Phase Field Benchmark Problems for Dendritic Growth and Linear Elasticity

Published

June 15, 2018

Author(s)

Andrea Jokisaari, P W. Voorhees, Jonathan E. Guyer, James A. Warren, O. G. Heinonen

Abstract

We present the second set of benchmark problems for phase field models that are being jointly developed by the Center for Hierarchical Design (CHiMaD) and the National Insti- tute 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 capabili- ties, 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 demon- strate the utility and sensitivity of the the benchmark problems by comparing the results of 1) dendritic growth simulations performed with different time integrators and 2) elasti- cally 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.

Citation

Computational Materials Science

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.commatsci.2018.03.015

Local Download

Keywords

phase field, benchmark, dendrite, elasticity

Citation

Jokisaari, A. , Voorhees, P. , Guyer, J. , Warren, J. and Heinonen, O. (2018), Phase Field Benchmark Problems for Dendritic Growth and Linear Elasticity, Computational Materials Science, [online], https://doi.org/10.1016/j.commatsci.2018.03.015, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=924430 (Accessed January 13, 2025)