含能材料2026，Vol.34Issue(4)：350-358,9.DOI:10.11943/CJEM2026007
基于结构化生成对抗模型的类铜密度含能高熵合金体系设计及性能预测
Composition Design and Property Optimization on High-entropy Alloys with Copper-like Density Based on Structured Generative Adversarial Networks
摘要
Abstract
High-entropy alloys break the design limitations of traditional metal material component systems,greatly expand the application space of metal material component lineage and performance design and engineering,and the generative model de-sign method provides a new technical means for the design and performance prediction of high-entropy alloy systems.In this pa-per,a structured generative adversarial model composed of Maximum Mean Difference Variational Autoencoder(MMD-VAE)and Wasserstein Generative Adversarial Network with Gradient Penalty(WGAN-GP)is established,and three new energetic high-entropy alloy systems are generated by learning the performance parameters of three types of NbTaW energetic high-entropy alloys,and the energy density of the material system under the constraint of copper-like density is taken as the core index,and their energy density characteristics are predicted and analyzed.The results show that the accuracy of the structured generative adversarial model for the design and performance prediction of energetic high-entropy alloy systems is significantly better than that of the single MMD-VAE model algorithm,with an overall coefficient of determination of 0.7326 and a root mean square error of 0.0540,the accuracy of the generated data is balanced.This paper provides an efficient and reliable model meth-od for the design and performance prediction of energetic high-entropy alloys of the new system.关键词
高熵合金/生成模型/体系设计/性能预测Key words
high-entropy alloys/generative models/system design/performance prediction分类
军事科技引用本文复制引用
吕博宇,李顺平,高睿林,葛超..基于结构化生成对抗模型的类铜密度含能高熵合金体系设计及性能预测[J].含能材料,2026,34(4):350-358,9.基金项目
国家自然科学基金(12302460,12132003)National Natural Science Foundation of China(Nos.12302460,12132003) （12302460,12132003）
