This work presents a model reduction approach for problems with coherent structures that
propagate over time, such as convection-dominated flows and wave-type phenomena …

This work introduces a new approach to reduce the computational cost of solving partial
differential equations (PDEs) with convection-dominated solutions: model reduction with …

Friedrichs' systems (FS) are symmetric positive linear systems of first-order partial differential
equations (PDEs), which provide a unified framework for describing various elliptic …

This work presents a method for constructing online-efficient reduced models of large-scale
systems governed by parametrized nonlinear scalar conservation laws. The solution …

We present a registration method for model reduction of parametric partial differential
equations with dominating advection effects and moving features. Registration refers to the …

Computational optimal transport is used to analyze the difference between pairs of
continuous molecular spectra. It is demonstrated that transport distances which are derived …

In the last few years, several methods have been developed to deal with jump singularities
in parametric or stochastic hyperbolic PDEs. They typically use some alignment of the jump …

View Video Presentation: https://doi. org/10.2514/6.2022-1250. vid As designers become
increasingly reliant upon expensive, high-fidelity numerical modeling and simulation …

Classical reduced models are low-rank approximations using a fixed basis designed to
achieve dimensionality reduction of large-scale systems. In this work, we introduce reduced …

This work introduces an empirical quadrature‐based hyperreduction procedure and greedy
training algorithm to effectively reduce the computational cost of solving convection …