Conference Tools for 2020 TMS Annual Meeting & Exhibition

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About this Abstract
Meeting	2020 TMS Annual Meeting & Exhibition
Symposium	Characterization: Structural Descriptors, Data-Intensive Techniques, and Uncertainty Quantification
Presentation Title	Uncertainty Propagation in a Multiscale CALPHAD-reinforced Elastochemical Phase-field Model
Author(s)	Vahid Attari, Pejman Honarmandi, Thien Duong, Daniel J Sauceda, Douglas Allaire, Raymundo Arroyave
On-Site Speaker (Planned)	Vahid Attari
Abstract Scope	In any materials design framework, uncertainties across the chain of models alter the final outcome considerably. The quantification of these uncertainties across the chain is often a sobering task, requiring 1) extensive computational resources, 2) systematic automation of propagation processes, 3) defining/designing proper descriptors, and 4) rigorous analysis of large amount of results. In this work, a framework to propagate uncertainties in a chain of models that involve CALPHAD, microleasticity, and phase-field models is utilized to investigate the uncertainty in microstructure of Mg_2(Si_xSn_{1-x}) thermoelectric materials. First, Markov Chain Monte Carlo-based inference of the CALPHAD model parameters are carried out, and then advanced sampling schemes are used to propagate uncertainties across the model input space. High throughput phase-field simulations resulted in approximately 200,000 time series of synthetic microstructures. Moreover, machine learning techniques are employed to differentiate between the parameter space that induces phonon scattering versus mass scattering for better thermoelectric response.
Proceedings Inclusion?	Planned: Supplemental Proceedings volume

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