Computer Physics Communications最新文献

{"title":"uniGasFoam: A particle-based OpenFOAM solver for multiscale rarefied gas flows","authors":"N. Vasileiadis ,&nbsp;G. Tatsios ,&nbsp;C. White ,&nbsp;D.A. Lockerby ,&nbsp;M.K. Borg ,&nbsp;L. Gibelli","doi":"10.1016/j.cpc.2025.109532","DOIUrl":"10.1016/j.cpc.2025.109532","url":null,"abstract":"<div><div>This paper presents uniGasFoam, an open-source particle-based solver for multiscale rarefied gas flow simulations, which has been developed within the well-established OpenFOAM framework, and is an extension of the direct simulation Monte Carlo (DSMC) solver dsmcFoam+. The developed solver addresses the coupling challenges inherent in hybrid continuum-particle methods, originating from the disparate nature of finite-volume (FV) solvers found in computational fluid dynamics (CFD) software and DSMC particle solvers. This is achieved by employing alternative stochastic particle methods, resembling DSMC, to tackle the continuum limit. The uniGasFoam particle-particle coupling produces a numerical implementation that is simpler and more robust, faster in many steady-state flows, and more scalable for transient flows compared to conventional continuum-particle coupling. The presented framework is unified and generic, and can couple DSMC with stochastic particle (SP) and unified stochastic particle (USP) methods, or be employed for pure DSMC, SP, and USP gas simulations. To enhance user experience, reduce required computational resources and minimise user error, advanced adaptive algorithms such as transient adaptive sub-cells, non-uniform cell weighting, and adaptive global time stepping have been integrated into uniGasFoam. In this paper, the hybrid USP-DSMC module of uniGasFoam is rigorously validated through multiple benchmark cases, consistently showing excellent agreement with pure DSMC, hybrid CFD-DSMC, and literature results. Notably, uniGasFoam achieves significant computational gains compared to pure dsmcFoam+ simulations, rendering it a robust computational tool well-suited for addressing multiscale rarefied gas flows of engineering importance.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> uniGasFoam</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/9rvyjbvjw3.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/NVasileiadis93/uniGasFoam</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GNU General Public License 3</div><div><em>Programming language:</em> C++</div><div><em>Nature of problem:</em> uniGasFoam has been developed as an open-source framework for particle-based multiscale rarefied gas flow simulations.</div><div><em>Solution method:</em> uniGasFoam implements an explicit time stepping solver with a hybrid stochastic molecular collision-relaxation scheme appropriate for studying multiscale rarefied gas flows.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"310 ","pages":"Article 109532"},"PeriodicalIF":7.2,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143200071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MeshAC: A 3D mesh generation and adaptation package for multiscale coupling methods","authors":"Kejie Fu ,&nbsp;Mingjie Liao ,&nbsp;Yangshuai Wang ,&nbsp;Jianjun Chen ,&nbsp;Lei Zhang","doi":"10.1016/j.cpc.2025.109523","DOIUrl":"10.1016/j.cpc.2025.109523","url":null,"abstract":"<div><div>This paper introduces the <span>MeshAC</span> package, which generates three-dimensional adaptive meshes tailored for the efficient and robust implementation of multiscale coupling methods. While Delaunay triangulation is commonly used for mesh generation across the entire computational domain, generating meshes for multiscale coupling methods is more challenging due to intrinsic discrete structures such as defects, and the need to match these structures to the continuum domain at the interface. The <span>MeshAC</span> package tackles these challenges by creating hierarchical mesh structures linked through a novel modified interface region. It also incorporates localized modification and reconstruction operations specifically designed for interfaces. These enhancements improve both the implementation efficiency and the quality of the coupled mesh. Furthermore, <span>MeshAC</span> introduces a novel adaptive feature that utilizes gradient-based a posteriori error estimation, which automatically adjusts the atomistic region and continuum mesh, striving for an appropriate trade-off between accuracy and efficiency. This package can be directly applied to the geometry optimization problems of a/c coupling in static mechanics <span><span>[1]</span></span>, <span><span>[2]</span></span>, <span><span>[3]</span></span>, <span><span>[4]</span></span>, <span><span>[5]</span></span>, with potential extensions to many other scenarios. Its capabilities are demonstrated for complex material defects, including straight edge dislocation in BCC W and double voids in FCC Cu. These results suggest that <span>MeshAC</span> can be a valuable tool for researchers and practitioners in computational mechanics.