爆炸与冲击2026，Vol.46Issue(5)：30-45,16.DOI:10.11883/bzycj-2025-0259
基于深度学习的亚稳态高熵合金高应变率冲击响应预测
Deep learning-based prediction of high-strain-rate shock response in metastable high-entropy alloys
摘要
Abstract
Metastable high-entropy alloys(HEA)have attracted considerable attention due to their exceptional mechanical properties at high strain rates.However,their engineering applications under high strain rates are limited,which stems from an inadequate understanding of the relationship between microstructure and impact response.An end-to-end deep learning framework has been implemented,combining the crystal plasticity finite element(CPFE)method with a convolutional neural network(CNN)to elucidate the mapping between microstructure and shock response.A crystal plasticity constitutive model,which couples dislocation slip and martensitic transformation mechanisms,has been developed and validated against experimental results,confirming the model's effectiveness.Based on this constitutive model,a dataset for training the deep learning model is generated,including the complete stress-strain response and martensite volume fraction evolution of metastable HEA with corresponding textures and loading conditions at high strain rates.The two-branch CNN model is used to extract microstructural features.Its input is microstructural information in image format and loading conditions,and its output consists of two branches corresponding to stress-strain curves and the evolution of martensite volume fraction.The collected dataset was used to train the CNN model.The results show that the model can accurately predict the shock response of metastable HEA under high strain rate conditions.This study demonstrates that the deep learning framework,while maintaining predictive accuracy,offers a significant computational efficiency advantage over CPFE simulations.It provides a novel approach for efficiently assessing the mechanical behavior of metastable high-entropy alloys under high strain rates.关键词
深度学习/冲击响应/晶体塑性/亚稳态高熵合金Key words
deep learning/shock response/crystal plasticity/metastable high-entropy alloy分类
数理科学引用本文复制引用
刘传志,安稳,熊启林..基于深度学习的亚稳态高熵合金高应变率冲击响应预测[J].爆炸与冲击,2026,46(5):30-45,16.基金项目
国家自然科学基金(12522216) （12522216）
冲击波物理与爆轰物理全国重点实验室基金(2023JCJQLB05403) （2023JCJQLB05403）
