Texture Prediction of Cold- and Hot-Rolled Titanium Using Processing Path Model

Abstract

Titanium alloys have very attractive properties, which are highly dependent on the material microstructure. Accurately predicting the microstructure of such materials during processing for materials design is, therefore, very important. In this study, texture evolution of titanium alloys cold rolled at room temperature and hot rolled at 260 °C is simulated using a processing path model. Texture coefficients, a set of weights in spherical harmonics expansion of texture, are utilized as descriptors of materials to represent the texture state of polycrystalline materials during processing. This model is based on the conservation principle in the orientation space. Deriving from experimental texture input at different deformation stages, the texture evolution matrix was calculated. This matrix is used to predict texture evolution for the specified deformation mode. The simulated texture evolution results agree well with experimental results.