In the field of reduced order modeling, filtering methods have received significant recent attention for treating poorly performing models as a method of regularization. However, filtering by itself can be susceptible to over-smoothing of generated solutions. We propose new reduced order models that integrate the methods of approximate deconvolution into Leray filtering models with a goal of balancing accuracy and smoothing properties. The models are tested with particular application to fluid flows simulated by the Navier-Stokes equations.
Approximate Deconvolution Leray Reduced Order Modeling
Ian Moore, Virginia TechAuthors: Ian Moore, Anna Sanfilippo, Traian Iliescu, Francesco Ballarin
2023 AWM Research Symposium
Recent Developments in Control, Optimization, and the Analysis of Partial Differential Equations [Organized by Lorena Bociu and Pelin Guven Geredeli]