用于基于粒子的 CFD 模拟的复杂几何等值面重建算法

IF 7.2 2区 物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
{"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}
引用次数: 0

摘要

本文介绍了一种新的预处理算法,用于为基于粒子法的复杂几何形状 CFD 模拟生成精确的初始条件。该算法基于改进的 Marching Cubes 方法(MC)和新提出的等面粒子再分布优化。它不仅能生成拓扑精确的等值面和覆盖整个边界面的边界粒子,还提供了一种无缝的内部流体粒子均匀分布方法,从而消除了额外流场重建算法的必要性。为了解决复杂几何形状中 MC 与锐角相交造成的表面边界上的粒子集群问题,我们引入了一种粒子移动迭代算法。该算法旨在实现边界颗粒在整个表面上的均匀分布,并重新计算颗粒移动时的法向量。在介绍我们新开发的预处理算法时,我们主动利用优化理论系统地阐明了在复杂表面上生成边界粒子的整个过程,在这方面做出了开创性的努力。所开发的粒子预处理优化技术可使用来自 MRI/CT 的体图像数据格式和标准 CAD 文件(如 STL 模型)的输入。我们使用了标准 CAD 几何图形和复杂实际应用几何图形的各种测试案例来验证和测试算法。结果表明,我们的预处理工具包1 处理实际复杂几何图形的能力以及新开发算法的鲁棒性和效率令人印象深刻。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Computer Physics Communications
Computer Physics Communications 物理-计算机:跨学科应用
CiteScore
12.10
自引率
3.20%
发文量
287
审稿时长
5.3 months
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信