A dataset of synthetic face centered cubic 3D polycrystalline microstructures, grain-wise microstructural descriptors and grain averaged stress fields under uniaxial tensile deformation

This data article presents a data set comprised of 36 synthetic 3D equiaxed polycrystalline microstructures, the microstructural descriptors for each grain, and the stress and strain fields resulting from crystal plasticity simulations mimicking uniaxial tensile deformation to a total strain of 4%. This is related to the research article entitled “Applied Machine Learning to predict stress hotspots I: Face Centered Cubic Materials” (Mangal and Holm, 2018) [1]. The microstructures were created using an open source Dream.3D software tool, and the crystal plasticity simulations were carried out using the elasto-viscoplastic fast Fourier transform (EVPFFT) method. Six different kinds of FCC textures are represented with six stochastically different microstructures with varying texture intensity for each texture kind. This dataset is freely available in a Mendeley Data archive “A dataset of synthetic face centered cubic 3D polycrystalline microstructures, grain-wise microstructural descriptors and grain averaged stress fields under uniaxial tensile deformation” located at 〈http://dx.doi.org/10.17632/ss75fdg5dg.1〉 for any academic, educational, or research purposes.