4.3 Article

VAMPYR: A MATLAB-Based Toolset Leveraging MTEX for Automating VPSC

Journal

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s40192-023-00308-4

Keywords

Crystal plasticity; Viscoplastic self-consistent model; ICME; Application programming interface

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Mean-field crystal plasticity models, such as the viscoplastic self-consistent (VPSC) model, play a crucial role in metallurgy, particularly in integrated computational materials engineering. Among these models, VPSC is widely used due to its high computational efficiency, which enables high-throughput investigations of texture evolution and simplifies integration into multiscale models. However, the original FORTRAN implementation of VPSC, with its plaintext interface, poses challenges for new users and makes high-throughput simulations difficult to set up.
Mean-field crystal plasticity models, like the viscoplastic self-consistent (VPSC) model, are an important component of the integrated computational materials engineering (ICME) workflow in metallurgy. Their computational efficiency in comparison to full-field models enables high-throughput investigations of texture evolution and simplifies integration into multiscale models. VPSC, being arguably the most ubiquitous of these models, is both a powerful tool for experienced computational researchers and a common entry point to simulations for primarily experimental metallurgists. The original FORTRAN implementation of VPSC has a plaintext interface that causes challenges for new users and makes high-throughput VPSC simulations difficult to set up. In this work, a MATLAB-based application programming interface (API) making use of the MTEX crystallographic toolbox is developed in order to provide an intuitive, script-based interface for VPSC. Named VPSC Automation in MTEX for Polycrystal plasticitY Research (VAMPYR) (VPSC Automation in MTEX for Polycrystal plasticitY Research), the API encourages a workflow which enables quick development of high-throughput experiments or multiscale models using VPSC; VAMPYR also includes ease-of-use functions for extracting input data from experimental sources and generating data visualizations of simulation results. An example case of optimizing Voce hardening law parameters to match experimental stress-strain curves demonstrates the process of developing a script to run VPSC using the API.

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