DMC-TPE: tree-structured Parzen estimator-based efficient data assimilation method for phase-field simulation of solid-state sintering

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  • Akimitsu Ishii
    International Center for Young Scientists, National Institute for Materials Science, Tsukuba, Ibaraki, Japan
  • Akiyasu Yamamoto
    Division of Advanced Applied Physics, Institute of Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, Japan
  • Akinori Yamanaka
    Division of Advanced Mechanical Systems Engineering, Institute of Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, Japan

Description

In phase-field simulations, accurate material parameters are required to quantitatively predict microstructural evolutions. Non-sequential data assimilations enable the estimation of unknown material parameters by minimizing a cost function that represents the misfit between numerical simulation results and time-series observation data. In this study, a new non-sequential data assimilation method Minimizing the Cost function using tree-structured Parzen estimator (TPE), namely DMC-TPE, with higher estimation accuracy than that of a conventional method (DMC-Bayesian optimization (BO)) is developed. The estimation accuracy of DMC-TPE is compared with that of DMC-BO via numerical experiments, where these methods are applied to a phase-field simulation of solid-state sintering. The comparison results demonstrate that the estimation accuracy of DMC-TPE is higher than that of DMC-BO, specifically in cases where numerous parameters have to be estimated, because TPE can continuously minimize the cost function by increasing the number of iterative minimization calculations. Furthermore, DMC-TPE provides less scatter in the estimation results than that in the case of DMC-BO. The DMC-TPE developed herein leads to highly accurate PF simulations of microstructural evolution by simultaneously estimating the states and many unknown material parameters with high accuracies based on experimental data.

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