The flow stress prediction of TiB2/2024 aluminum matrix composites based on modified Arrhenius model and gene expression programming model

材料科学 基因表达程序设计 复合材料 阿累尼乌斯方程 基质(化学分析) 压力(语言学) 流量(数学) 活化能 机械 计算机科学 有机化学 语言学 机器学习 物理 哲学 化学
作者
Jing Wang,Qiang Liang,Yan Li
出处
期刊:Journal of Science: Advanced Materials and Devices [Elsevier BV]
卷期号:9 (4): 100777-100777 被引量:3
标识
DOI:10.1016/j.jsamd.2024.100777
摘要

The high temperature flow data of TiB2/2024 aluminum matrix composites (referred to as TiB2/2024 alloy) was investigated using a Gleeble-3500 thermal simulation testing machine. The experiments were conducted at various deformation temperatures (573 K, 623 K, 673 K, and 723 K), strain rates (0.01s−1, 0.1s−1, 1s−1, and 10s−1), and a maximum deformation of 60%. By comprehensively accounting for the deformation conditions, the relationships between the material parameters α, n, S, f of TiB2/2024 alloy and the deformation temperature, strain, and strain rate were determined, leading to the modification of the Arrhenius model. A constitutive model for TiB2/2024 alloy was constructed using the Gene expression programming (GEP) approach. The flow stress of TiB2/2024 alloy during the compression process was predicted using both the modified Arrhenius model and the GEP model. The statistical analysis was performed to evaluate the prediction accuracy of the two models, and the extended stress-strain data was implemented in finite element simulations of the hot compression process. The results indicate that the flow stress of TiB2/2024 alloy is significantly affected by the strain rate and temperature during the deformation process. The flow stress decreases with increasing temperature and increases with increasing strain rate. Both the modified Arrhenius model and the GEP model can effectively predict the alloy's flow stress. However, the modified Arrhenius model exhibits greater prediction accuracy than the GEP model.
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