期刊论文

Peng, X;Jia, WQ

英文

Polymer Composites

0272-8397

2025

10.1002/pc.30048

This work was supported by the National Natural Science Foundation of China (grant numbers 51875525, 52275235), the Zhejiang Provincial Natural Science Foundation of China (grant numbers LY21E050008, LHZ22F020001), and Fundamental Research Funds for the Provincial Universities of Zhejiang (RF-B2024004).

本校为其他机构

Predicting the full-field stress distribution has important significance in analyzing mechanical characteristics of composite materials. Numerical calculations of stress field distribution using finite element analysis (FEA) can call for significant computational effort for microscale geometries. To address this challenge, this paper demonstrates a deep learning (DL) framework for predicting local stress distributions in fiber-reinforced composites with diverse fiber volume fractions. An adaptive generation algorithm of representative volume element (RVE) microstructures is developed for const...