Scholarlink

<p>Titanium alloys play a crucial role in aerospace, biomedicine, chemical engineering, and marine engineering. Developing a constitutive model for Ti-6Al-4V titanium alloy enables more precise description and prediction of its mechanical properties, thereby providing a robust and reliable theoretical foundation for its production and application. To address the challenge of predicting the mechanical behavior of Ti-6Al-4V titanium alloy under tensile stress, this study carried out tensile tests on Ti-6Al-4V titanium alloy rods at a constant strain rate and temperatures ranging from 25 to 300&#xa0;°C. Through the analysis of microstructural changes in the material following tensile deformation, this study systematically investigated the effects of temperature on both the tensile behavior and fracture characteristics of the material. This study presents a novel constitutive model that combines traditional physical models with deep neural networks. The research findings demonstrate that the novel constitutive model exhibits superior accuracy in predicting the stress variations of Ti-6Al-4V titanium alloy across different temperatures compared to the classical constitutive model. Furthermore, its engineering feasibility has been substantiated through finite element simulations.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Development of a Novel Constitutive Model for Ti-6Al-4V Titanium Alloy Bars Based on Experimental Data and a Hybrid “Shallow” + “Deep” Neural Network Framework

  • 期刊论文

  • 发表日期：

    2025年10月10日

查看全文
  • Haoqing Wang,
  • Dewang Zhao,
  • Hanjie Liu

摘要

Titanium alloys play a crucial role in aerospace, biomedicine, chemical engineering, and marine engineering. Developing a constitutive model for Ti-6Al-4V titanium alloy enables more precise description and prediction of its mechanical properties, thereby providing a robust and reliable theoretical foundation for its production and application. To address the challenge of predicting the mechanical behavior of Ti-6Al-4V titanium alloy under tensile stress, this study carried out tensile tests on Ti-6Al-4V titanium alloy rods at a constant strain rate and temperatures ranging from 25 to 300 °C. Through the analysis of microstructural changes in the material following tensile deformation, this study systematically investigated the effects of temperature on both the tensile behavior and fracture characteristics of the material. This study presents a novel constitutive model that combines traditional physical models with deep neural networks. The research findings demonstrate that the novel constitutive model exhibits superior accuracy in predicting the stress variations of Ti-6Al-4V titanium alloy across different temperatures compared to the classical constitutive model. Furthermore, its engineering feasibility has been substantiated through finite element simulations.