Prediction of the effective properties of matrix composites via micromechanics-based machine learning

IF 5.7 1区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

International Journal of Engineering Science Pub Date : 2025-02-01 DOI:10.1016/j.ijengsci.2024.104184

E. Polyzos

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Abstract

This study aims to integrate micromechanics-based analytical models with machine learning (ML) models to predict the effective properties of two-phase composites. A novel approach grounded in Maxwell’s effective field method (EFM) is proposed to address the accuracy limitations inherent in micromechanics-based models while minimizing the amount of data needed to fit ML models. Notably, this new approach requires only two macroscale data points to predict the effective properties. The approach is introduced for inhomogeneities of arbitrary shape, orientation, and properties and is applicable to effective thermal, electrical, elastic, and other properties. Two case studies focusing on the elasticity problem are presented to illustrate the applicability and accuracy of the new approach; one involving a particulate composite of copper reinforced with diamond particles, and the other a unidirectional composite of 3D-printed nylon reinforced with Kevlar fibers. The results of these case studies are compared with finite element models and demonstrate an excellent agreement.

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基于微力学的机器学习预测基体复合材料的有效性能

本研究旨在将基于微观力学的分析模型与机器学习（ML）模型相结合，以预测两相复合材料的有效性能。提出了一种基于麦克斯韦有效场方法（EFM）的新方法，以解决基于微力学的模型固有的精度限制，同时最大限度地减少拟合ML模型所需的数据量。值得注意的是，这种新方法只需要两个宏观数据点来预测有效性质。该方法适用于任意形状、取向和性质的非均匀性，适用于有效的热学、电学、弹性和其他性质。以弹性问题为例，说明了该方法的适用性和准确性；一种是用金刚石颗粒增强的铜颗粒复合材料，另一种是用凯夫拉纤维增强的3d打印尼龙的单向复合材料。将这些算例的结果与有限元模型进行了比较，结果表明两者非常吻合。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Engineering Science 工程技术-工程：综合

CiteScore

11.80

自引率

16.70%

发文量

审稿时长

45 days

期刊介绍： The International Journal of Engineering Science is not limited to a specific aspect of science and engineering but is instead devoted to a wide range of subfields in the engineering sciences. While it encourages a broad spectrum of contribution in the engineering sciences, its core interest lies in issues concerning material modeling and response. Articles of interdisciplinary nature are particularly welcome. The primary goal of the new editors is to maintain high quality of publications. There will be a commitment to expediting the time taken for the publication of the papers. The articles that are sent for reviews will have names of the authors deleted with a view towards enhancing the objectivity and fairness of the review process. Articles that are devoted to the purely mathematical aspects without a discussion of the physical implications of the results or the consideration of specific examples are discouraged. Articles concerning material science should not be limited merely to a description and recording of observations but should contain theoretical or quantitative discussion of the results.