Comparison of grain growth mean-field models regarding predicted grain size distributions
Mean-field models have the ability to predict grain size distribution evolution occurring through thermomechanical solicitations. This article focuses on a comparison of mean-field models under grain growth conditions. Different microstructure representations are considered and discussed, especially regarding the consideration of topology in the neighborhood construction. Experimental data obtained with a heat treatment campaign on a 316L austenitic stainless steel are used for material parameters identification and as a reference for model comparisons. Mean-field models are also confronted to both mono- and bimodal initial grain size distributions to investigate the interest of introducing neighborhood topology in microstructure predictions models. This article exposes that improvements in the predictions are obtained in monomodal cases for topological models. In bimodal test, no comparison with experimental data were performed as no data were available. But relative comparisons between models indicate few differences in predictions. The interest of neighborhood topology in grain growth mean-field models gives overall small improvements compared to classical mean-field models when comparing implementation complexity.