Data-driven approach for efficient multiscale damage analysis of fiber reinforced composites

被引：0

作者：

Ma, Penghui ^{[1
]}

Hu, Dianyin ^{[2
,3
,4
]}

Liu, Xi ^{[1
,3
,4
]}

Liu, Yu ^{[1
]}

Wang, Rongqiao ^{[1
,3
,4
]}

机构：

[1] School of Energy and Power Engineering, Beihang University, Beijing

[2] Research Institute of Aero-Engine, Beihang University, Beijing

[3] United Research Center of Mid-Small Aero-Engine, Beijing

[4] Beijing Key Laboratory of Aero-Engine Structure and Strength, Beihang University, Beijing

来源：

Hangkong Dongli Xuebao/Journal of Aerospace Power | 2025年 / 40卷 / 07期

关键词：

composites; data-driven; general method of cells model; multiscale simulation; neural networks;

D O I：

10.13224/j.cnki.jasp.20230051

中图分类号：

学科分类号：

摘要：

In order to realize the damage analysis of fiber reinforced composites， an efficient multiscale damage analysis method is developed. Firstly， based on the generalized method of cells， a multiscale damage analysis framework is constructed for laminate and plain weave composites， and the damage processes at the mesoscale and microscale under uniaxial tension are analyzed， The results show that the complex weave structure of plain weave composites leads to a more complex mesoscale and microscale damage evolution process， which is significantly different from the damage process of laminates. Based on this， neural networks are introduced， and a data-driven multiscale damage analysis strategy is proposed to realize the efficient damage simulation of plain weave composites. Compared with the experimental and simulant results， the error of predicting tensile strength by the efficient multiscale damage analysis method is less than 7%; and compared with traditional multiscale damage analysis method，the efficiency of macroscale calculations can be improved by about 12.47 times. © 2025 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.

引用

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