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141008 ||| eng |
| 020 |
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|a 9783709117941
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| 100 |
1 |
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|a Chinesta, Francisco
|e [editor]
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| 245 |
0 |
0 |
|a Separated Representations and PGD-Based Model Reduction
|h Elektronische Ressource
|b Fundamentals and Applications
|c edited by Francisco Chinesta, Pierre Ladevèze
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| 250 |
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|a 1st ed. 2014
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| 260 |
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|a Vienna
|b Springer Vienna
|c 2014, 2014
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| 300 |
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|a VII, 227 p. 74 illus
|b online resource
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| 505 |
0 |
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|a From the Contents: Model order reduction based on proper orthogonal decomposition: Model reduction: extracting relevant information -- Interpolation of reduced basis: a geometrical approach -- POD for non-linear models
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| 653 |
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|a Computational Science and Engineering
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| 653 |
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|a Mechanics, Applied
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| 653 |
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|a Theoretical and Applied Mechanics
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| 653 |
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|a Computer-aided engineering
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| 653 |
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|a Computer-Aided Engineering (CAD, CAE) and Design
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| 653 |
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|a Computer mathematics
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| 653 |
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|a Mechanics
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| 700 |
1 |
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|a Ladevèze, Pierre
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a CISM International Centre for Mechanical Sciences, Courses and Lectures
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-7091-1794-1?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 620.1
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| 520 |
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|a The papers in this volume start with a description of the construction of reduced models through a review of Proper Orthogonal Decomposition (POD) and reduced basis models, including their mathematical foundations and some challenging applications, then followed by a description of a new generation of simulation strategies based on the use of separated representations (space-parameters, space-time, space-time-parameters, space-space,…), which have led to what is known as Proper Generalized Decomposition (PGD) techniques. The models can be enriched by treating parameters as additional coordinates, leading to fast and inexpensive online calculations based on richer offline parametric solutions. Separated representations are analyzed in detail in the course, from their mathematical foundations to their most spectacular applications. It is also shown how such an approximation could evolve into a new paradigm in computational science, enabling one to circumvent various computational issues in a vast array of applications in engineering science
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