18 citations · 38 across the 10 of their papers we have counts for
6 papers · 1 filter
Reduced Order Models for the Quasi-Geostrophic Equations: A Brief Survey
Changhong Mou, Zhu Wang, David R. Wells +2
Reduced order models (ROMs) are computational models whose dimension is significantly lower than those obtained through classical numerical discretizations (e.g., finite element, f…
Closure Learning for Nonlinear Model Reduction Using Deep Residual Neural Network
Xuping Xie, Clayton G. Webster, Traian Iliescu
Developing accurate, efficient, and robust closure models is essential in the construction of reduced order models (ROMs) for realistic nonlinear systems, which generally require d…
Lagrangian Data-Driven Reduced Order Modeling of Finite Time Lyapunov Exponents
Xuping Xie, Peter J. Nolan, Shane D. Ross +2
There are two main strategies for improving the projection-based reduced order model (ROM) accuracy: (i) improving the ROM, i.e., adding new terms to the standard ROM; and (ii) imp…
Regularized Reduced Order Models for a Stochastic Burgers Equation
Traian Iliescu, Honghu Liu, Xuping Xie
In this paper, we study the numerical stability of reduced order models for convection-dominated stochastic systems in a relatively simple setting: a stochastic Burgers equation wi…
Approximate Deconvolution Reduced Order Modeling
Xuping Xie, David Wells, Zhu Wang +1
This paper proposes a large eddy simulation reduced order model(LES-ROM) framework for the numerical simulation of realistic flows. In this LES-ROM framework, the proper orthogonal…
An Evolve-Then-Filter Regularized Reduced Order Model
David Wells, Zhu Wang, Xuping Xie +1
In this paper, we propose a new evolve-then-filter reduced order model (EF-ROM). This is a regularized ROM (Reg-ROM), which aims at the numerical stabilization of proper orthogonal…