IMI Interdisciplinary Mathematics InstituteCollege of Arts and Sciences

Ninth Annual Graduate Student Mini-conference in Computational Mathematics

Muhammad Mohebujjaman
Virginia Tech

Physically-constrained data-driven reduced order modeling of fluid flows

  • Feb. 17, 2018
  • 4:40 p.m.
  • LeConte 412

In this talk, we present two approaches for enforcing better conservation properties for reduced order models (ROMs) of fluid flows. In the first approach, to construct the centering trajectory, we use the Stokes extension instead of the standard snapshot average. We show that the Stokes extension yields significantly more accurate results. In the second approach, we enforce physical constraints in the data-driven modeling of the ROM closure term. The constrained data-driven ROM is significantly more accurate than its unconstrained counterpart.

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