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Prediction of Hot Strength of Steels with Advanced Models

机译：用高级模型预测钢的热强度

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摘要

It has been difficult to accurately predict hot strength of steels in order to control the quality of rolled steel strips, as the hot strength varies in a complicated way with deformation conditions such as strain, temperature, and strain rate, and steel compositions ie carbon contents. In this work, advanced models are used to predict the stress-strain behavior of austenitic steels with a carbon content ranging from 0.0037 to 0.79wt%. The models include a constitutive model, a finite element model, artificial neural networks, and a hybrid model by integrating these three models. The prediction accuracy is analyzed and the prediction of the hot strength in both work hardening and dynamic recrystallization zones by these models is compared.
机译：难以准确预测钢的热强度以控制轧制钢带的质量，因为热强度会随变形条件（例如应变，温度和应变率）以及钢成分（即碳含量）以复杂的方式变化。在这项工作中，使用高级模型来预测碳含量为0.0037至0.79wt％的奥氏体钢的应力应变行为。这些模型包括本构模型，有限元模型，人工神经网络和通过整合这三个模型的混合模型。分析了预测精度，并比较了这些模型对加工硬化和动态再结晶区中热强度的预测。

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