Modelling of the Steel High-Temperature Deformation Behaviour Using Artificial Neural Network

Hot forming is an essential part of the manufacturing most steel products. The hot deformation behaviour determined by temperature, strain rate, and chemical composition steel. To date, constitutive models are constructed for many steels; however, their specific limits application. In this paper, a novel artificial neural network (ANN) model was built to determine flow stress with high accuracy in wide range concentration elements high-alloyed, corrosion-resistant steels. additional compression tests stainless Cr12Ni3Cu were carried out at rates 0.1–10 s−1 temperatures 900–1200 °C using thermomechanical simulator Gleeble 3800. ANN-based showed both training (the error 6.6%) approvement (11.5%) datasets. values effective activation energy experimental (410 ± 16 kJ/mol) predicted peak (380 29 good agreement. implementation significant influence variation within grade on steady state deformation.