Development of safety and reliability prediction methodology for aircraft systems with common-cause failures

dc.contributor.advisorFielding, John
dc.contributor.authorNam, G. W.
dc.date.accessioned2017-01-17T14:12:57Z
dc.date.available2017-01-17T14:12:57Z
dc.date.issued1996-04
dc.description.abstractA methodology has been developed for predicting aircraft safety and reliability incorporating both C.C.F.s(Common-Cause Failures), and phased missions. Failure behaviour of an aircraft, or its systems due to both independent failures and C.C.F.s are modelled by the Markov process, and simulated using Monte Carlo method with the robust variance reduction techniques. Prediction of safety and reliability is made through discrete-event simulation of aircraft operations. Validation was made by comparing the predicted safety and reliability results of B767 ETOPS aircraft propulsion system, using the developed methodology, to those obtained from the analysis of real operation data. The credibility and the accuracy of the developed methodology are shown through the comparison of results. A case study was conducted for investigating the safety and reliability of the propulsion system of two-, three- and four-engined aircraft using the developed methodology. The case study produced valuable results concerning the safety of ETOPS flight, which were not previously known. These results were able to be used for further trade studies of aircraft design to decide the number of engines, and also for establishing new regulations for ETOPS flights.en_UK
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/11287
dc.language.isoenen_UK
dc.publisherCranfield Universityen_UK
dc.rights© Cranfield University, 1996. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.en_UK
dc.titleDevelopment of safety and reliability prediction methodology for aircraft systems with common-cause failuresen_UK
dc.typeThesis or dissertationen_UK
dc.type.qualificationlevelDoctoralen_UK
dc.type.qualificationnamePhDen_UK

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