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Mg-5.21%Li-3.44%Zn-0.32%Y-0.01%Zr型镁锂合金热变形物理过程的数值模拟
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摘要
镁锂合金被称为超轻合金,由于其超轻的特性在工程中有一定的用武之地。锂的加入一定程度上改善了镁合金的塑性变形能力,但对于镁锂合金的热变形过程及机理的探讨还较少,本文结合物理模拟与多种数值方法探讨镁锂合金热变形过程的本构关系以及该过程中材料的晶粒度变化。
     物理模拟采用Gleeble—1500热模拟试验机在真应变为1的条件下选择了250℃、300-C、350-C和400-C4种变形温度和0.001s-1、0.01s-1、0.1s-1、1s-1和10s-15种应变速率对一种镁锂合金进行了热压缩实验。
     合金热变形本构关系建立在热变形物理模拟数据的基础上,建立的方法分别为回归分析以及人工神经网络。通过本构关系的建立确定了镁锂合金的变形激活能、临界应变同Z参数的关系。本构关系说明该合金在所选变形条件下为典型的动态再结晶型变形,所得到的本构方程以及人工神经网络预测结果都能够很好的反映材料的应力应变关系。本构方程对材料加工中各参量关系有更加清楚的描述,神经网络模型则有着更高的精确度。
     根据实验数据及热加工理论建立了材料的临界应变和再结晶尺寸的数学模型。在模型的基础上基于有限元软件Marc通过二次开发建立了有限元模型,并对该合金在热压缩中的温度场、应力应变场尤其是晶粒度的变化进行了模拟研究并与金相检验结果进行了对比,结果说明模拟与实际结果吻合良好。
Magnesium-lithium alloys are called super light alloy, and have certain applications in engineering due to its super light characteristic. The join of lithium improves the plastic deformation ability of magnesium alloy to a certain extent, but it is lesser to discuss hot deformation process and mechanism of magnesium-lithium alloys, this paper discusses constitutive relationship and changes of crystallite size of material in hot deformation process of magnesium-lithium alloys combining with physical simulation and various numerical methods.
     The physical simulation performed hot compression test to a kind of magnesium-lithium alloys using Gleeble-1500 thermal simulation testing machine under the condition of real strain was 1 choosing 250℃、300℃、350℃and 400℃four deformation temperatures and 0.001 s-1、0.01 s-1、0.1 s-1、Is-1、and 10-1 five strain rates.
     Thermal deformation constitutive relationship of alloy based on the physical simulation data of thermal deformation, the methods of establishment were respectively regression analysis and artificial neural networks. Through the establishment of constitutive relationship confirmed the relationship of deformation activation energy, critical strain of magnesium-lithium alloys and Z parameters. The constitutive relationship illustrated the deformation of alloy was dynamic recrystallization type under the condition of choosing deformation, the obtained constitutive equation and results predicted by artificial neural network can reflect the stress-strain relationship of material well. The constitutive equation has more clear description for the relationships between each parameter in material processing, while neural network model has a higher accuracy.
     Critical strain and recrystallization size mathematical model of material established according to the experimental data and hot-working theory. Finite element model established based on finite element software Marc through the secondary development on the bases of model, and the temperature field and stress strain field particularly the changes of crystallite size of the alloy in hot compress were simulated and compared with metallographic examination results, the results show that the simulation results are in good agreement with the experimental results.
引文
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