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Pressure Data-Driven Variational Multiscale Reduced Order Models

Anna IvagnesGiovanni StabileAndrea MolaTraian IliescuGianluigi Rozza
May 2022
摘要
In this paper, we develop data-driven closure/correction terms to increasethe pressure and velocity accuracy of reduced order models (ROMs) for fluidflows. Specifically, we propose the first pressure-based data-drivenvariational multiscale ROM, in which we use the available data to constructclosure/correction terms for both the momentum equation and the continuityequation. Our numerical investigation of the two-dimensional flow past acircular cylinder at Re=50000 in the marginally-resolved regime shows that thenovel pressure data-driven variational multiscale ROM yields significantly moreaccurate velocity and pressure approximations than the standard ROM and, moreimportantly, than the original data-driven variational multiscale ROM (i.e.,without pressure components). In particular, our numerical results show thatadding the closure/correction term in the momentum equation significantlyimproves both the velocity and the pressure approximations, whereas adding theclosure/correction term in the continuity equation improves only the pressureapproximation.
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