Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines
This book introduces novel design techniques developed to increase the safety of aircraft engines. The authors demonstrate how the application of uncertainty methods can overcome problems in the accurate prediction of engine lift, caused by manufacturing
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Francesco Montomoli Mauro Carnevale Antonio D'Ammaro Michela Massini Simone Salvadori
Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines
SpringerBriefs in Applied Sciences and Technology
More information about this series at http://www.springer.com/series/8884
Francesco Montomoli · Mauro Carnevale Antonio D’Ammaro · Michela Massini Simone Salvadori
Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines
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Francesco Montomoli Imperial College of London London UK
Michela Massini Imperial College of London London UK
Mauro Carnevale Imperial College of London London UK
Simone Salvadori University of Florence Florence Italy
Antonio D’Ammaro University of Cambridge Cambridge UK
ISSN 2191-530X ISSN 2191-5318 (electronic) SpringerBriefs in Applied Sciences and Technology ISBN 978-3-319-14680-5 ISBN 978-3-319-14681-2 (eBook) DOI 10.1007/978-3-319-14681-2 Library of Congress Control Number: 2015930818 Springer Cham Heidelberg New York Dordrecht London © The Author(s) 2015 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. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www.springer.com)
To Manola and Marcello
Preface
It is no wonder that Uncertainty Quantification has become more and more of an actuality in the last decade as the modelling capability jointly with computational power has increased a lot. In the past, the capability to predict flow field and performance in aero engines as well as in turbomachinery was of great support to the design. However, the range of errors in such results was so large as to suggest the use of CFD, mainly to understand the direction of trends and improvements more than the exact evaluation of thermo-fluid-dynamic parameters, which could affect performance, reliability and life of the engine components. Recently, we have seen two different but relevant matters: • the improvement of simulation and modellin
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