Format:
1 Online-Ressource (VIII, 466 Seiten)
ISBN:
9783110499001
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 two-volume handbook covers methods as well as applications. This second volume focuses on applications in engineering, biomedical engineering, computational physics and computer science.
Content:
Intro -- 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.
Note:
Description based on publisher supplied metadata and other sources
Additional Edition:
Erscheint auch als Druck-Ausgabe Model order reduction ; Volume 3: Applications Berlin$aBoston : De Gruyter, 2021 ISBN 9783110500448
Additional Edition:
ISBN 3110500442
Language:
English
Subjects:
Mathematics
Keywords:
Modellordnungsreduktion
;
Dynamisches System
;
Mathematisches Modell
Author information:
Benner, Peter 1967-
Author information:
Quarteroni, Alfio 1952-
