A Stochastic Reduced-Order Model for Statistical Microstructure Descriptors Evolution

نویسندگان

چکیده

Abstract Integrated computational materials engineering (ICME) models have been a crucial building block for modern development, relieving heavy reliance on experiments and significantly accelerating the design process. However, ICME are also computationally expensive, particularly with respect to time integration dynamics, which hinders ability study statistical ensembles thermodynamic properties of large systems long scales. To alleviate bottleneck, we propose model evolution microstructure descriptors as continuous-time stochastic process using non-linear Langevin equation, where probability density function (PDF) descriptors, quantities interests (QoIs), is modeled by Fokker–Planck equation. We discuss how calibrate drift diffusion terms equation from theoretical perspectives. The calibrated can be used reduced-order simulate PDF. Considering in QoIs, demonstrate our proposed methodology three integrated models: kinetic Monte Carlo, phase field, molecular dynamics simulations.

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ژورنال

عنوان ژورنال: Journal of Computing and Information Science in Engineering

سال: 2022

ISSN: ['1530-9827', '1944-7078']

DOI: https://doi.org/10.1115/1.4054237