Parametric Reduced Order Models for the Generalized Kuramoto--Sivashinsky Equations

The paper studies parametric Reduced Order Models (ROMs) for the Kuramoto–Sivashinsky (KS) and generalized Kuramoto–Sivashinsky (gKS) equations. We consider several POD and POD-DEIM projection ROMs with various strategies for parameter sampling and snapshot collection. The aim is to identify an approach for constructing a ROM that is efficient across a range of parameters, encompassing several regimes exhibited by the KS and gKS solutions: weakly chaotic, transitional, and quasi-periodic dynamics. We describe such an approach and demonstrate that it is essential to develop ROMs that adequately represent the short-time transient behavior of the gKS model.