Nearly all model-reduction techniques project the governing equations onto a linear
subspace of the original state space. Such subspaces are typically computed using methods …

Conventional reduced order modeling techniques such as the reduced basis (RB) method
(relying, eg, on proper orthogonal decomposition (POD)) may incur in severe limitations …

Numerical simulation of parametrized differential equations is of crucial importance in the
study of real-world phenomena in applied science and engineering. Computational methods …

Parametric model order reduction using reduced basis methods can be an effective tool for
obtaining quickly solvable reduced order models of parametrized partial differential equation …

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 …

Transport-dominated phenomena provide a challenge for common mode-based model
reduction approaches. We present a model reduction method, which is suited for these kinds …

In the literature on nonlinear projection-based model order reduction for computational fluid
dynamics problems, it is often claimed that due to modal truncation, a projection-based …

This work proposes a method for model reduction of finite-volume models that guarantees
the resulting reduced-order model is conservative, thereby preserving the structure intrinsic …

The reduced basis method allows to propose accurate approximations for many parameter
dependent partial differential equations, almost in real time, at least if the Kolmogorov n …

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