RedEigCD enables stable timestep increases up to 40 times larger than full-order models for projection-based ROMs of incompressible flows by using exact spectral bounds on reduced convective and diffusive operators together with a proof that ROM stable timesteps are at least as large as FOM ones.
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A POD-RBF reduced-order model predicts parametrized unsteady Navier-Stokes flows with periodic boundary changes, shown on cylinder flow to cut CPU time over 99% with under 5.2% accuracy loss.
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Stable self-adaptive timestepping for Reduced Order Models for incompressible flows
RedEigCD enables stable timestep increases up to 40 times larger than full-order models for projection-based ROMs of incompressible flows by using exact spectral bounds on reduced convective and diffusive operators together with a proof that ROM stable timesteps are at least as large as FOM ones.
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Reduced-order modelling of parametrized unsteady Navier-Stokes equations and application to flow around cylinders with periodic changing boundary conditions
A POD-RBF reduced-order model predicts parametrized unsteady Navier-Stokes flows with periodic boundary changes, shown on cylinder flow to cut CPU time over 99% with under 5.2% accuracy loss.