Characterization of hot flow behaviour and deformation stability of medium carbon microalloyed steel using artificial neural networks and dynamic material model

Artificial neural network (ANN) and dynamic material model (DMM) are considered to be powerful methods to characterize the flow behaviour of metallic materials. The aim of this study is to analyze the performance of these two methods in the characterization of flow behaviour and deformation stability of medium-carbon microalloyed steel. Flow curves obtained from hot compression tests have been used to describe the flow behaviour of the studied steel using an ANN model. Good correlation between experimental and predicted data was observed. To characterize the deformation stability of the studied steel, experimental processing maps are generated using DMM. Finally, in order to verify the accuracy of ANN results, processing maps based on the DMM have been developed using ANN predicted data. It has been found that these maps agree closely with those obtained using experimental data.