{"title":"A novel coupled clustering FFT2 multiscale method for modeling the nonlinear behavior and failure of composites","authors":"Menglei Li , Marco Magri , Bing Wang , Bing Wang","doi":"10.1016/j.cma.2025.117854","DOIUrl":null,"url":null,"abstract":"<div><div>We propose a novel FFT<sup>2</sup> parallel multiscale computational method to predict the nonlinear behavior and failure of composite materials. Unlike traditional multiscale methods, the proposed approach reformulates the mechanical boundary value problem into Lippmann-Schwinger type integral equations at both the micro- and macro-scale, thereby leveraging the numerical efficiency of the fast Fourier transform (FFT) method at both scales. The application of generic (e.g. non-periodic) boundary conditions at the macro-scale is carried out by using the virtual boundary technique and buffer zones. In addition, the introduction of a clustering algorithm further improves the computational efficiency of the numerical method during the information transfer between scales. To ensure accurate damage prediction and mitigate spurious strain localization at both scales, suitable regularization techniques are employed. The proposed multiscale method is applied to investigate the transverse tension of unidirectional composite dog-bone specimens. After experimental verification, the method is applied to simulate 2D and 3D brittle fracture, elasto-plastic damage, and examples with non-uniform material orientation. The results demonstrate the robustness and adaptability of the clustering approach, which achieves up to 65.90-fold speedup and 81.62-fold reduction in memory usage compared to non-clustered multiscale methods, while maintaining a comparable level of accuracy.</div></div>","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"438 ","pages":"Article 117854"},"PeriodicalIF":6.9000,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Methods in Applied Mechanics and Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0045782525001264","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
We propose a novel FFT2 parallel multiscale computational method to predict the nonlinear behavior and failure of composite materials. Unlike traditional multiscale methods, the proposed approach reformulates the mechanical boundary value problem into Lippmann-Schwinger type integral equations at both the micro- and macro-scale, thereby leveraging the numerical efficiency of the fast Fourier transform (FFT) method at both scales. The application of generic (e.g. non-periodic) boundary conditions at the macro-scale is carried out by using the virtual boundary technique and buffer zones. In addition, the introduction of a clustering algorithm further improves the computational efficiency of the numerical method during the information transfer between scales. To ensure accurate damage prediction and mitigate spurious strain localization at both scales, suitable regularization techniques are employed. The proposed multiscale method is applied to investigate the transverse tension of unidirectional composite dog-bone specimens. After experimental verification, the method is applied to simulate 2D and 3D brittle fracture, elasto-plastic damage, and examples with non-uniform material orientation. The results demonstrate the robustness and adaptability of the clustering approach, which achieves up to 65.90-fold speedup and 81.62-fold reduction in memory usage compared to non-clustered multiscale methods, while maintaining a comparable level of accuracy.
期刊介绍:
Computer Methods in Applied Mechanics and Engineering stands as a cornerstone in the realm of computational science and engineering. With a history spanning over five decades, the journal has been a key platform for disseminating papers on advanced mathematical modeling and numerical solutions. Interdisciplinary in nature, these contributions encompass mechanics, mathematics, computer science, and various scientific disciplines. The journal welcomes a broad range of computational methods addressing the simulation, analysis, and design of complex physical problems, making it a vital resource for researchers in the field.