Modeling and prediction of hot deformation flow curves

Abstract

The modeling of hot flow stress and prediction of flow curves for unseen deformation conditions are important in metal-forming processes because any feasible mathematical simulation needs accurate flow description. In the current work, in an attempt to summarize, generalize, and introduce efficient methods, the dynamic recrystallization (DRX) flow curves of a 17-4 PH martensitic precipitation hardening stainless steel, a medium carbon microalloyed steel, and a 304 H austenitic stainless steel were modeled and predicted using (1) a hyperbolic sine equation with strain dependent constants, (2) a developed constitutive equation in a simple normalized stress-normalized strain form and its modified version, and (3) a feed-forward artificial neural network (ANN). These methods were critically discussed, and the ANN technique was found to be the best for the modeling available flow curves; however, the developed constitutive equation showed slightly better performance than that of ANN and significantly better predicted values than those of the hyperbolic sine equation in prediction of flow curves for unseen deformation conditions.