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Shared-Memory parallelization of consistent particle method for violent wave impact problems
Applied Ocean Research, Volume: 69, Pages: 87 - 99
Swansea University Author: Min Luo
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DOI (Published version): 10.1016/j.apor.2017.09.013
Abstract
A shared-memory parallelization is implemented to the recently developed Consistent Particle Method (CPM) for violent wave impact problems. The advantages of this relatively new particle method lie in four key aspects: (1) accurate computation of Laplacian and gradient operators based on Taylor seri...
Published in: | Applied Ocean Research |
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ISSN: | 01411187 |
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2017
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URI: | https://cronfa.swan.ac.uk/Record/cronfa36811 |
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2019-06-10T15:39:13.0968802 v2 36811 2017-11-16 Shared-Memory parallelization of consistent particle method for violent wave impact problems 91e3463c73c6a9d1f5c025feebe4ad0f 0000-0002-6688-9127 Min Luo Min Luo true false 2017-11-16 GENG A shared-memory parallelization is implemented to the recently developed Consistent Particle Method (CPM) for violent wave impact problems. The advantages of this relatively new particle method lie in four key aspects: (1) accurate computation of Laplacian and gradient operators based on Taylor series expansion, alleviating spurious pressure fluctuation and being able to model two-phase flows characterized by large density difference, (2) a thermodynamics-based compressible solver for modelling compressible air that eliminates the need of determining artificial sound speed, (3) seamless coupling of the compressible air solver and incompressible water solver, and (4) parallelization of the numerical model based on Open Multi-Processing (OpenMP) and a parallel direct sparse solver (Pardiso) to significantly improve computational efficiency. Strong and weak scaling analyses of the parallelized CPM are conducted, showing an efficiency speedup of 100 times or more depending on the size of simulated problem. To demonstrate the accuracy of the developed numerical model, three numerical examples are studied including the benchmark study of wave impact on seawall, and our experimental studies of violent water sloshing under rotational excitations and sloshing impact with entrapped air pocket. CPM is shown to accurately capture highly deformed breaking waves and violent wave impact pressure including pressure oscillation induced by air cushion effect. Journal Article Applied Ocean Research 69 87 99 01411187 particle method; wave impact; shared-memory; two-phase flow; air compressibility 31 12 2017 2017-12-31 10.1016/j.apor.2017.09.013 COLLEGE NANME General Engineering COLLEGE CODE GENG Swansea University 2019-06-10T15:39:13.0968802 2017-11-16T18:55:01.9542172 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - General Engineering M. Luo 1 C.G. Koh 2 Min Luo 0000-0002-6688-9127 3 0036811-08012018090806.pdf luo2017v2.pdf 2018-01-08T09:08:06.6100000 Output 1987235 application/pdf Accepted Manuscript true 2018-11-05T00:00:00.0000000 true eng |
title |
Shared-Memory parallelization of consistent particle method for violent wave impact problems |
spellingShingle |
Shared-Memory parallelization of consistent particle method for violent wave impact problems Min Luo |
title_short |
Shared-Memory parallelization of consistent particle method for violent wave impact problems |
title_full |
Shared-Memory parallelization of consistent particle method for violent wave impact problems |
title_fullStr |
Shared-Memory parallelization of consistent particle method for violent wave impact problems |
title_full_unstemmed |
Shared-Memory parallelization of consistent particle method for violent wave impact problems |
title_sort |
Shared-Memory parallelization of consistent particle method for violent wave impact problems |
author_id_str_mv |
91e3463c73c6a9d1f5c025feebe4ad0f |
author_id_fullname_str_mv |
91e3463c73c6a9d1f5c025feebe4ad0f_***_Min Luo |
author |
Min Luo |
author2 |
M. Luo C.G. Koh Min Luo |
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Journal article |
container_title |
Applied Ocean Research |
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69 |
container_start_page |
87 |
publishDate |
2017 |
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Swansea University |
issn |
01411187 |
doi_str_mv |
10.1016/j.apor.2017.09.013 |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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School of Aerospace, Civil, Electrical, General and Mechanical Engineering - General Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - General Engineering |
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description |
A shared-memory parallelization is implemented to the recently developed Consistent Particle Method (CPM) for violent wave impact problems. The advantages of this relatively new particle method lie in four key aspects: (1) accurate computation of Laplacian and gradient operators based on Taylor series expansion, alleviating spurious pressure fluctuation and being able to model two-phase flows characterized by large density difference, (2) a thermodynamics-based compressible solver for modelling compressible air that eliminates the need of determining artificial sound speed, (3) seamless coupling of the compressible air solver and incompressible water solver, and (4) parallelization of the numerical model based on Open Multi-Processing (OpenMP) and a parallel direct sparse solver (Pardiso) to significantly improve computational efficiency. Strong and weak scaling analyses of the parallelized CPM are conducted, showing an efficiency speedup of 100 times or more depending on the size of simulated problem. To demonstrate the accuracy of the developed numerical model, three numerical examples are studied including the benchmark study of wave impact on seawall, and our experimental studies of violent water sloshing under rotational excitations and sloshing impact with entrapped air pocket. CPM is shown to accurately capture highly deformed breaking waves and violent wave impact pressure including pressure oscillation induced by air cushion effect. |
published_date |
2017-12-31T03:46:10Z |
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1763752196320526336 |
score |
11.036837 |