Reduced-Order Modeling (ROM) for Simulation and Optimization Powerfu
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, n
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ced-Order Modeling (ROM) for Simulation and Optimization Powerful Algorithms as Key Enablers for Scientific Computing
Reduced-Order Modeling (ROM) for Simulation and Optimization
Winfried Keiper Anja Milde Stefan Volkwein •
Editors
Reduced-Order Modeling (ROM) for Simulation and Optimization Powerful Algorithms as Key Enablers for Scientific Computing
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Editors Winfried Keiper Department of Corporate Research Robert Bosch GmbH Renningen Germany
Stefan Volkwein Fachbereich Mathematik Universität Konstanz Konstanz Germany
Anja Milde Interdisciplinary Center for Scientific Computing Heidelberg University Heidelberg Germany
ISBN 978-3-319-75318-8 ISBN 978-3-319-75319-5 https://doi.org/10.1007/978-3-319-75319-5
(eBook)
Library of Congress Control Number: 2018932542 © Springer International Publishing AG, part of Springer Nature 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by the registered company Springer International Publishing AG part of Springer Nature The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
KoMSO Workshop The growing demand for numerical solutions in scientific computing (modeling, simulation, data analysis, and optimization problems in many application fields) requires ever-higher algorithmic and computational performance. Why is this so? To name just a few reasons: Models become larger and require higher geometrical resolution and full 3D topology. Larger, more comprehensive systems with challenging boundary conditions are being modeled and ask for robust process control. Inverse problems of much larger size need to be solved. Connected components with more relevant physical effects are simulated simultaneously. Optimization with parametric variants is performed. Problems require multi-domain and multi-scale modeling. An analysis of ve
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