# A Non-stationary Thermal-Block Benchmark Model for Parametric Model Order Reduction

@article{Rave2020ANT, title={A Non-stationary Thermal-Block Benchmark Model for Parametric Model Order Reduction}, author={Stephan Rave and Jens Saak}, journal={Model Reduction of Complex Dynamical Systems}, year={2020} }

In this contribution, we aim to satisfy the demand for a publicly available benchmark for parametric model order reduction that is scalable both in degrees of freedom as well as parameter dimension.

## 2 Citations

### A Training Set Subsampling Strategy for the Reduced Basis Method

- Computer ScienceJ. Sci. Comput.
- 2021

A subsampling strategy for the offline stage of the Reduced Basis Method aimed at bringing down the considerable offline costs associated with using a finely-sampled training set and exploiting the potential of the pivoted QR decomposition and the discrete empirical interpolation method to identify important parameter samples.

### Parametric model order reduction using pyMOR

- Computer ScienceModel Reduction of Complex Dynamical Systems
- 2021

A brief overview of the available methods for pyMOR is given and experimentally compare them for the parametric instationary thermal-block benchmark defined in arXiv:2003.00846.

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