A time-step-robust algorithm to compute particle trajectories in 3-D unstructured meshes for Lagrangian stochastic methods

IF 0.8 Q3 STATISTICS & PROBABILITY Monte Carlo Methods and Applications Pub Date : 2023-03-15 DOI:10.1515/mcma-2023-2002
Guilhem Balvet, J. Minier, C. Henry, Y. Roustan, M. Ferrand
{"title":"A time-step-robust algorithm to compute particle trajectories in 3-D unstructured meshes for Lagrangian stochastic methods","authors":"Guilhem Balvet, J. Minier, C. Henry, Y. Roustan, M. Ferrand","doi":"10.1515/mcma-2023-2002","DOIUrl":null,"url":null,"abstract":"Abstract The purpose of this paper is to propose a time-step-robust cell-to-cell integration of particle trajectories in 3-D unstructured meshes in particle/mesh Lagrangian stochastic methods. The main idea is to dynamically update the mean fields used in the time integration by splitting, for each particle, the time step into sub-steps such that each of these sub-steps corresponds to particle cell residence times. This reduces the spatial discretization error. Given the stochastic nature of the models, a key aspect is to derive estimations of the residence times that do not anticipate the future of the Wiener process. To that effect, the new algorithm relies on a virtual particle, attached to each stochastic one, whose mean conditional behavior provides free-of-statistical-bias predictions of residence times. After consistency checks, this new algorithm is validated on two representative test cases: particle dispersion in a statistically uniform flow and particle dynamics in a non-uniform flow.","PeriodicalId":46576,"journal":{"name":"Monte Carlo Methods and Applications","volume":"29 1","pages":"95 - 126"},"PeriodicalIF":0.8000,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Monte Carlo Methods and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/mcma-2023-2002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 2

Abstract

Abstract The purpose of this paper is to propose a time-step-robust cell-to-cell integration of particle trajectories in 3-D unstructured meshes in particle/mesh Lagrangian stochastic methods. The main idea is to dynamically update the mean fields used in the time integration by splitting, for each particle, the time step into sub-steps such that each of these sub-steps corresponds to particle cell residence times. This reduces the spatial discretization error. Given the stochastic nature of the models, a key aspect is to derive estimations of the residence times that do not anticipate the future of the Wiener process. To that effect, the new algorithm relies on a virtual particle, attached to each stochastic one, whose mean conditional behavior provides free-of-statistical-bias predictions of residence times. After consistency checks, this new algorithm is validated on two representative test cases: particle dispersion in a statistically uniform flow and particle dynamics in a non-uniform flow.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
拉格朗日随机方法计算三维非结构化网格中粒子轨迹的时间步长鲁棒算法
摘要:本文的目的是在粒子/网格拉格朗日随机方法中提出一种时间步长鲁棒的三维非结构化网格中粒子轨迹的胞间积分方法。其主要思想是动态更新时间积分中使用的平均场,方法是将每个粒子的时间步分成子步,这样每个子步对应于粒子单元的停留时间。这减少了空间离散误差。考虑到模型的随机性质,一个关键方面是推导出不预测维纳过程未来的停留时间的估计。为了达到这个效果,新的算法依赖于一个虚拟粒子,附着在每个随机粒子上,它的平均条件行为提供了无统计偏差的停留时间预测。通过一致性检验,在统计均匀流中的粒子弥散和非均匀流中的粒子动力学两个典型测试案例上对该算法进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Monte Carlo Methods and Applications
Monte Carlo Methods and Applications STATISTICS & PROBABILITY-
CiteScore
1.20
自引率
22.20%
发文量
31
期刊最新文献
Asymmetric kernel method in the study of strong stability of the PH/M/1 queuing system Random walk on spheres method for solving anisotropic transient diffusion problems and flux calculations Strong approximation of a two-factor stochastic volatility model under local Lipschitz condition On the estimation of periodic signals in the diffusion process using a high-frequency scheme Stochastic simulation of electron transport in a strong electrical field in low-dimensional heterostructures
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1