程彬洋,刘祥,芦俊杰,等.Al-Zn合金热成形本构模型[J].精密成形工程,2022,14(4):11-19.
CHENG Bin-yang,LIU Xiang,LU Jun-jie,et al.Constitutive Model of Al-Zn Alloy Hot Forming[J].Journal of Netshape Forming Engineering,2022,14(4):11-19. |
| Al-Zn合金热成形本构模型 |
| Constitutive Model of Al-Zn Alloy Hot Forming |
| 投稿时间：2022-01-07 |
| DOI：10.3969/j.issn.1674-6457.2022.04.002 |
| 中文关键词: 预时效强化温热成形工艺 Al-Zn合金 本构模型 |
| 英文关键词: pre-aged hardening warm forming (PHF) process Al-Zn alloy constitutive model |
| 基金项目:国家重点研发计划(2019YFB1704500);国家自然科学基金(52075400);湖北省重点研发计划(2020BAB140) |
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| 中文摘要: |
| 目的 表征Al-Zn合金在预时效强化温热成形工艺下的流动行为。方法 利用MMS200热模拟机对Al-Zn合金进行热拉伸试验，变形参数分别为变形温度180~220 ℃、应变速率0.01~1 s−1。通过对试验值进行修正，可得到不同变形条件下的真应力-应变曲线，并建立应变补偿的含Z参数本构模型和PSO-BP人工神经网络本构模型。结果 Al-Zn合金热变形过程中呈现正的应变速率敏感性和热软化效应;应变补偿的含Z参数本构模型的R值和EAARE值分别为0.961和8.761%;而PSO-BP人工神经网络本构模型的R值和EAARE值分别为0.993 5和2.51%。结论 PSO-BP人工神经网络本构模型的预测值和试验值高度吻合，拥有更准确、更快速的数据采集和分析能力，对铝合金及其他合金材料的热变形行为预测有着重要意义。 |
| 英文摘要: |
| The work aims to characterize the flow behavior of Al-Zn alloy under the proposed pre-aged hardening warm forming (PHF) process. A MMS200 thermal simulator was used to conduct a hot tensile test on Al-Zn alloy. For deformation parameters, the deformation temperature was 180~220 ℃, and the strain rate was 0.01~1 s−1. By correcting the test values, the true stress-strain curves under different deformation conditions can be obtained, and a strain-compensated constitutive model with Z parameters and a PSO-BP artificial neural network constitutive model can be established. The Al-Zn alloy showed positive strain rate sensitivity and thermal softening effect during the hot deformation process; the R value and EAARE value of the strain-compensated Z-parameter constitutive model were 0.961 and 8.761%, respectively; while the R value and EAARE value of the PSO-BP artificial constitutive model were 0.993 5 and 2.51%, respectively. The PSO-BP artificial neural network constitutive model shows a high degree of agreement between the predicted value and the experimental value, and has more accurate and faster data collection and analysis capabilities, which is of great significance to the prediction of the hot deformation behavior of aluminum alloys and other alloy materials. |
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