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一种逆向优化方法用于确定Ti6Al4V合金的高温损伤模型和高温损伤图的参数

Xuewen Chen¹, Zhen Yang¹, Bo Zhang¹

¹School of Materials Science and Engineering, Henan University of Science and Technology, 263 Kaiyuan Avenue, Luoyang 471023, China.

Materials (Basel, Switzerland)

|July 14, 2023

概括

这项研究为Ti6Al4V合金开发了精确的热成型损伤模型,这对于防止裂缺陷至关重要. 标准化的Cockcroft和Latham模型在高温制造过程中预测损坏时证明最准确.

科学领域:

材料科学与工程材料科学与工程
机械工程机械工程
计算材料科学科学计算材料科学

背景情况:

合金Ti6Al4V在生物医学和能源领域至关重要.
热成型对于Ti6Al4V制造至关重要,但有可能出现裂缺陷.
需要准确的预测模型来缓解热形成损伤.

研究的目的:

开发和验证Ti6Al4V合金的高温损伤模型.
评估正常化的Cockcroft和Latham (NCL),Oyane和Rice和Tracey (RT) 模型的预测准确性.
使用遗传算法和有限元素分析优化损伤参数.

主要方法:

开发了三种高温损伤模型 (NCL,Oyane,RT) 用于Ti6Al4V.
利用遗传算法与有限元模拟相结合,以确定模型参数.
嵌入式模型在Forge® NxT 2.1软件中进行模拟的热拉力测试 (800-1000°C,0.01-5秒-1).

主要成果:

规范化的Cockcroft和Latham模型在预测裂缺陷方面表现出最高的准确性 (R=0.997).
奥雅内 (R=0.951) 和赖斯和特雷西 (R=0.912) 模型也显示出良好的相关性.
构建了骨折应变和损伤演变图,分析了可形成性与温度和应变速率的对比.

结论:

规范化的Cockcroft和Latham模型在预测Ti6Al4V热形成损伤方面优越.
开发的模型和方法允许准确预测热可塑性和裂缺陷.
这些发现支持在关键应用中改进Ti6Al4V的制造工艺.

关键词:

这是一种Ti6Al4V合金.损伤图表损伤图表高温损伤模型的高温损伤模型反向优化反向优化

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