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Reduced-Order Modeling (ROM) for Simulation and Optimization

Powerful Algorithms as Key Enablers for Scientific Computing

  • Winfried Keiper
  • Anja Milde
  • Stefan Volkwein

Table of contents

  1. Front Matter
    Pages i-ix
  2. Bernard Haasdonk, Gabriele Santin
    Pages 21-45
  3. Dennis Beermann, Michael Dellnitz, Sebastian Peitz, Stefan Volkwein
    Pages 47-72
  4. Peter Benner, Maike Braukmüller, Sara Grundel
    Pages 99-119
  5. Zeger Bontinck, Oliver Lass, Oliver Rain, Sebastian Schöps
    Pages 121-140
  6. Jörg Fehr, Dennis Grunert, Philip Holzwarth, Benjamin Fröhlich, Nadine Walker, Peter Eberhard
    Pages 141-166
  7. Dirk Hartmann, Matthias Herz, Utz Wever
    Pages 167-179

About this book

Introduction

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. 

Keywords

Model Reduction Algorithms for scientific computing Scientific Computing Applications in Industry Optimization and Control Model order reduction MOR for optimization Model order reduction for electrochemistry

Editors and affiliations

  • Winfried Keiper
    • 1
  • Anja Milde
    • 2
  • Stefan Volkwein
    • 3
  1. 1.Department of Corporate ResearchRobert Bosch GmbHRenningenGermany
  2. 2.Interdisciplinary Center for Scientific ComputingHeidelberg UniversityHeidelbergGermany
  3. 3.Fachbereich MathematikUniversität KonstanzKonstanzGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-75319-5
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-75318-8
  • Online ISBN 978-3-319-75319-5
  • Buy this book on publisher's site