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"310 ","pages":"Article 109523"},"PeriodicalIF":7.2,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143200070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A boundary integral based particle initialization algorithm for Smooth Particle Hydrodynamics","authors":"Parikshit Boregowda ,&nbsp;Gui-Rong Liu","doi":"10.1016/j.cpc.2025.109531","DOIUrl":"10.1016/j.cpc.2025.109531","url":null,"abstract":"<div><div>Algorithms for initializing particle distribution in SPH simulations are important for improving simulation accuracy. However, no such algorithms exist for boundary integral SPH models, which can model complex geometries without requiring layers of virtual particles. This study introduces the Boundary Integral based Particle Initialization (BIPI) algorithm. It employs a particle packing algorithm meticulously designed to redistribute particles to fit the geometry boundary. The BIPI algorithm directly utilizes the geometry's boundary information using the SPH boundary integral formulation. Special consideration is given to particles adjacent to the boundary to prevent artificial volume compression. The BIPI algorithm can hence generate a particle distribution with reduced concentration gradients for domains with complex geometrical shapes. Finally, several examples are presented to demonstrate the effectiveness of the proposed algorithm, including the application of the BIPI algorithm in flow problems.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"310 ","pages":"Article 109531"},"PeriodicalIF":7.2,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Logarithmically complex rigorous Fourier space solution to the 1D grating diffraction problem","authors":"Evgeniy Levdik ,&nbsp;Alexey A. Shcherbakov","doi":"10.1016/j.cpc.2025.109530","DOIUrl":"10.1016/j.cpc.2025.109530","url":null,"abstract":"<div><div>The rigorous solution to the grating diffraction problem is a cornerstone step in many scientific fields and industrial applications ranging from the study of the fundamental properties of metasurfaces to the simulation of photolithography masks. Fourier space methods, such as the Fourier Modal Method, are established tools for the analysis of the electromagnetic properties of periodic structures, but are too computationally demanding to be directly applied to large and multiscale optical structures. This work focuses on pushing the limits of rigorous computations of periodic electromagnetic structures by adapting a powerful tensor compression technique called the Tensor Train decomposition. We have found that the millions and billions of numbers produced by standard discretization schemes are inherently excessive for storing the information about diffraction problems required for computations with a given accuracy, and we show how to adapt the TT algorithms to have a logarithmically growing amount of information to be sufficient for reliable rigorous solution of the Maxwell's equations on an example of large period multiscale 1D grating structures.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"310 ","pages":"Article 109530"},"PeriodicalIF":7.2,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine-learning enhanced predictors for accelerated convergence of partitioned fluid-structure interaction simulations","authors":"Azzeddine Tiba ,&nbsp;Thibault Dairay ,&nbsp;Florian De Vuyst ,&nbsp;Iraj Mortazavi ,&nbsp;Juan Pedro Berro Ramirez","doi":"10.1016/j.cpc.2025.109522","DOIUrl":"10.1016/j.cpc.2025.109522","url":null,"abstract":"<div><div>Stable partitioned techniques for simulating unsteady fluid-structure interaction (FSI) are known to be computationally expensive when high added-mass is involved. Multiple coupling strategies have been developed to accelerate these simulations, but often use predictors in the form of simple finite-difference extrapolations. In this work, we propose a non-intrusive data-driven predictor that couples reduced-order models of both the solid and fluid subproblems, providing an initial guess for the nonlinear problem of the next time step calculation. Each reduced order model is composed of a nonlinear encoder-regressor-decoder architecture and is equipped with an adaptive update strategy that adds robustness for extrapolation. In doing so, the proposed methodology leverages physics-based insights from high-fidelity solvers, thus establishing a physics-aware machine learning predictor. Using three strongly coupled FSI examples, this study demonstrates the improved convergence obtained with the new predictor and the overall computational speedup realized compared to classical approaches.