Process-informed material model selection

Abstract

Abstract. The efficient development of metal products with high quality usually requires realistic numerical simulations before the manufacturing procedure. The choice of the constitutive model has a considerable influence on the predicted material behavior’s description. Several material constitutive models have been proposed to describe different mechanical phenomena. However, its selection is a labored task that requires expertise. This lack of knowledge can lead to errors in the numerical predictions and, consequently, large costs and delays in the manufacturing procedure. To overcome this problem, an automatic material model selection tool is necessary. This work aims to compare the impact of different constitutive models and their features on the simulation of a forming process and develop a rational and systematic strategy for model selection. The approach focuses on the study of a hole expansion test using Abaqus and a statistical analysis of variance (ANOVA). It was possible to establish a ranking for the importance of the types of models that can help with model selection decision-making and efficient parameter calibration for accurate predictions.