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Modelling of microstructure and mechanical properties of steel using the artificial neural network

机译:使用人工神经网络对钢的显微组织和力学性能进行建模

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摘要

The paper presents some results of the research connected with the development of new approach based on the artificial intelligence of predicting the volume fraction and mean size of the phase constituents occurring in a steel after thermomechanical processing and cooling. The independent variables in the model are austenite grain size and cooling rate over the temperature range of the occurrence of phase transformations. The dependent parameters are proeutectoid ferrite, Widmanstatten ferrite and pearlite fractions as well as ferrite grain size. Furthermore, a preliminary model for the prediction of mechanical properties was elaborated based upon the same idea.
机译:本文介绍了基于人工智能的新方法开发的一些研究成果,该方法可预测热机械加工和冷却后钢中出现的相成分的体积分数和平均尺寸。模型中的自变量是在发生相变的温度范围内的奥氏体晶粒尺寸和冷却速率。相关参数是原共析铁素体,Widmanstatten铁素体和珠光体部分以及铁素体晶粒尺寸。此外,基于相同的想法,建立了用于预测机械性能的初步模型。

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