报告时间：2026年7月5日 上午11:30-12:30

报告地点：逸夫楼1537

报告人：姚慧 博士（北京交通大学）

报告题目：Fast supremizer method on penalty-based reduced-order modeling for incompressible flows

报告摘要：In reduced-order modeling of incompressible flows, the supremizer method ensures inf-sup stability for pressure recovery. However, when applied to snapshots from a penalized full-order model, the accuracy of the supremizer method deteriorates if the penalty term is ignored. But incorporating the penalty term with the supremizer method leads to a coupled system that significantly increases computational cost. We propose a novel decoupled supremizer strategy that maintains accuracy and stability while reducing costs. We derive a priori error estimate independent of the penalty coefficient and introduce new supremizer options that reduce offline costs. Numerical experiments demonstrate the accuracy of the proposed method, and reduce online computational cost to under 10% and offline cost by roughly 30% compared to the standard approach.