@article {1456, title = {Microstructure and property based statistically equivalent RVEs for intragranular γ-γ{\textquoteright} microstructures of Ni-based superalloys}, journal = {Acta Materialia}, volume = {157}, year = {2018}, pages = {245{\textendash}258}, abstract = {

This paper develops statistically equivalent RVEs or SERVEs for intragranular microstructures of Ni-based superalloys, characterized by \γ-\γ\&$\#$39; 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 Ren\é 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.

}, keywords = {M-SERVE, Ni-based superalloys, P-SERVE, SEVM, Two-point correlation function, γ-γ{\textquoteright} distribution}, issn = {13596454}, doi = {10.1016/j.actamat.2018.07.034}, url = {https://doi.org/10.1016/j.actamat.2018.07.034}, author = {Pinz, M. and Weber, G. and Lenthe, W. C. and Uchic, M. D. and Pollock, T. M. and Ghosh, S.} }