首页> 外文期刊>Journal of Materials Engineering and Performance >Constitutive Modeling of the Hot Deformation Behavior in 6082 Aluminum Alloy
【24h】

Constitutive Modeling of the Hot Deformation Behavior in 6082 Aluminum Alloy

机译:6082铝合金热变形行为的组成型建模

获取原文
获取原文并翻译 | 示例
           

摘要

The hot compressive tests of 6082 aluminum alloy were conducted on a Gleeble-3500 thermomechanical simulator at temperature ranges of 380-530 degrees C and strain rate range of 0.01-10s(-1). The constitutive analysis and microstructural evolution of the alloy were investigated. It was indicated that the peak stress increased with increasing strain rate and decreasing temperature. Dynamic recovery and dynamic recrystallization lead to the softening behavior of the alloy. In order to characterize the flow behavior of this alloy, some models were established based on the experimental data including the phenomenological Arrhenius-type model, the physically based Estrin and Mecking (EM) model for work hardening and dynamic recovery, and the EM model, which was combined with the Avrami equation for dynamic recrystallization. An artificial neural network model was also established to predict the flow stress. The results indicate that the Arrhenius-type model is more simple and more efficient than the EM+Avrami model. Moreover, the well-trained ANN model has the best predicting performance.
机译:6082铝合金的热压缩试验在GLEEBLE-3500热机械模拟器上进行,温度范围为380-530℃,应变率范围为0.01-10s(-1)。研究了合金的组成型分析和微观结构演化。结果表明,随着应变率的增加和温度降低,峰值应力增加。动态回收和动态再结晶导致合金的软化行为。为了表征这种合金的流动性能,基于包括现象学arrhenius型模型,物理上的雌激素和熔化(EM)模型的实验数据建立了一些模型,用于工作硬化和动态恢复,以及EM模型,这与AVRAMI方程组合进行动态再结晶。还建立了一种人工神经网络模型以预测流量应力。结果表明,Arrhenius型模型比EM + AVRAMI模型更简单且更高效。此外,训练有素的ANN模型具有最佳的预测性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号