Cargando…

A parallel methodology of adaptive Cartesian grid for compressible flow simulations

The combination of Cartesian grid and the adaptive mesh refinement (AMR) technology is an effective way to handle complex geometry and solve complex flow problems. Some high-efficiency Cartesian-based AMR libraries have been developed to handle dynamic changes of the grid in parallel but still can n...

Descripción completa

Detalles Bibliográficos
Autores principales: Qi, Xinyu, Yang, Yuchen, Tian, Linlin, Wang, Zhenming, Zhao, Ning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9073473/
http://dx.doi.org/10.1186/s42774-022-00108-y
_version_ 1784701294338899968
author Qi, Xinyu
Yang, Yuchen
Tian, Linlin
Wang, Zhenming
Zhao, Ning
author_facet Qi, Xinyu
Yang, Yuchen
Tian, Linlin
Wang, Zhenming
Zhao, Ning
author_sort Qi, Xinyu
collection PubMed
description The combination of Cartesian grid and the adaptive mesh refinement (AMR) technology is an effective way to handle complex geometry and solve complex flow problems. Some high-efficiency Cartesian-based AMR libraries have been developed to handle dynamic changes of the grid in parallel but still can not meet the unique requirements of simulating flow around objects. In this paper, we propose an efficient Cartesian grid generation method and an information transmission approach for the wall boundary to parallelize the implementation of ghost-cell method (GCM). Also, the multi-valued ghost-cell method to handle multi-value points is improved to adapt to the parallel framework. Combining the mentioned methodologies with the open-source library p4est, an automatic and efficient simulation of compressible flow is achieved. The overall performance of the methodology is tested through a wide range of inviscid/viscous flow cases. The results indicate that the capability and parallel scalability of the present numerical methodology for solving multiple types of flows, involving shock and vortices, multi-body flow and unsteady flows are agreeable as compared with related reference data.
format Online
Article
Text
id pubmed-9073473
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Springer Nature Singapore
record_format MEDLINE/PubMed
spelling pubmed-90734732022-05-06 A parallel methodology of adaptive Cartesian grid for compressible flow simulations Qi, Xinyu Yang, Yuchen Tian, Linlin Wang, Zhenming Zhao, Ning Adv. Aerodyn. Research The combination of Cartesian grid and the adaptive mesh refinement (AMR) technology is an effective way to handle complex geometry and solve complex flow problems. Some high-efficiency Cartesian-based AMR libraries have been developed to handle dynamic changes of the grid in parallel but still can not meet the unique requirements of simulating flow around objects. In this paper, we propose an efficient Cartesian grid generation method and an information transmission approach for the wall boundary to parallelize the implementation of ghost-cell method (GCM). Also, the multi-valued ghost-cell method to handle multi-value points is improved to adapt to the parallel framework. Combining the mentioned methodologies with the open-source library p4est, an automatic and efficient simulation of compressible flow is achieved. The overall performance of the methodology is tested through a wide range of inviscid/viscous flow cases. The results indicate that the capability and parallel scalability of the present numerical methodology for solving multiple types of flows, involving shock and vortices, multi-body flow and unsteady flows are agreeable as compared with related reference data. Springer Nature Singapore 2022-05-06 2022 /pmc/articles/PMC9073473/ http://dx.doi.org/10.1186/s42774-022-00108-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Qi, Xinyu
Yang, Yuchen
Tian, Linlin
Wang, Zhenming
Zhao, Ning
A parallel methodology of adaptive Cartesian grid for compressible flow simulations
title A parallel methodology of adaptive Cartesian grid for compressible flow simulations
title_full A parallel methodology of adaptive Cartesian grid for compressible flow simulations
title_fullStr A parallel methodology of adaptive Cartesian grid for compressible flow simulations
title_full_unstemmed A parallel methodology of adaptive Cartesian grid for compressible flow simulations
title_short A parallel methodology of adaptive Cartesian grid for compressible flow simulations
title_sort parallel methodology of adaptive cartesian grid for compressible flow simulations
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9073473/
http://dx.doi.org/10.1186/s42774-022-00108-y
work_keys_str_mv AT qixinyu aparallelmethodologyofadaptivecartesiangridforcompressibleflowsimulations
AT yangyuchen aparallelmethodologyofadaptivecartesiangridforcompressibleflowsimulations
AT tianlinlin aparallelmethodologyofadaptivecartesiangridforcompressibleflowsimulations
AT wangzhenming aparallelmethodologyofadaptivecartesiangridforcompressibleflowsimulations
AT zhaoning aparallelmethodologyofadaptivecartesiangridforcompressibleflowsimulations
AT qixinyu parallelmethodologyofadaptivecartesiangridforcompressibleflowsimulations
AT yangyuchen parallelmethodologyofadaptivecartesiangridforcompressibleflowsimulations
AT tianlinlin parallelmethodologyofadaptivecartesiangridforcompressibleflowsimulations
AT wangzhenming parallelmethodologyofadaptivecartesiangridforcompressibleflowsimulations
AT zhaoning parallelmethodologyofadaptivecartesiangridforcompressibleflowsimulations