欧拉-拉格朗日并行算法模拟含颗粒湍流

IF 4.6 2区 工程技术 Q1 ENGINEERING, MECHANICAL
Harshal P. Mahamure, Deekshith I. Poojary, Vagesh D. Narasimhamurthy, Lihao Zhao  (, )
{"title":"欧拉-拉格朗日并行算法模拟含颗粒湍流","authors":"Harshal P. Mahamure,&nbsp;Deekshith I. Poojary,&nbsp;Vagesh D. Narasimhamurthy,&nbsp;Lihao Zhao \n (,&nbsp;)","doi":"10.1007/s10409-025-24946-x","DOIUrl":null,"url":null,"abstract":"<div><p>This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation (DNS) of particle-laden flows. The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in turbulent carrier flow. The Eulerian framework numerically resolves turbulent carrier flow using a parallelized, finite-volume DNS solver on a staggered Cartesian grid. Particles are tracked using a point-particle method utilizing a Lagrangian particle tracking (LPT) algorithm. The proposed Eulerian-Lagrangian algorithm is validated using an inertial particle-laden turbulent channel flow for different Stokes number cases. The particle concentration profiles and higher-order statistics of the carrier and dispersed phases agree well with the benchmark results. We investigated the effect of fluid velocity interpolation and numerical integration schemes of particle tracking algorithms on particle dispersion statistics. The suitability of fluid velocity interpolation schemes for predicting the particle dispersion statistics is discussed in the framework of the particle tracking algorithm coupled to the finite-volume solver. In addition, we present parallelization strategies implemented in the algorithm and evaluate their parallel performance.</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":7109,"journal":{"name":"Acta Mechanica Sinica","volume":"42 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Eulerian-Lagrangian parallel algorithm for simulation of particle-laden turbulent flows\",\"authors\":\"Harshal P. Mahamure,&nbsp;Deekshith I. Poojary,&nbsp;Vagesh D. Narasimhamurthy,&nbsp;Lihao Zhao \\n (,&nbsp;)\",\"doi\":\"10.1007/s10409-025-24946-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation (DNS) of particle-laden flows. The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in turbulent carrier flow. The Eulerian framework numerically resolves turbulent carrier flow using a parallelized, finite-volume DNS solver on a staggered Cartesian grid. Particles are tracked using a point-particle method utilizing a Lagrangian particle tracking (LPT) algorithm. The proposed Eulerian-Lagrangian algorithm is validated using an inertial particle-laden turbulent channel flow for different Stokes number cases. The particle concentration profiles and higher-order statistics of the carrier and dispersed phases agree well with the benchmark results. We investigated the effect of fluid velocity interpolation and numerical integration schemes of particle tracking algorithms on particle dispersion statistics. The suitability of fluid velocity interpolation schemes for predicting the particle dispersion statistics is discussed in the framework of the particle tracking algorithm coupled to the finite-volume solver. In addition, we present parallelization strategies implemented in the algorithm and evaluate their parallel performance.</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>\",\"PeriodicalId\":7109,\"journal\":{\"name\":\"Acta Mechanica Sinica\",\"volume\":\"42 1\",\"pages\":\"\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Mechanica Sinica\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10409-025-24946-x\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Mechanica Sinica","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s10409-025-24946-x","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0

摘要

本文提出了一种用于颗粒流直接数值模拟(DNS)的欧拉-拉格朗日算法。该算法适用于湍流载流中惯性小颗粒稀悬液的模拟。欧拉框架在交错笛卡尔网格上使用并行的有限体积DNS求解器对湍流载流子流进行数值求解。利用拉格朗日粒子跟踪(LPT)算法,采用点粒子方法对粒子进行跟踪。在不同斯托克斯数的情况下,利用惯性粒子负载湍流通道对欧拉-拉格朗日算法进行了验证。载体相和分散相的颗粒浓度分布和高阶统计量与基准结果吻合较好。研究了流体速度插值和粒子跟踪算法的数值积分方案对粒子色散统计的影响。在粒子跟踪算法与有限体积求解器耦合的框架下,讨论了流体速度插值格式预测粒子色散统计的适用性。此外,我们还提出了在该算法中实现的并行化策略,并评估了它们的并行性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Eulerian-Lagrangian parallel algorithm for simulation of particle-laden turbulent flows

This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation (DNS) of particle-laden flows. The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in turbulent carrier flow. The Eulerian framework numerically resolves turbulent carrier flow using a parallelized, finite-volume DNS solver on a staggered Cartesian grid. Particles are tracked using a point-particle method utilizing a Lagrangian particle tracking (LPT) algorithm. The proposed Eulerian-Lagrangian algorithm is validated using an inertial particle-laden turbulent channel flow for different Stokes number cases. The particle concentration profiles and higher-order statistics of the carrier and dispersed phases agree well with the benchmark results. We investigated the effect of fluid velocity interpolation and numerical integration schemes of particle tracking algorithms on particle dispersion statistics. The suitability of fluid velocity interpolation schemes for predicting the particle dispersion statistics is discussed in the framework of the particle tracking algorithm coupled to the finite-volume solver. In addition, we present parallelization strategies implemented in the algorithm and evaluate their parallel performance.

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
Acta Mechanica Sinica
Acta Mechanica Sinica 物理-工程:机械
CiteScore
5.60
自引率
20.00%
发文量
1807
审稿时长
4 months
期刊介绍: Acta Mechanica Sinica, sponsored by the Chinese Society of Theoretical and Applied Mechanics, promotes scientific exchanges and collaboration among Chinese scientists in China and abroad. It features high quality, original papers in all aspects of mechanics and mechanical sciences. Not only does the journal explore the classical subdivisions of theoretical and applied mechanics such as solid and fluid mechanics, it also explores recently emerging areas such as biomechanics and nanomechanics. In addition, the journal investigates analytical, computational, and experimental progresses in all areas of mechanics. Lastly, it encourages research in interdisciplinary subjects, serving as a bridge between mechanics and other branches of engineering and the sciences. In addition to research papers, Acta Mechanica Sinica publishes reviews, notes, experimental techniques, scientific events, and other special topics of interest. Related subjects » Classical Continuum Physics - Computational Intelligence and Complexity - Mechanics
×
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:604180095
Book学术官方微信