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"310 ","pages":"Article 109522"},"PeriodicalIF":7.2,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143348909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"KinetiX: A performance portable code generator for chemical kinetics and transport properties","authors":"Bogdan A. Danciu,&nbsp;Christos E. Frouzakis","doi":"10.1016/j.cpc.2025.109504","DOIUrl":"10.1016/j.cpc.2025.109504","url":null,"abstract":"<div><div>We present <span>KinetiX</span>, a software toolkit to generate computationally efficient fuel-specific routines for the chemical source term, thermodynamic and mixture-averaged transport properties for use in combustion simulation codes. The C++ routines are designed for high-performance execution on both CPU and GPU architectures. On CPUs, chemical kinetics computations are optimized by eliminating redundant operations and using data alignment and loops with trivial access patterns that enable auto-vectorization, reducing the latency of complex mathematical operations. On GPUs, performance is improved by loop unrolling, reducing the number of costly exponential evaluations and limiting the number of live variables for better register usage. The accuracy of the generated routines is checked against reference values computed using Cantera and the maximum relative errors are below <span><math><msup><mrow><mn>10</mn></mrow><mrow><mo>−</mo><mn>7</mn></mrow></msup></math></span>. We evaluate the performance of the kernels on some of the latest CPU and GPU architectures from AMD and NVIDIA, i.e., AMD EPYC 9653, AMD MI250X, and NVIDIA H100. The routines generated by <span>KinetiX</span> outperform the general-purpose Cantera library, achieving speedups of up to 2.4x for species production rates and 3.2x for mixture-averaged transport properties on CPUs. Compared to the routines generated by PelePhysics (CEPTR), <span>KinetiX</span> achieves speedups of up to 2.6x on CPUs and 1.7x on GPUs for the species production rates kernel on a single-threaded basis.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> KinetiX</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/cjwxfw4btt.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/bogdandanciu/KinetiX</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> BSD 2-clause</div><div><em>Programming language:</em> Python, C++</div><div><em>Nature of problem:</em> Combustion simulations require efficient computation of chemical source terms, thermodynamic and transport properties for diverse fuel types. The challenge is optimizing these computations for both CPUs and GPUs without compromising accuracy.</div><div><em>Solution method:</em> Starting from an input file containing kinetic parameters, thermodynamic and transport data, <span>KinetiX</span> generates fuel-specific routines to compute species production rates, thermodynamic and mixture-averaged transport properties for high-performance execution on both CPU and GPU architectures.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"310 ","pages":"Article 109504"},"PeriodicalIF":7.2,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved velocity-Verlet algorithm for the discrete element method","authors":"Dhairya R. Vyas ,&nbsp;Julio M. Ottino ,&nbsp;Richard M. Lueptow ,&nbsp;Paul B. Umbanhowar","doi":"10.1016/j.cpc.2025.109524","DOIUrl":"10.1016/j.cpc.2025.109524","url":null,"abstract":"<div><div>The Discrete Element Method is widely employed for simulating granular flows, but conventional integration techniques may produce unphysical results for simulations with static friction when particle size ratios exceed <span><math><mi>R</mi><mo>≈</mo><mn>3</mn></math></span>. These inaccuracies arise under certain circumstances because some variables in the velocity-Verlet algorithm are calculated at the half-timestep, while others are computed at the full timestep. To correct this, we develop an improved velocity-Verlet integration algorithm to ensure physically accurate outcomes up to the largest size ratios examined (<span><math><mi>R</mi><mo>=</mo><mn>100</mn></math></span>). The implementation of this improved <span>synchronized_verlet</span> integration method within the LAMMPS framework is detailed, and its effectiveness is validated through a simple three-particle test case and a more general example of granular flow in mixtures with large size-ratios, for which we provide general guidelines for selecting simulation parameters and accurately modeling inelasticity in large particle size-ratio simulations.