Grain reconstruction and determination of grain attributes from MD data sets of FCC polycrystals

Abstract

International audienceAn algorithm for the identification and reconstruction of crystallites from molecular dynamics data sets of FCC materials was developed. The algorithm was tested in an Al polycrystal possessing a weak texture. For the conditions tested, the algorithm was able to find all of the input orientations and reconstruct the grains according to their crystallographic orientation. The method is capable of calculating specific attributes of grains, namely, volume, center of mass, average orientation and orientation spread. The method additionally provides a mapping method to track grains during time-row dataset. The software uses shared-memory parallelization implemented by the use of the OpenMP-API, which enables a fast analysis of large volumes of data with excellent performance