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.
翻译:压力稳定的连续数据同化降阶模型
翻译后的摘要:
我们提出一种新颖的压力稳定策略,基于连续数据同化 (CDA),用于二维不可压 Navier-Stokes 方程。通过将反馈控制项嵌入到压力修正投影方法中,导出了基于 Galerkin 投影的 CDA Proper Orthogonal Decomposition 降阶模型 (POD-ROM),该模型同时使用压力模式和速度模式计算降阶解。相比其他 ROM,最大的优势是避免了使用CDA绕过混合POD速度-压力空间标准离散inf-sup条件,而CDA还保证了降阶解的高精度;此外,经典投影方法将速度和压力降阶结果解藕,进一步提高了计算效率。我们提供了POD模态上无条件稳定性和收敛性(直至离散误差),并进行了基准测试来验证理论结果。