Conference Tools for 2023 TMS Annual Meeting & Exhibition

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Meeting	2023 TMS Annual Meeting & Exhibition
Symposium	Algorithm Development in Materials Science and Engineering
Presentation Title	Data Assimilation for Estimation of Microstructural Evolution during Solid-state Sintering: Integration of Phase-field Simulation and In-situ Experimental Observation
Author(s)	Akimitsu Ishii, Akinori Yamanaka, Akiyasu Yamamoto
On-Site Speaker (Planned)	Akimitsu Ishii
Abstract Scope	Sintering is a fundamental technology for manufacturing various materials. Improvement of the properties of sintered materials requires the prediction of their microstructure. Phase-field (PF) method is a powerful numerical simulation methodology for predicting microstructural evolutions during a solid-state sintering. However, material parameters required for the PF simulation are largely unknown. Recently, data assimilation (DA) has attracted attention as an effective method for estimating unobservable states and unknown material parameters. DA enables the estimations by integrating experimental data and numerical simulation results based on Bayesian inference. In this work, we estimate material parameters related to low-temperature sintering of copper by integrating morphological data observed using an in-situ scanning transmission electron microscopy (STEM) and PF simulation results of the solid-state sintering. To estimate materials parameters at a low computational cost, in this study, we used an efficient data assimilation method called DMC-BO. This work was supported by JST CREST (JPMJCR18J4).
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