Title: Uncertainty Quantification of Physics-constrained Problems – Data Assimilation and Parameter Estimation

Date: 01/09/2018

Time: 4:10 PM - 5:00 PM

Place: C304 Wells Hall

Speaker: Yoonsang Lee, Lawrence Berkeley National Laboratory

Observation 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 uncertainty quantification methods, 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.