Modeling of grain boundary character reconstruction and predicting intergranular fracture susceptibility of textured and random polycrystalline materials

A grain boundary character reconstruction model has been developed that can reproduce the experimentally determined grain boundary character distribution (GBCD) from the simple texture and overall GBCD descriptions. It is based on defining the texture intensity by Gaussian half-width, orientation exchange of the grains, and Monte Carlo simulations. Subsequently, this model has been integrated with a Voronoi microstructure based Markov Chain–Monte Carlo algorithm to evaluate the intergranular fracture susceptibility of polycrystalline materials. The character dependent individual grain boundary fracture strength and the projected local stress on the grain boundary plane were considered in the crack-propagation decision strategy. The predicted threshold fracture stress has been compared with the experimental fracture stress data of both fiber and random textured polycrystals available in the literature, and good agreement was observed. Besides, it has been shown that the overall GBCD could be a misleading parameter in predicting the relative fracture strengths of different types of specimens and how a texture-based grain boundary character reconstruction model can help overcome this difficulty by assessing the true fraction of special grain boundaries in a given microstructure. The effect of grain shape on relative change of fracture stress has been also quantitatively presented and discussed.