
Reduced-Order Modeling (ROM) for Simulation and Optimization
Powerful Algorithms as Key Enablers for Scientific Computing
Springer (Publisher)
Published on 26. January 2019
Book
Paperback/Softback
IX, 179 pages
978-3-030-09199-6 (ISBN)
Description
This edited monograph collects research contributions and addresses the advancement of efficient numerical procedures in the area of model order reduction (MOR) for simulation, optimization and control. The topical scope includes, but is not limited to, new out-of-the-box algorithmic solutions for scientific computing, e.g. reduced basis methods for industrial problems and MOR approaches for electrochemical processes. The target audience comprises research experts and practitioners in the field of simulation, optimization and control, but the book may also be beneficial for graduate students alike.
More details
Edition
Softcover Reprint of the Original 1st 2018 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
13 s/w Abbildungen, 47 farbige Abbildungen
IX, 179 p. 60 illus., 47 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 11 mm
Weight
300 gr
ISBN-13
978-3-030-09199-6 (9783030091996)
DOI
10.1007/978-3-319-75319-5
Schweitzer Classification
Other editions
Additional editions

Winfried Keiper | Anja Milde | Stefan Volkwein
Reduced-Order Modeling (ROM) for Simulation and Optimization
Powerful Algorithms as Key Enablers for Scientific Computing
Book
04/2018
Springer
€90.94
Shipment within 10-15 days
Content
Greedy Kernel Approximation for Sparse Surrogate Modelling.- Set-Oriented Multiobjective Optimal Control ofPDEs using Proper Orthogonal Decomposition.- A Direct Index 1 DAE Model of Gas Networks.- Model Order Reduction for Rotating Electrical Machines.- Morembs - a Model Order Reduction Package for Elastic Multibody Systems and Beyond.- An Iterative Model Reduction Scheme for Quadratic-Bilinear Descriptor Systems with an Application to Navier-Stokes Equations.- Sequential Reduced Order Modeling for Time-Dependent Optimization Problems with Initial Value Controls.