Phase Field Benchmark Problems for Dendritic Growth and Linear Elasticity

TL;DR

This paper introduces standardized benchmark problems for phase field models to evaluate their accuracy and computational performance in simulating microstructure evolution, specifically dendritic growth and elastic shape changes.

Contribution

It presents the second set of benchmark problems for phase field models, facilitating consistent evaluation of algorithms in materials design simulations.

Findings

Demonstrated sensitivity of benchmarks to different numerical parameters

Compared results of dendritic growth with various time integrators

Analyzed elastic precipitate simulations with different conditions

Abstract

We present the second set of benchmark problems for phase field models that are being jointly developed by the Center for Hierarchical Materials Design (CHiMaD) and the National Institute of Standards and Technology (NIST) along with input from other members in the phase field community. As the integrated computational materials engineering (ICME) approach to materials design has gained traction, there is an increasing need for quantitative phase field results. New algorithms and numerical implementations increase computational capabilities, necessitating standard problems to evaluate their impact on simulated microstructure evolution as well as their computational performance. We propose one benchmark problem for solidification and dendritic growth in a single-component system, and one problem for linear elasticity via the shape evolution of an elastically constrained precipitate. We demonstrate the utility and sensitivity of the benchmark problems by comparing the results of 1) dendritic growth simulations performed with different time integrators and 2) elastically constrained precipitate simulations with different precipitate sizes, initial conditions, and elastic moduli. These numerical benchmark problems will provide a consistent basis for evaluating different algorithms, both existing and those to be developed in the future, for accuracy and computational efficiency when applied to simulate physics often incorporated in phase field models.