Image-based data on strain fields of microstructures with porosity defects

Pranav Khanolkar; Saurabh Basu; Christopher McComb

doi:10.1016/j.dib.2020.106627

Image-based data on strain fields of microstructures with porosity defects

Data Brief. 2020 Dec 8:34:106627. doi: 10.1016/j.dib.2020.106627. eCollection 2021 Feb.

Authors

Pranav Khanolkar¹, Saurabh Basu¹, Christopher McComb²

Affiliations

¹ Harold and Inge Marcus Department of Industrial Engineering, The Pennsylvania State University, University Park, PA, USA.
² School of Engineering Design, Technology and Professional Programs, The Pennsylvania State University, University Park, PA, USA.

Abstract

The present article provides a compilation of microstructures and respective strain fields expressed by them during elastic loading. These microstructures were synthesized in Abaqus Standard software and their strain fields were modelled using Abaqus based static implicit analysis. The Python Development Environment (PDE) in Abaqus was used. These microstructures were subjected to uniform displacement boundary condition to obtain strain fields in the plane-strain mode. The purpose of the generating this data was to test the efficacy of convolutional neural networks (CNNs) in predicting strain fields. This raw data consisting of microstructure and their strain fields was converted to images using MATLAB as two dimensional arrays with each pixel denoting value to be used as input for training the CNN. This processed data in the form of images can be potentially used in deep learning or data science methodologies to perform finite element simulations.

Keywords: Finite element analysis; Images; Microstructure; Strain fields.