A Pressure-Stabilized Continuous Data Assimilation Reduced Order Model
Abstract
We present a novel reduced-order pressure stabilization strategy based on continuous data assimilation(CDA) for two-dimensional incompressible Navier-Stokes equations. A feedback control term is incorporated into pressure-correction projection method to derive the Galerkin projection-based CDA proper orthogonal decomposition reduced order model(POD-ROM) that uses pressure modes as well as velocity's simultaneously to compute the reduced-order solutions. The greatest advantage over this ROM is circumventing the standard discrete inf-sup condition for the mixed POD velocity-pressure spaces with the help of CDA which also guarantees the high accuracy of reduced-order solutions; moreover, the classical projection method decouples reduced-order velocity and pressure, which further enhances computational efficiency. Unconditional stability and convergence over POD modes(up to discretization error) are presented, and a benchmark test is performed to validate the theoretical results.
Cite
@article{arxiv.2304.00289,
title = {A Pressure-Stabilized Continuous Data Assimilation Reduced Order Model},
author = {Xi Li and Youcai Xu and Minfu Feng},
journal= {arXiv preprint arXiv:2304.00289},
year = {2023}
}