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Prediction of Stress-Strain Behaviors in Steels Using an Integrated Constitutive, FEM and ANN Model

机译:应用本构,有限元和人工神经网络模型预测钢的应力-应变行为

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摘要

Austenitic steels with a carbon content of 0.0037 to 0.79 wt/100C are torsion tested and modeled using a physically based constitutive model and an Integrated Phenomenological and Artificial neural Network (IPANN) model. The prediction of both the constitutive and IPANN models on steel 0.017 wt/100 C is then evaluated using a finite element (FEM) code ABAQUS with different reduction in the thickness after rolling through one roll stand.
机译:使用基于物理的本构模型和综合现象学与人工神经网络(IPANN)模型对碳含量为0.0037至0.79 wt / 100C的奥氏体钢进行扭转测试和建模。然后使用有限元(FEM)代码ABAQUS评估在0.017 wt / 100 C的钢上的本构模型和IPANN模型的预测,该模型在通过一个轧机机架轧制后厚度会有所不同。

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