32 citations · 147 across the 27 of their papers we have counts for
7 papers · 1 filter
A Two-Level Galerkin Reduced Order Model for the Steady Navier-Stokes Equations
Dylan Park, Changhong Mou, Honghu Liu +2
We propose, analyze, and investigate numerically a novel two-level Galerkin reduced order model (2L-ROM) for the efficient and accurate numerical simulation of the steady Navier-St…
Stochastic Data-Driven Variational Multiscale Reduced Order Models
Fei Lu, Changhong Mou, Honghu Liu +1
Trajectory-wise data-driven reduced order models (ROMs) tend to be sensitive to training data, and thus lack robustness. We propose to construct a robust stochastic ROM closure (S-…
Reduced Order Model Closures: A Brief Tutorial
William Snyder, Changhong Mou, Honghu Liu +3
In this paper, we present a brief tutorial on reduced order model (ROM) closures. First, we carefully motivate the need for ROM closure modeling in under-resolved simulations. Then…
Shock trace prediction by reduced models for a viscous stochastic Burgers equation
Nan Chen, Honghu Liu, Fei Lu
Viscous shocks are a particular type of extreme events in nonlinear multiscale systems, and their representation requires small scales. Model reduction can thus play an important r…
Conditional Gaussian Nonlinear System: a Fast Preconditioner and a Cheap Surrogate Model For Complex Nonlinear Systems
Nan Chen, Yingda Li, Honghu Liu
Developing suitable approximate models for analyzing and simulating complex nonlinear systems is practically important. This paper aims at exploring the skill of a rich class of no…
Least-Squares Finite Element Method for Ordinary Differential Equations
Matthias Chung, Justin Krueger, Honghu Liu
We consider the least-squares finite element method (lsfem) for systems of nonlinear ordinary differential equations and establish an optimal error estimate for this method when pi…