Computationally Efficient Phase-field Simulation Studies Using RVE Sampling and Statistical Analysis

Christian Schwarze

doi:10.1016/j.commatsci.2018.02.005

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Computationally Efficient Phase-field Simulation Studies Using RVE Sampling and Statistical Analysis

2018-05-01

Christian Schwarze

Reza Darvishi Kamachali *

Markus Kühbach

Christian Mießen

Marvin Tegeler

Luis A. Barrales‐Mora

Ingo Steinbach

Günter Gottstein

DOI：10.1016/j.commatsci.2018.02.005

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Abstract

En 中文

For large-scale phase-field simulations, the trade-off between accuracy and computational cost as a function of the size and number of simulations was studied. For this purpose, a large reference representative volume element (RVE) was incrementally subdivided into smaller solitary samples. We have considered diffusion-controlled growth and early ripening of delta' (Al3Li) precipitate in a model Al-Li system. The results of the simulations show that decomposition of reference RVE can be a valuable computational technique to accelerate simulations without a substantial loss of accuracy. In the current case study, the precipitate number density was found to be the key controlling parameter. For a pre-set accuracy, it turned out that large-scale simulations of the reference RVE can be replaced by simulating a combination of smaller solitary samples. This shortens the required simulation time and improves the memory usage of the simulation considerably, and thus substantially increases the efficiency of massive parallel computation for phase-field applications. (C) 2018 Elsevier B.V. All rights reserved.

Keywords:

Microstructure evolution

Phase-field simulation

Precipitation

Sampling

Statistical analysis

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