Microstructure and property based statistically equivalent RVEs for intragranular γ−γ' microstructures of Ni-based superalloys

Abstract This paper develops statistically equivalent RVEs or SERVEs for intragranular microstructures of Ni-based superalloys, characterized by γ - γ ' phase distribution. The SERVE represents an optimal computational domain to be used for micromechanical simulations for effective properties or response variables in the microstructure. The SERVE is further classified as a microstructure-based SERVE or M-SERVE or property-based SERVE or P-SERVE , depending on whether the statistics of morphological characteristics or convergence of chosen material properties are its determinants. Starting from FIB-SEM data for the superalloy Rene 88DT, the paper systematically develops a host of algorithms for generating validated statistically equivalent virtual microstructures, from which the M-SERVE is estimated from convergence of selected morphological and spatial distributions. Subsequently the P-SERVEs are established for global properties like yield strength and hardening rate, and local variables including dislocation density and the maximum resolved shear stress. Spatially-averaged quantities are found to converge quicker than the local distributions for both M-SERVE and P-SERVE.