice boltzmann method adaptive mesh refinement high performance computing gpu Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/f7a642d1e85542abbc4be55ef21a864d
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spelling	oai:doaj.org-article:f7a642d1e85542abbc4be55ef21a864d2021-11-29T05:56:30ZLocally mesh-refined lattice Boltzmann method for fuel debris air cooling analysis on GPU supercomputer2187-974510.1299/mej.19-00531https://doaj.org/article/f7a642d1e85542abbc4be55ef21a864d2020-01-01T00:00:00Zhttps://www.jstage.jst.go.jp/article/mej/7/3/7_19-00531/_pdf/-char/enhttps://doaj.org/toc/2187-9745A dry method is one of practical methods for decommissioning the TEPCO's Fukushima Daiichi nuclear power station. Japan Atomic Energy Agency (JAEA) has been evaluating the air cooling performance of the fuel debris by using the JUPITER code based on an incompressible fluid model and the CityLBM code based on the lattice Boltzmann method (LBM). However, these codes were based on a uniform Cartesian grid system, and required large computational time and cost to capture complicated debris structures and multi-scale flows at the actual reactor scale. The adaptive mesh refinement (AMR) method is one of the key techniques to accelerate multi-scale simulations. We develop an AMR version of the CityLBM code on GPU based supercomputers and apply it to thermal-hydrodynamics problems. The proposed method is validated against free convective heat transfer experiments at JAEA. Thanks to the AMR method, grid resolution is optimized near the walls where velocity and temperature gradients are large, and the temperature distribution agrees with the experimental data using half the number of grid points. It is also shown that the AMR based CityLBM code on 4 NVIDIA TESLA V100 GPUs gives 6.7x speedup of the time to solution compared with the JUPITER code on 36 Intel Xeon E5-2680v3 CPUs. The results show that the AMR based LBM is promising for accelerating extreme scale thermal convective simulations.Naoyuki ONODERAYasuhiro IDOMURAShinichiro UESAWASusumu YAMASHITAHiroyuki YOSHIDAThe Japan Society of Mechanical Engineersarticlenatural convectionair coolinglattice boltzmann methodadaptive mesh refinementhigh performance computinggpuMechanical engineering and machineryTJ1-1570ENMechanical Engineering Journal, Vol 7, Iss 3, Pp 19-00531-19-00531 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	natural convection air cooling lattice boltzmann method adaptive mesh refinement high performance computing gpu Mechanical engineering and machinery TJ1-1570
spellingShingle	natural convection air cooling lattice boltzmann method adaptive mesh refinement high performance computing gpu Mechanical engineering and machinery TJ1-1570 Naoyuki ONODERA Yasuhiro IDOMURA Shinichiro UESAWA Susumu YAMASHITA Hiroyuki YOSHIDA Locally mesh-refined lattice Boltzmann method for fuel debris air cooling analysis on GPU supercomputer
description	A dry method is one of practical methods for decommissioning the TEPCO's Fukushima Daiichi nuclear power station. Japan Atomic Energy Agency (JAEA) has been evaluating the air cooling performance of the fuel debris by using the JUPITER code based on an incompressible fluid model and the CityLBM code based on the lattice Boltzmann method (LBM). However, these codes were based on a uniform Cartesian grid system, and required large computational time and cost to capture complicated debris structures and multi-scale flows at the actual reactor scale. The adaptive mesh refinement (AMR) method is one of the key techniques to accelerate multi-scale simulations. We develop an AMR version of the CityLBM code on GPU based supercomputers and apply it to thermal-hydrodynamics problems. The proposed method is validated against free convective heat transfer experiments at JAEA. Thanks to the AMR method, grid resolution is optimized near the walls where velocity and temperature gradients are large, and the temperature distribution agrees with the experimental data using half the number of grid points. It is also shown that the AMR based CityLBM code on 4 NVIDIA TESLA V100 GPUs gives 6.7x speedup of the time to solution compared with the JUPITER code on 36 Intel Xeon E5-2680v3 CPUs. The results show that the AMR based LBM is promising for accelerating extreme scale thermal convective simulations.
format	article
author	Naoyuki ONODERA Yasuhiro IDOMURA Shinichiro UESAWA Susumu YAMASHITA Hiroyuki YOSHIDA
author_facet	Naoyuki ONODERA Yasuhiro IDOMURA Shinichiro UESAWA Susumu YAMASHITA Hiroyuki YOSHIDA
author_sort	Naoyuki ONODERA
title	Locally mesh-refined lattice Boltzmann method for fuel debris air cooling analysis on GPU supercomputer
title_short	Locally mesh-refined lattice Boltzmann method for fuel debris air cooling analysis on GPU supercomputer
title_full	Locally mesh-refined lattice Boltzmann method for fuel debris air cooling analysis on GPU supercomputer
title_fullStr	Locally mesh-refined lattice Boltzmann method for fuel debris air cooling analysis on GPU supercomputer
title_full_unstemmed	Locally mesh-refined lattice Boltzmann method for fuel debris air cooling analysis on GPU supercomputer
title_sort	locally mesh-refined lattice boltzmann method for fuel debris air cooling analysis on gpu supercomputer
publisher	The Japan Society of Mechanical Engineers
publishDate	2020
url	https://doaj.org/article/f7a642d1e85542abbc4be55ef21a864d
work_keys_str_mv	AT naoyukionodera locallymeshrefinedlatticeboltzmannmethodforfueldebrisaircoolinganalysisongpusupercomputer AT yasuhiroidomura locallymeshrefinedlatticeboltzmannmethodforfueldebrisaircoolinganalysisongpusupercomputer AT shinichirouesawa locallymeshrefinedlatticeboltzmannmethodforfueldebrisaircoolinganalysisongpusupercomputer AT susumuyamashita locallymeshrefinedlatticeboltzmannmethodforfueldebrisaircoolinganalysisongpusupercomputer AT hiroyukiyoshida locallymeshrefinedlatticeboltzmannmethodforfueldebrisaircoolinganalysisongpusupercomputer
_version_	1718407623818084352

Locally mesh-refined lattice Boltzmann method for fuel debris air cooling analysis on GPU supercomputer

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