{"title":"用于基于粒子的 CFD 模拟的复杂几何等值面重建算法","authors":"","doi":"10.1016/j.cpc.2024.109333","DOIUrl":null,"url":null,"abstract":"<div><p>This paper presents a new preprocessing algorithm to generate accurate initial conditions for particle-method-based CFD simulations with complex geometries. The algorithm is based on the improved Marching Cubes method (MC) with the newly proposed isosurface particle redistribution optimisation. It can not only produce topologically accurate isosurfaces and boundary particles that encompass the entire boundary surface but also offers a seamless method for evenly distributing internal fluid particles, eliminating the necessity for additional fluid field reconstruction algorithms. To address the issue of particle clustering on the surface boundary caused by MC intersection with sharp corners in complex geometries, we have introduced an iterative particle-moving algorithm. This algorithm aims to both achieve a uniform distribution of boundary particles across the surface and to recompute their normal vectors due to particles movement. In introducing our newly developed preprocessing algorithm, we have taken the initiative to systematically elucidate the entire process of generating boundary particles on complex surfaces using optimization theory, marking a pioneering effort in this regard. The developed particle preprocessing optimization techniques can use inputs from both the volume image data format from MRI/CT and standard CAD files, such as STL models. We have used various test cases with standard CAD geometries and complex real-world application geometries to validate and test the algorithms. The results demonstrate the impressive ability of our preprocessing toolkit<span><span><sup>1</sup></span></span> to handle real complex geometries, along with the robustness and efficiency of the newly developed algorithms.</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":7.2000,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A complex geometry isosurface reconstruction algorithm for particle based CFD simulations\",\"authors\":\"\",\"doi\":\"10.1016/j.cpc.2024.109333\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper presents a new preprocessing algorithm to generate accurate initial conditions for particle-method-based CFD simulations with complex geometries. The algorithm is based on the improved Marching Cubes method (MC) with the newly proposed isosurface particle redistribution optimisation. It can not only produce topologically accurate isosurfaces and boundary particles that encompass the entire boundary surface but also offers a seamless method for evenly distributing internal fluid particles, eliminating the necessity for additional fluid field reconstruction algorithms. To address the issue of particle clustering on the surface boundary caused by MC intersection with sharp corners in complex geometries, we have introduced an iterative particle-moving algorithm. This algorithm aims to both achieve a uniform distribution of boundary particles across the surface and to recompute their normal vectors due to particles movement. In introducing our newly developed preprocessing algorithm, we have taken the initiative to systematically elucidate the entire process of generating boundary particles on complex surfaces using optimization theory, marking a pioneering effort in this regard. The developed particle preprocessing optimization techniques can use inputs from both the volume image data format from MRI/CT and standard CAD files, such as STL models. We have used various test cases with standard CAD geometries and complex real-world application geometries to validate and test the algorithms. The results demonstrate the impressive ability of our preprocessing toolkit<span><span><sup>1</sup></span></span> to handle real complex geometries, along with the robustness and efficiency of the newly developed algorithms.</p></div>\",\"PeriodicalId\":285,\"journal\":{\"name\":\"Computer Physics Communications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":7.2000,\"publicationDate\":\"2024-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Physics Communications\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S001046552400256X\",\"RegionNum\":2,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Physics Communications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S001046552400256X","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
A complex geometry isosurface reconstruction algorithm for particle based CFD simulations
This paper presents a new preprocessing algorithm to generate accurate initial conditions for particle-method-based CFD simulations with complex geometries. The algorithm is based on the improved Marching Cubes method (MC) with the newly proposed isosurface particle redistribution optimisation. It can not only produce topologically accurate isosurfaces and boundary particles that encompass the entire boundary surface but also offers a seamless method for evenly distributing internal fluid particles, eliminating the necessity for additional fluid field reconstruction algorithms. To address the issue of particle clustering on the surface boundary caused by MC intersection with sharp corners in complex geometries, we have introduced an iterative particle-moving algorithm. This algorithm aims to both achieve a uniform distribution of boundary particles across the surface and to recompute their normal vectors due to particles movement. In introducing our newly developed preprocessing algorithm, we have taken the initiative to systematically elucidate the entire process of generating boundary particles on complex surfaces using optimization theory, marking a pioneering effort in this regard. The developed particle preprocessing optimization techniques can use inputs from both the volume image data format from MRI/CT and standard CAD files, such as STL models. We have used various test cases with standard CAD geometries and complex real-world application geometries to validate and test the algorithms. The results demonstrate the impressive ability of our preprocessing toolkit1 to handle real complex geometries, along with the robustness and efficiency of the newly developed algorithms.
期刊介绍:
The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper.
Computer Programs in Physics (CPiP)
These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged.
Computational Physics Papers (CP)
These are research papers in, but are not limited to, the following themes across computational physics and related disciplines.
mathematical and numerical methods and algorithms;
computational models including those associated with the design, control and analysis of experiments; and
algebraic computation.
Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.