Design and Shape Optimization of Unmanned, Semi-Rigid Airship for Rapid Descent Using Hybrid Genetic Algorithm

FieldValue
dc.contributor.authorSingh, Vinay
dc.date.accessioned2019-01-10T16:35:04Z
dc.date.available2019-01-10T16:35:04Z
dc.date.issued2019-01-10
dc.identifier.urihttp://hdl.handle.net/10393/38673
dc.identifier.urihttp://dx.doi.org/10.20381/ruor-22925
dc.description.abstractAirships provide an eco-friendly and cost-effective means to suit sustained airborne operations. Smaller autonomous airships are highly susceptible to adverse atmospheric conditions owing to their under-actuated, underpowered and bulky size relative to other types of unmanned aerial vehicles (UAVs). To mitigate these limitations, careful considerations of the size and shape must be made at the design stage. This research presents a methodology for obtaining an optimized shape of a semi-rigid airship. Rapid descent of the LTA ship is achieved by means of a moving gondola attached to a rigid keel mounted under the helium envelope from the bow to the mid-section of the hull. The study entails the application of a robust hybrid genetic algorithm (HGA) for the multi-disciplinary design and optimization of an airship capable of rapid descent, with lower drag and optimum surface area. A comprehensive sensitivity analysis was also performed on the basis of algorithmic parameters and atmospheric conditions. With the help of HGA, a semi-rigid airship capable of carrying a payload of 0.25 kg to 1.0 kg and capable of pitching at right angles is conceptually designed. The algorithm is also tested on commercially available vehicles to validate the results. In multi-objective optimization problems (MOOPs), the significance of different objectives is dependent on the user.
dc.language.isoen
dc.publisherUniversité d'Ottawa / University of Ottawa
dc.subjectgenetic algorithm
dc.subjecthill climbing
dc.subjectoptimization
dc.subjectPareto optimality
dc.subjectrapid descent
dc.subjectsemi-rigid airship
dc.titleDesign and Shape Optimization of Unmanned, Semi-Rigid Airship for Rapid Descent Using Hybrid Genetic Algorithm
dc.typeThesis
dc.contributor.supervisorLanteigne, Eric
thesis.degree.nameMASc
thesis.degree.levelMasters
thesis.degree.disciplineGénie / Engineering
uottawa.departmentGénie mécanique / Mechanical Engineering
CollectionThèses, 2011 - // Theses, 2011 -

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