Homogenization

Physics-informed Neural Networks for Learning the Homogenized Coefficients of Multiscale Elliptic Equations

Dr. Jun Sur Richard Park, Korea Institute for Advanced Study

Jan 10, 10:00 - 11:00

KAUST

Physics-informed Neural Networks multiscale methods Homogenization

Abstract Multiscale elliptic equations with scale separation are often approximated by the corresponding homogenized equations with slowly varying homogenized coefficients (the G-limit). The traditional homogenization techniques typically rely on the periodicity of the multiscale coefficients, thus finding the G-limits often requires sophisticated techniques in more general settings even when multiscale coefficient is known, if possible. Alternatively, we propose a simple approach to estimate the G-limits from (noisy-free or noisy) multiscale solution data, either from the existing forward

Zainab Alali

Visiting Student, Waves in Complex Media

computational physics Homogenization

Research Interests Zainab Alali is doing Directed Research in WCM group for the summer 2013.

Bingmu Xiao

M.S. Student, Waves in Complex Media

Master, KAUST 2013 Research Interests: Homogenization