Overview
- A complete review on the state of the art of model order reduction advances and developments
- A gallery of application examples on reduced order modeling in computational science and engineering
- It covers several topics and techniques by leading experts
- Includes supplementary material: sn.pub/extras
Part of the book series: MS&A (MS&A, volume 9)
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About this book
Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects.
This book is primarily addressed to computational scientists interested in computational reduction techniques for large scale differential problems.
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Table of contents (11 chapters)
Editors and Affiliations
Bibliographic Information
Book Title: Reduced Order Methods for Modeling and Computational Reduction
Editors: Alfio Quarteroni, Gianluigi Rozza
Series Title: MS&A
DOI: https://doi.org/10.1007/978-3-319-02090-7
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-02089-1Published: 12 December 2013
Softcover ISBN: 978-3-319-37735-3Published: 17 September 2016
eBook ISBN: 978-3-319-02090-7Published: 05 June 2014
Series ISSN: 2037-5255
Series E-ISSN: 2037-5263
Edition Number: 1
Number of Pages: X, 334
Number of Illustrations: 79 b/w illustrations
Topics: Computational Mathematics and Numerical Analysis, Numeric Computing, Mathematical and Computational Engineering, Mathematical Modeling and Industrial Mathematics, Solid Mechanics, Numerical and Computational Physics, Simulation