PyAdMesh: A novel high-performance software for adaptive finite element analysis

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory Pub Date : 2025-01-14 DOI:10.1016/j.simpat.2025.103074

S. Asil Gharebaghi, A.H. Khatami

{"title":"PyAdMesh: A novel high-performance software for adaptive finite element analysis","authors":"S. Asil Gharebaghi, A.H. Khatami","doi":"10.1016/j.simpat.2025.103074","DOIUrl":null,"url":null,"abstract":"<div><div>This study introduces PyAdMesh, an open-source software for reducing discretization errors in finite element analysis using an h-adaptive method. Adaptive approaches iteratively refine meshes to minimize errors but require substantial computational resources due to repeated analyses. PyAdMesh addresses this challenge by employing efficient data transfer operators for displacement, stress, and strain, avoiding full reanalysis. The software achieves performance gains through parallel processing on CPU and GPU, leveraging CuPy, Numba, and Python’s multiprocessing library. GPU parallelization achieves speed-ups of 30 times compared to serial execution, while CPU parallelization yields an 8-fold improvement. PyAdMesh reduces discretization error from 5.5% to 0.07% using a recovery-based error estimation method. Despite low-end hardware, including an Intel Xeon 6148 CPU and NVIDIA Quadro P4000 GPU, the software demonstrates significant potential for adaptive finite element analysis. Future studies should explore its performance on high-end hardware. This work highlights PyAdMesh’s potential for large-scale engineering simulations, balancing computational efficiency and accuracy.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"140 ","pages":"Article 103074"},"PeriodicalIF":3.5000,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Simulation Modelling Practice and Theory","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569190X25000097","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}

引用次数: 0

Abstract

This study introduces PyAdMesh, an open-source software for reducing discretization errors in finite element analysis using an h-adaptive method. Adaptive approaches iteratively refine meshes to minimize errors but require substantial computational resources due to repeated analyses. PyAdMesh addresses this challenge by employing efficient data transfer operators for displacement, stress, and strain, avoiding full reanalysis. The software achieves performance gains through parallel processing on CPU and GPU, leveraging CuPy, Numba, and Python’s multiprocessing library. GPU parallelization achieves speed-ups of 30 times compared to serial execution, while CPU parallelization yields an 8-fold improvement. PyAdMesh reduces discretization error from 5.5% to 0.07% using a recovery-based error estimation method. Despite low-end hardware, including an Intel Xeon 6148 CPU and NVIDIA Quadro P4000 GPU, the software demonstrates significant potential for adaptive finite element analysis. Future studies should explore its performance on high-end hardware. This work highlights PyAdMesh’s potential for large-scale engineering simulations, balancing computational efficiency and accuracy.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Simulation Modelling Practice and Theory 工程技术-计算机：跨学科应用

CiteScore

9.80

自引率

4.80%

发文量

142

审稿时长

21 days

期刊介绍： The journal Simulation Modelling Practice and Theory provides a forum for original, high-quality papers dealing with any aspect of systems simulation and modelling. The journal aims at being a reference and a powerful tool to all those professionally active and/or interested in the methods and applications of simulation. Submitted papers will be peer reviewed and must significantly contribute to modelling and simulation in general or use modelling and simulation in application areas. Paper submission is solicited on: • theoretical aspects of modelling and simulation including formal modelling, model-checking, random number generators, sensitivity analysis, variance reduction techniques, experimental design, meta-modelling, methods and algorithms for validation and verification, selection and comparison procedures etc.; • methodology and application of modelling and simulation in any area, including computer systems, networks, real-time and embedded systems, mobile and intelligent agents, manufacturing and transportation systems, management, engineering, biomedical engineering, economics, ecology and environment, education, transaction handling, etc.; • simulation languages and environments including those, specific to distributed computing, grid computing, high performance computers or computer networks, etc.; • distributed and real-time simulation, simulation interoperability; • tools for high performance computing simulation, including dedicated architectures and parallel computing.