Department of Scientific Computing, Florida State University
"Efficient Ensemble Methods for the Incompressible Navier-Stokes Equations"
1:30 p.m. Tuesday, January 30, 2018, 499 Dirac Science Library
The definition of partial differential equation (PDE) models usually involves a set of parameters whose values may vary over a wide range. The solution of even a single set of parameter values may be quite expensive and in many cases, (i.e., optimization, control, uncertainty quantification) solutions are needed for many sets of parameter values. We consider the specific case of the time-dependent Navier-Stokes equations and introduce a novel ensemble-based method that allows for the efficient determination of the multiple solutions corresponding to many distinct parameter sets. To further reduce the costs of determining multiple solutions of the Navier-Stokes equations, we incorporate a proper orthogonal decomposition (POD) reduced-order model into the ensemble-based method.