In this work we present an integrated computational pipeline involving several model order reduction techniques for industrial and applied mathematics, as emerging technology for product and/or process design procedures. Its data-driven nature and its modularity allow an easy integration into existing pipelines.

An integrated data-driven computational pipeline with model order reduction for industrial and applied mathematics / Tezzele, Marco; Demo, Nicola; Mola, Andrea; Rozza, Gianluigi. - (2022), pp. 179-200. [10.1007/978-3-030-96173-2_7]

An integrated data-driven computational pipeline with model order reduction for industrial and applied mathematics

Marco Tezzele;Nicola Demo;Andrea Mola;Gianluigi Rozza
2022-01-01

Abstract

In this work we present an integrated computational pipeline involving several model order reduction techniques for industrial and applied mathematics, as emerging technology for product and/or process design procedures. Its data-driven nature and its modularity allow an easy integration into existing pipelines.
2022
Novel Mathematics Inspired by Industrial Challenges
179
200
https://doi.org/10.1007/978-3-030-96173-2_7
Tezzele, Marco; Demo, Nicola; Mola, Andrea; Rozza, Gianluigi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/130171
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