Kooperativer Bibliotheksverbund

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Format: 1 online resource (VIII, 466 p.)

ISBN: 3-11-049775-1 , 3-11-049900-2

Series Statement: Model Order Reduction ; Volume 3

Content: An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This three-volume handbook covers methods as well as applications. This third volume focuses on applications in engineering, biomedical engineering, computational physics and computer science.

Note: Frontmatter -- , Preface to the third volume of Model Order Reduction -- , Contents -- , 1 Model reduction in chemical process optimization -- , 2 Model order reduction in mechanical engineering -- , 3 Case studies of model order reduction for acoustics and vibrations -- , 4 Model order reduction in microelectronics -- , 5 Complexity reduction of electromagnetic systems -- , 6 Model reduction in computational aerodynamics -- , 7 Model order reduction in neuroscience -- , 8 Reduced-order modeling for applications to the cardiovascular system -- , 9 From the POD-Galerkin method to sparse manifold models -- , 10 Model order reduction in uncertainty quantification -- , 11 Reduced-order modeling of large-scale network systems -- , 12 Model order reduction and digital twins -- , 13 MOR software -- , Index , Issued also in print. , In English.

Additional Edition: ISBN 3-11-050044-2

Language: English

Subjects: Mathematics

DOI: 10.1515/9783110499001