Some Tools to Study Random Fractional Differential Equations and Applications
Random fractional differential equations are useful mathematical tools to model problems involving memory effects and uncertainties. In this contribution, we present some results, which extent their deterministic counterpart, to fractional differential eq
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José Eduardo Souza De Cursi Editor
Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling Uncertainties 2020
Lecture Notes in Mechanical Engineering ABCM Series on Mechanical Sciences and Engineering
Series Editors Heraldo da Costa Mattos, Niterói, Rio de Janeiro, Brazil Maria Laura Martins Costa, Niterói, Rio de Janeiro, Brazil João Laredo dos Reis, Niterói, Rio de Janeiro, Brazil
This series publishes selected papers as well as full proceedings of events organized and/or promoted by the Brazilian Society for Mechanical Sciences and Engineering (ABCM) on an international level. These include the International Congress of Mechanical Engineering (COBEM) and the International Symposium on Dynamic Problems of Mechanics (DINAME), among others.
More information about this series at http://www.springer.com/series/14172
José Eduardo Souza De Cursi Editor
Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling Uncertainties 2020
123
Editor José Eduardo Souza De Cursi Department Mechanics/Civil Engineering, INSA Rouen Normandie Saint-Etienne du Rouvray, France
ISSN 2195-4356 ISSN 2195-4364 (electronic) Lecture Notes in Mechanical Engineering ISSN 2662-3021 ISSN 2662-303X (electronic) ABCM Series on Mechanical Sciences and Engineering ISBN 978-3-030-53668-8 ISBN 978-3-030-53669-5 (eBook) https://doi.org/10.1007/978-3-030-53669-5 © Springer Nature Switzerland AG 2021 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, 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. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
Uncertainty quantification (UQ) is a field of research that has taken off recently, driven by the ever-increasing need to assess risks, take into account variability and provide qua