Model Reduction of Complex Dynamical Systems (1st ed. 2021) (International Series of Numerical Mathematics #171)

Synopsis

This contributed volume presents some of the latest research related to model order reduction of complex dynamical systems with a focus on time-dependent problems. Chapters are written by leading researchers and users of model order reduction techniques and are based on presentations given at the 2019 edition of the workshop series Model Reduction of Complex Dynamical Systems – MODRED, held at the University of Graz in Austria. The topics considered can be divided into five categories:system-theoretic methods, such as balanced truncation, Hankel norm approximation, and reduced-basis methods; data-driven methods, including Loewner matrix and pencil-based approaches, dynamic mode decomposition, and kernel-based methods;surrogate modeling for design and optimization, with special emphasis on control and data assimilation;model reduction methods in applications, such as control and network systems, computational electromagnetics, structural mechanics, and fluid dynamics; andmodel order reduction software packages and benchmarks.This volume will be an ideal resource for graduate students and researchers in all areas of model reduction, as well as those working in applied mathematics and theoretical informatics.

Copyright:

2021

Book Details

Book Quality:

Publisher Quality

ISBN-13:

9783030729837

Related ISBNs:

9783030729820

Publisher:

Springer International Publishing

Date of Addition:

09/29/21

Copyrighted By:

Springer Nature Switzerland AG

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Computers and Internet, Technology, Mathematics and Statistics

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.

Edited by:

Peter Benner

Edited by:

Tobias Breiten

Edited by:

Heike Faßbender

Edited by:

Michael Hinze

Edited by:

Tatjana Stykel

Edited by:

Ralf Zimmermann