In this work we present a Reduced Order Model which is specifically designed to deal with
turbulent flows in a finite volume setting. The method used to build the reduced order model …

Reduced order modeling is an important and fast-growing research field in computational
science and engineering, motivated by several reasons, of which we mention just a few …

For over a century, reduced order models (ROMs) have been a fundamental discipline of
theoretical fluid mechanics. Early examples include Galerkin models inspired by the Orr …

We propose a component-based (CB) parametric model order reduction (pMOR) formulation
for parameterized nonlinear elliptic partial differential equations (PDEs) based on …

We propose an automated nonlinear model reduction and mesh adaptation framework for
rapid and reliable solution of parameterized advection-dominated problems, with emphasis …

We propose a model reduction procedure for rapid and reliable solution of parameterized
hyperbolic partial differential equations. Due to the presence of parameter-dependent shock …

Projection-based model reduction has become a popular approach to reduce the cost
associated with integrating large-scale dynamical systems so they can be used in many …

Numerous cutting-edge scientific technologies originate at the laboratory scale, but
transitioning them to practical industry applications is a formidable challenge. Traditional …

We propose a nonlinear registration-based model reduction procedure for rapid and reliable
solution of parameterized two-dimensional steady conservation laws. This class of problems …

Abstract Galerkin and Petrov–Galerkin projection-based reduced-order models (ROMs) of
transient partial differential equations are typically obtained by performing a dimension …