Model Order Reduction and Applications

Cetraro, Italy 2021
1. Auflage 2023
ISBN: 978-3-031-29562-1
Verlag: Springer Nature Switzerland

Buch, Englisch, Band 2328, 230 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 421 g

Reihe: Lecture Notes in Mathematics

This book addresses the state of the art of reduced order methods for modelling and computational reduction of complex parametrised systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in various fields.

Consisting of  four contributions presented at the CIME summer school, the book presents several points of view and techniques to solve demanding problems of increasing complexity. The focus is on theoretical investigation and applicative algorithm development for reduction in the complexity – the dimension, the degrees of freedom, the data – arising in these models.

The book is addressed to graduate students, young researchers and people interested in the field. It is a good companion for graduate/doctoral classes.

Zielgruppe

Research

Autoren/Hrsg.

Hinze, Michael

Kutz, J. Nathan

Mula, Olga

Urban, Karsten

Falcone, Maurizio

Rozza, Gianluigi

Fachgebiete

• Mathematik | Informatik Mathematik Mathematische Analysis
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik

Inhaltsverzeichnis

- 1. The Reduced Basis Method in Space and Time: Challenges, Limits and Perspectives. - 2. Inverse Problems: A Deterministic Approach Using Physics-Based Reduced Models. - 3. Model Order Reduction for Optimal Control Problems. - 4. Machine Learning Methods for Reduced Order Modeling.