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dc.contributor.authorKevorkian, Christopher Georgeen_US
dc.date.accessioned2016-09-28T08:00:31Z
dc.date.available2016-09-28T08:00:31Z
dc.date.issued2016-09-27en_US
dc.identifier.othervt_gsexam:8776en_US
dc.identifier.urihttp://hdl.handle.net/10919/73047
dc.description.abstractSmall Unmanned Aerial Vehicles (SUAVs) are rapidly being adopted in the National Airspace (NAS) but experience a much higher failure rate than traditional aircraft. These SUAVs are quickly becoming complex enough to investigate alternative methods of failure analysis. This thesis proposes a method of expanding on the Fault Tree Analysis (FTA) method to a Bayesian Belief Network (BBN) model. FTA is demonstrated to be a special case of BBN and BBN can allow for more complex interactions between nodes than is allowed by FTA. A model can be investigated to determine the components to which failure is most sensitive and allow for redundancies or mitigations against those failures. The introduced method is then applied to the Virginia Tech ESPAARO SUAV.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis Item is protected by copyright and/or related rights. Some uses of this Item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectUASen_US
dc.subjectReliabilityen_US
dc.subjectBayesianen_US
dc.subjectFault Tree Analysisen_US
dc.titleUAS Risk Analysis using Bayesian Belief Networks: An Application to the VirginiaTech ESPAAROen_US
dc.typeThesisen_US
dc.contributor.departmentAerospace and Ocean Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineAerospace Engineeringen_US
dc.contributor.committeechairWoolsey, Craig A.en_US
dc.contributor.committeechairLuxhoj, James Thomasen_US
dc.contributor.committeememberRaj, Pradeepen_US


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