This work addresses model order reduction for complex moving fronts, which are
transported by advection or through a reaction–diffusion process. Such systems are …

Using nonlinear projections and preserving structure in model order reduction (MOR) are
currently active research fields. In this paper, we provide a novel differential geometric …

We propose a new hyper-reduction method for a recently introduced nonlinear model
reduction framework based on dynamically transformed basis functions and especially well …

This paper presents a neural network-based methodology for the decomposition of transport-
dominated fields using the shifted proper orthogonal decomposition (sPOD). Classical sPOD …

Transport-dominated systems are characterized by the propagation of waves and occur in
many applications such as aerodynamics and chemical engineering. To predict the …

In the context of model reduction, we study an optimization problem related to the
approximation of given data by a linear combination of transformed modes, called …

This work addresses model order reduction for complex moving fronts, which are
transported by advection or through a reaction-diffusion process. Such systems are …

We present a new methodology for decomposing flows with multiple transports that further
extends the shifted proper orthogonal decomposition (sPOD). The sPOD tries to …

In this paper, we consider model order reduction (MOR) methods for problems with slowly
decaying Kolmogorov $ n $-widths as, eg, certain wave-like or transport-dominated …

The numerical simulation of neuromuscular processes in skeletal muscles typically imposes
high computational costs, resulting in the need for techniques to reduce these costs. One …