This paper discusses the most relevant multiscale models for predicting crystallographic textures formed during the primary static recrystallization of metals. Two main groups of approaches are presented, namely those which spatially discretize the grains and the interface motion associated with recrystallization and those which treat these phenomena in an Avrami-type statistical fashion. The article gives a concise review of the methods, placing particular attention on their strengths and weaknesses in the context of process modelling, of conceptual aspects, and of the data sets required as input for practically applying the models to the prediction of crystallographic textures in the course of metallurgical processes.
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