Quantification of Uncertainty: Improving Efficiency and Technology Q
This book explores four guiding themes – reduced order modelling, high dimensional problems, efficient algorithms, and applications – by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty
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Marta D’Elia · Max Gunzburger Gianluigi Rozza Editors
Quantification of Uncertainty: Improving Efficiency and Technology QUIET selected contributions
Editorial Board T. J.Barth M.Griebel D.E.Keyes R.M.Nieminen D.Roose T.Schlick
Lecture Notes in Computational Science and Engineering Editors: Timothy J. Barth Michael Griebel David E. Keyes Risto M. Nieminen Dirk Roose Tamar Schlick
137
More information about this series at http://www.springer.com/series/3527
Marta D’Elia • Max Gunzburger • Gianluigi Rozza Editors
Quantification of Uncertainty: Improving Efficiency and Technology QUIET selected contributions
Editors Marta D’Elia Computational Science and Analysis Sandia National Laboratories Livermore, CA, USA
Max Gunzburger Dept of Scientific Computing Florida State Univ Tallahassee, FL, USA
Gianluigi Rozza SISSA mathLab, Mathematics Area International School for Advanced Studies Trieste, Italy
ISSN 1439-7358 ISSN 2197-7100 (electronic) Lecture Notes in Computational Science and Engineering ISBN 978-3-030-48720-1 ISBN 978-3-030-48721-8 (eBook) https://doi.org/10.1007/978-3-030-48721-8 © National Technology & Engineering Solutions of Sandia, and The Editor(s), under exclusive licence to Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are solely and exclusively licensed 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, expressed 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. Cover illustration: Two face field fluid flow and a geometrically parameterized evolutionary 4th order Cahn-Hilliard system with physical boundary conditions: Background geometry and five reduced basis components, based on a full order cut finite element method. Courtesy Dr Efthymios Karatzas (SISSA mathLab). This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
The international workshop “Quantification of Uncertainty: Improving Eff
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