A Novel Framework for Automated Grid Generation and CFD Simulation of Complex Geometries

A novel technical framework for the automatic generation of grids and subsequent flow field computation in complex geometries was introduced. This framework integrated body-fitted grids that accommodate intersecting grid lines, the flexible-node finite difference method (FN-FDM) designed for unorder...

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Main Authors: Chunguang XU, Xin OUYANG, Jie CHEN, Jun LIU
Format: Article
Language:zho
Published: China Astronautic Publishing CO., LTD. ; Editorial Office of Physics of Gases 2024-11-01
Series:气体物理
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Online Access:http://qtwl.xml-journal.net/cn/article/doi/10.19527/j.cnki.2096-1642.1132
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author Chunguang XU
Xin OUYANG
Jie CHEN
Jun LIU
author_facet Chunguang XU
Xin OUYANG
Jie CHEN
Jun LIU
author_sort Chunguang XU
collection DOAJ
description A novel technical framework for the automatic generation of grids and subsequent flow field computation in complex geometries was introduced. This framework integrated body-fitted grids that accommodate intersecting grid lines, the flexible-node finite difference method (FN-FDM) designed for unordered point clouds, and a universal algorithm for freestream preservation (discrete equivalence equation and its discrete rule, DEER). It achieved full automation in the process from importing discrete surface points to generating flow field computation results. The grid generation algorithm, starting from a vector of discrete points on the object surface, generated body-fitted grides in a single pass based on parameters such as the height of the grid layer, growth rate, and number of layers. It removed overlapping grides and reconstructed the computational stencil required for FN-FDM. FN-FDM utilized the reconstructed computational stencil to perform the differential solution of flow field parameters. DEER was used to eliminate the geometrically induced errors introduced during the differential computation from the physical plane to the computational plane, achieving freestream preservation and improving computational accuracy. Verification results demonstrate that the new framework can automatically generate grids under complex geometries, significantly improving the efficiency of grid generation, while maintaining computational accuracy comparable to that of conventional methods. This framework has practical value in engineering applications.
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publishDate 2024-11-01
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series 气体物理
spelling doaj-art-ee2d1ec90f7c4f7090f4dc2abf71b0022025-08-20T02:43:42ZzhoChina Astronautic Publishing CO., LTD. ; Editorial Office of Physics of Gases气体物理2096-16422024-11-0196466110.19527/j.cnki.2096-1642.1132qtwl-9-6-46A Novel Framework for Automated Grid Generation and CFD Simulation of Complex GeometriesChunguang XU0Xin OUYANG1Jie CHEN2Jun LIU3School of Aeronautics and Astronautics, Sun Yat-Sen University, Guangzhou 510275, ChinaSchool of Aeronautics and Astronautics, Sun Yat-Sen University, Guangzhou 510275, ChinaSchool of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian 116024, ChinaSchool of Mechanical Engineering and Mechanics, Ningbo University, Ningbo 315211, ChinaA novel technical framework for the automatic generation of grids and subsequent flow field computation in complex geometries was introduced. This framework integrated body-fitted grids that accommodate intersecting grid lines, the flexible-node finite difference method (FN-FDM) designed for unordered point clouds, and a universal algorithm for freestream preservation (discrete equivalence equation and its discrete rule, DEER). It achieved full automation in the process from importing discrete surface points to generating flow field computation results. The grid generation algorithm, starting from a vector of discrete points on the object surface, generated body-fitted grides in a single pass based on parameters such as the height of the grid layer, growth rate, and number of layers. It removed overlapping grides and reconstructed the computational stencil required for FN-FDM. FN-FDM utilized the reconstructed computational stencil to perform the differential solution of flow field parameters. DEER was used to eliminate the geometrically induced errors introduced during the differential computation from the physical plane to the computational plane, achieving freestream preservation and improving computational accuracy. Verification results demonstrate that the new framework can automatically generate grids under complex geometries, significantly improving the efficiency of grid generation, while maintaining computational accuracy comparable to that of conventional methods. This framework has practical value in engineering applications.http://qtwl.xml-journal.net/cn/article/doi/10.19527/j.cnki.2096-1642.1132automatic cfdcartesian gridflexible-node finite difference methodbody-fitted gridstrand griddiscrete equivalence equation and its discrete rule
spellingShingle Chunguang XU
Xin OUYANG
Jie CHEN
Jun LIU
A Novel Framework for Automated Grid Generation and CFD Simulation of Complex Geometries
气体物理
automatic cfd
cartesian grid
flexible-node finite difference method
body-fitted grid
strand grid
discrete equivalence equation and its discrete rule
title A Novel Framework for Automated Grid Generation and CFD Simulation of Complex Geometries
title_full A Novel Framework for Automated Grid Generation and CFD Simulation of Complex Geometries
title_fullStr A Novel Framework for Automated Grid Generation and CFD Simulation of Complex Geometries
title_full_unstemmed A Novel Framework for Automated Grid Generation and CFD Simulation of Complex Geometries
title_short A Novel Framework for Automated Grid Generation and CFD Simulation of Complex Geometries
title_sort novel framework for automated grid generation and cfd simulation of complex geometries
topic automatic cfd
cartesian grid
flexible-node finite difference method
body-fitted grid
strand grid
discrete equivalence equation and its discrete rule
url http://qtwl.xml-journal.net/cn/article/doi/10.19527/j.cnki.2096-1642.1132
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