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

IF 6.7 3区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY Journal of Science: Advanced Materials and Devices Pub Date : 2024-09-14 DOI:10.1016/j.jsamd.2024.100777
Jing Wang, Qiang Liang, Yan Li
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Abstract

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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基于修正阿伦尼斯模型和基因表达编程模型的 TiB2/2024 铝基复合材料流动应力预测
使用 Gleeble-3500 热模拟试验机研究了 TiB2/2024 铝基复合材料(简称 TiB2/2024 合金)的高温流动数据。实验在不同的变形温度(573 K、623 K、673 K 和 723 K)、应变速率(0.01s-1、0.1s-1、1s-1 和 10s-1)和 60% 的最大变形下进行。通过综合考虑变形条件,确定了 TiB2/2024 合金的材料参数 α、n、S、f 与变形温度、应变和应变率之间的关系,从而修正了阿伦尼乌斯模型。利用基因表达编程(GEP)方法构建了 TiB2/2024 合金的构成模型。使用修正的阿伦尼斯模型和 GEP 模型预测了 TiB2/2024 合金在压缩过程中的流动应力。通过统计分析评估了两种模型的预测精度,并将扩展的应力应变数据用于热压缩过程的有限元模拟。结果表明,在变形过程中,TiB2/2024 合金的流动应力受到应变速率和温度的显著影响。流动应力随温度升高而减小,随应变率升高而增大。修正的 Arrhenius 模型和 GEP 模型都能有效预测合金的流动应力。但是,修正的 Arrhenius 模型比 GEP 模型的预测精度更高。
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来源期刊
Journal of Science: Advanced Materials and Devices
Journal of Science: Advanced Materials and Devices Materials Science-Electronic, Optical and Magnetic Materials
CiteScore
11.90
自引率
2.50%
发文量
88
审稿时长
47 days
期刊介绍: In 1985, the Journal of Science was founded as a platform for publishing national and international research papers across various disciplines, including natural sciences, technology, social sciences, and humanities. Over the years, the journal has experienced remarkable growth in terms of quality, size, and scope. Today, it encompasses a diverse range of publications dedicated to academic research. Considering the rapid expansion of materials science, we are pleased to introduce the Journal of Science: Advanced Materials and Devices. This new addition to our journal series offers researchers an exciting opportunity to publish their work on all aspects of materials science and technology within the esteemed Journal of Science. With this development, we aim to revolutionize the way research in materials science is expressed and organized, further strengthening our commitment to promoting outstanding research across various scientific and technological fields.
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