{"title":"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","authors":"Jing Wang, Qiang Liang, Yan Li","doi":"10.1016/j.jsamd.2024.100777","DOIUrl":null,"url":null,"abstract":"<div><p>The high temperature flow data of TiB<sub>2</sub>/2024 aluminum matrix composites (referred to as TiB<sub>2</sub>/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<sup>−1</sup>, 0.1s<sup>−1</sup>, 1s<sup>−1</sup>, and 10s<sup>−1</sup>), and a maximum deformation of 60%. By comprehensively accounting for the deformation conditions, the relationships between the material parameters <em>α</em>, <em>n</em>, <em>S</em>, <em>f</em> of TiB<sub>2</sub>/2024 alloy and the deformation temperature, strain, and strain rate were determined, leading to the modification of the Arrhenius model. A constitutive model for TiB<sub>2</sub>/2024 alloy was constructed using the Gene expression programming (GEP) approach. The flow stress of TiB<sub>2</sub>/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 TiB<sub>2</sub>/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.</p></div>","PeriodicalId":17219,"journal":{"name":"Journal of Science: Advanced Materials and Devices","volume":"9 4","pages":"Article 100777"},"PeriodicalIF":6.7000,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468217924001084/pdfft?md5=652fe7d25dd78fd3f643841d7528693a&pid=1-s2.0-S2468217924001084-main.pdf","citationCount":"0","resultStr":"{\"title\":\"The flow stress prediction of TiB2/2024 aluminum matrix composites based on modified Arrhenius model and gene expression programming model\",\"authors\":\"Jing Wang, Qiang Liang, Yan Li\",\"doi\":\"10.1016/j.jsamd.2024.100777\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The high temperature flow data of TiB<sub>2</sub>/2024 aluminum matrix composites (referred to as TiB<sub>2</sub>/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<sup>−1</sup>, 0.1s<sup>−1</sup>, 1s<sup>−1</sup>, and 10s<sup>−1</sup>), and a maximum deformation of 60%. By comprehensively accounting for the deformation conditions, the relationships between the material parameters <em>α</em>, <em>n</em>, <em>S</em>, <em>f</em> of TiB<sub>2</sub>/2024 alloy and the deformation temperature, strain, and strain rate were determined, leading to the modification of the Arrhenius model. A constitutive model for TiB<sub>2</sub>/2024 alloy was constructed using the Gene expression programming (GEP) approach. The flow stress of TiB<sub>2</sub>/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 TiB<sub>2</sub>/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.</p></div>\",\"PeriodicalId\":17219,\"journal\":{\"name\":\"Journal of Science: Advanced Materials and Devices\",\"volume\":\"9 4\",\"pages\":\"Article 100777\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2024-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2468217924001084/pdfft?md5=652fe7d25dd78fd3f643841d7528693a&pid=1-s2.0-S2468217924001084-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Science: Advanced Materials and Devices\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468217924001084\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Science: Advanced Materials and Devices","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468217924001084","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
The flow stress prediction of TiB2/2024 aluminum matrix composites based on modified Arrhenius model and gene expression programming model
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.
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.