Work

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

Year: 2020

Type: preprint

Abstract: 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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2003.00846

Authors: Saak, Jens, Rave, Stephan, Mlinarić, Petar, Werner, Steffen W. R., Himpe, Christian

Institutions: Max Planck Institute for Dynamics of Complex Technical Systems, University of Münster

Language: English

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

Funders: Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung

Awards: G1652504919, EXC 2044: Mathematik Münster: Dynamik – Geometrie – Struktur, G6938060324

OpenAlex ID: W4296465227

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