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"310 ","pages":"Article 109524"},"PeriodicalIF":7.2,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physical units helpful for multiscale modelling","authors":"Wayne Arter","doi":"10.1016/j.cpc.2025.109528","DOIUrl":"10.1016/j.cpc.2025.109528","url":null,"abstract":"<div><div>The work addresses the problem of the interoperability of modelling codes, especially in the context of the relatively limited bandwidth of current High-Performance Computers (HPC). Many codes employ non-dimensionalisations that effectively set units by the scalings they choose for length, time and other key quantities. These units can be difficult to unpick in a multiscale environment, but the natural choice of SI units usually leads to a need to treat a much large range of number with negative consequences for HPC deployment. A compromise, applicable to both particle and mesh-based codes, is sought whereby the user may set length- and time-scales in SI units appropriate to the plasma or other modelling problem under consideration. Application is made both analytically and to existing plasma software that demonstrates reduced need for number range relative to SI. An algorithm is presented that enables treatment of the often tricky problem of changing units with minimal user intervention. The code work indicates use of single-precision (32-bit real number representations) may be adequate for particle-mesh modelling in an unexpectedly large range of circumstances.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"310 ","pages":"Article 109528"},"PeriodicalIF":7.2,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GDGen: A gradient descent-based methodology for the generation of optimized spatial configurations of customized clusters in computational simulations","authors":"Ning Wang","doi":"10.1016/j.cpc.2025.109526","DOIUrl":"10.1016/j.cpc.2025.109526","url":null,"abstract":"<div><div>In this study, Gradient Descent Generation (GDGen) is presented, an innovative methodological framework that utilizes gradient descent algorithms to create dense, non-overlapping configurations of multiple, user-customized clusters and shapes. This technique is crucial for the accuracy and efficacy of molecular dynamics (MD) simulations, finite element analyses, and a multitude of scientific applications where precise spatial arrangement is paramount. GDGen intricately minimizes a loss function tailored to assess spatial overlaps and guide the arrangement process.</div><div>The implementation of GDGen is encapsulated in <em>Pygdgen</em>, a Python package developed to generate intricate atomic configurations, particularly excelling in scenarios involving dense clustering and unconventional geometries. <em>Pygdgen</em> ensures efficient arrangement processes through its optimized coding structure and GPU acceleration capabilities. Its adaptability is evidenced by its application in various fields, from material science and chemistry to urban planning and mechanical design, for arranging complex structures within constrained spaces.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"310 ","pages":"Article 109526"},"PeriodicalIF":7.2,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A domain decomposition parallelization scheme for the Poisson equation in particle-in-cell simulation","authors":"Renfan Mao ,&nbsp;Junxue Ren ,&nbsp;Haibin Tang ,&nbsp;Zhihui Li","doi":"10.1016/j.cpc.2025.109527","DOIUrl":"10.1016/j.cpc.2025.109527","url":null,"abstract":"<div><div>A novel domain decomposition parallelization scheme for solving the Poisson equation in explicit electrostatic particle-in-cell (PIC) plasma simulation is proposed in this paper. Using the Schwarz method, the original problem is transformed into a mapping process on a series of subsets of unknowns, thereby reducing the original problem to a problem with much fewer unknowns. The solver using this scheme will have explicit parallelism brought by domain decomposition and near theoretical scalability benefiting from low communication cost. A two-dimensional Poisson solver code is developed and a series of tests are implemented to verify its correctness and performance. This scheme can provide effective performance improvement for electrostatic PIC simulations.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"310 ","pages":"Article 109527"},"PeriodicalIF":7.2,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}