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SUMMARY:Machine learning approximations in finite volume methods - Sam Lew
 in\, Research Software Engineering\, University of Cambridge
DTSTART:20190220T130000Z
DTEND:20190220T140000Z
UID:TALK119458@talks.cam.ac.uk
CONTACT:Jeffrey Salmond
DESCRIPTION:The Riemann solver is the foundation of many finite volume met
 hods used in computational fluid dynamics (CFD). In this talk we discuss h
 ow a some of the approximations in common Riemann solvers can be improved:
  by constructing a neural network to estimate some of the physical quantit
 ies required to construct the approximate solution of the Riemann problem\
 , we can achieve better performance both in accuracy and in time-to-soluti
 on.
LOCATION:JJ Thomson Seminar Room\, Maxwell Centre\, Cavendish Laboratory
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