{"title":"Analysis of the particle relaxation method","authors":"Yu Fan, Xiaoliang Li, Shuoguo Zhang, Xiangyu Hu, Nikolaus A. Adams","doi":"10.1007/s40571-025-00965-6","DOIUrl":null,"url":null,"abstract":"<div><p>We establish a theoretical framework of the particle relaxation method for uniform particle generation of smoothed particle hydrodynamics. We achieve this by reformulating the particle relaxation as an optimization problem. The objective function is an integral difference between discrete particle-based and smoothed-analytical volume fractions, which globally measures zero-order inconsistency in the interior domain. The analysis demonstrates that the particle relaxation method in the domain interior is essentially equivalent to employing a gradient descent approach to solve this optimization problem, and we can extend such an equivalence to the bounded domain by introducing a proper boundary term. Additionally, each periodic particle distribution has a spatially uniform particle volume, denoted as characteristic volume. The relaxed particle distribution has the largest characteristic volume, and the kernel cut-off radius determines this volume. These insights explain the equivalence between uniform particle distributions and optimized zero-order consistency and enable us to control the relaxed particle distribution by selecting the target kernel cut-off radius for a given kernel function.</p></div>","PeriodicalId":524,"journal":{"name":"Computational Particle Mechanics","volume":"12 5","pages":"3007 - 3021"},"PeriodicalIF":3.4000,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40571-025-00965-6.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Particle Mechanics","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s40571-025-00965-6","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
We establish a theoretical framework of the particle relaxation method for uniform particle generation of smoothed particle hydrodynamics. We achieve this by reformulating the particle relaxation as an optimization problem. The objective function is an integral difference between discrete particle-based and smoothed-analytical volume fractions, which globally measures zero-order inconsistency in the interior domain. The analysis demonstrates that the particle relaxation method in the domain interior is essentially equivalent to employing a gradient descent approach to solve this optimization problem, and we can extend such an equivalence to the bounded domain by introducing a proper boundary term. Additionally, each periodic particle distribution has a spatially uniform particle volume, denoted as characteristic volume. The relaxed particle distribution has the largest characteristic volume, and the kernel cut-off radius determines this volume. These insights explain the equivalence between uniform particle distributions and optimized zero-order consistency and enable us to control the relaxed particle distribution by selecting the target kernel cut-off radius for a given kernel function.
期刊介绍:
GENERAL OBJECTIVES: Computational Particle Mechanics (CPM) is a quarterly journal with the goal of publishing full-length original articles addressing the modeling and simulation of systems involving particles and particle methods. The goal is to enhance communication among researchers in the applied sciences who use "particles'''' in one form or another in their research.
SPECIFIC OBJECTIVES: Particle-based materials and numerical methods have become wide-spread in the natural and applied sciences, engineering, biology. The term "particle methods/mechanics'''' has now come to imply several different things to researchers in the 21st century, including:
(a) Particles as a physical unit in granular media, particulate flows, plasmas, swarms, etc.,
(b) Particles representing material phases in continua at the meso-, micro-and nano-scale and
(c) Particles as a discretization unit in continua and discontinua in numerical methods such as
Discrete Element Methods (DEM), Particle Finite Element Methods (PFEM), Molecular Dynamics (MD), and Smoothed Particle Hydrodynamics (SPH), to name a few.