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홈 > 학술정보 >학술행사 > 세미나
KAIST 수리과학과 세미나

Title
Stochastic Super-parameterization : a Multiscale Coarse-grained Model for Complex Dynamical Systems
Speaker
이윤상   (Berkeley Lawrence Lab )
Date
2017-10-16 11:00:00
Host
KAIST
Place
E6 Room 2411
Abstract
Observational data along with mathematical models play a crucial role in improving prediction skills in science and engineering. In this talk we focus on the recent development of Bayesian inference techniques, data assimilation and parameter estimation, for Physics-constrained problems that are often described by partial differential equations. We discuss the similarities shared by the two methods and their differences in mathematical and computational points of view and future research topics. As applications, numerical weather prediction for geophysical flows and parameter estimation of kinetic reaction rates in the hydrogen-oxygen combustion are provided. This talk aims for researchers and students in all disciplines of science and engineering and only a minimum level of undergraduate mathematics is required.
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