Inverse modeling of inelastic properties of a two-phase microstructure

The prediction ofmaterial propertieswith the inclusion ofmorphology has been an area of increasing interest formaterial scientists in the past decades. A myriad of statistical continuummechanics formulations have been developed to investigate the properties of a two-phase microstructure given its morphology. In this study, the structure-propertymodel is inverted to create an inverse microstructure model for a two-phase Ti64 material to predict the microstructure required to achieve a desired property. For this purpose, an inverse formulation is developed using the two-point correlation function representation of the microstructure within the statistical continuum framework. Using this formulation the initial microstructure is then predicted by knowing a desired strength. This approach calculates the optimumvalues of the two-point probability functionswhich are associated with theminimumerror in the predicted strength with respect to the desired strength. Finally, 2D microstructures are reconstructed using the predicted values of the two-point probability functions to represent the morphology of the initial microstructure at four different temperatures of Ti64 (850, 900, 950, 1000 °C).