UAS Risk Analysis using Bayesian Belief Networks: An Application to the VirginiaTech ESPAARO
Small 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 o...
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ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-730472021-11-24T05:37:33Z UAS Risk Analysis using Bayesian Belief Networks: An Application to the VirginiaTech ESPAARO Kevorkian, Christopher George Aerospace and Ocean Engineering Woolsey, Craig A. Luxhoj, James T. Raj, Pradeep UAS Reliability Bayesian Fault Tree Analysis Small 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. Master of Science 2016-09-28T08:00:31Z 2016-09-28T08:00:31Z 2016-09-27 Thesis vt_gsexam:8776 http://hdl.handle.net/10919/73047 In Copyright http://rightsstatements.org/vocab/InC/1.0/ ETD application/pdf Virginia Tech |
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UAS Reliability Bayesian Fault Tree Analysis |
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UAS Reliability Bayesian Fault Tree Analysis Kevorkian, Christopher George UAS Risk Analysis using Bayesian Belief Networks: An Application to the VirginiaTech ESPAARO |
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Small 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. === Master of Science |
author2 |
Aerospace and Ocean Engineering |
author_facet |
Aerospace and Ocean Engineering Kevorkian, Christopher George |
author |
Kevorkian, Christopher George |
author_sort |
Kevorkian, Christopher George |
title |
UAS Risk Analysis using Bayesian Belief Networks: An Application to the VirginiaTech ESPAARO |
title_short |
UAS Risk Analysis using Bayesian Belief Networks: An Application to the VirginiaTech ESPAARO |
title_full |
UAS Risk Analysis using Bayesian Belief Networks: An Application to the VirginiaTech ESPAARO |
title_fullStr |
UAS Risk Analysis using Bayesian Belief Networks: An Application to the VirginiaTech ESPAARO |
title_full_unstemmed |
UAS Risk Analysis using Bayesian Belief Networks: An Application to the VirginiaTech ESPAARO |
title_sort |
uas risk analysis using bayesian belief networks: an application to the virginiatech espaaro |
publisher |
Virginia Tech |
publishDate |
2016 |
url |
http://hdl.handle.net/10919/73047 |
work_keys_str_mv |
AT kevorkianchristophergeorge uasriskanalysisusingbayesianbeliefnetworksanapplicationtothevirginiatechespaaro |
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1719495527839563776 |