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dc.contributor.advisorHartfield, Roy
dc.contributor.advisorBurkhalter, Johnen_US
dc.contributor.advisorGross, Roberten_US
dc.contributor.advisorBarrett, Ronald M.en_US
dc.contributor.authorBurger, Christophen_US
dc.date.accessioned2008-09-09T21:15:10Z
dc.date.available2008-09-09T21:15:10Z
dc.date.issued2007-12-15en_US
dc.identifier.urihttp://hdl.handle.net/10415/210
dc.description.abstractA propeller performance analysis program has been developed and integrated into a Genetic Algorithm for design optimization. The design tool will produce optimal propeller geometries for a given goal, which includes performance and/or acoustic signature. A vortex lattice model is used for the propeller performance analysis and a subsonic compact source model is used for the acoustic signature determination. Compressibility effects are taken into account with the implementation of Prandtl-Glauert domain stretching. Viscous effects are considered with a simple Reynolds number based model to account for the effects of viscosity in the spanwise direction. An empirical flow separation model developed from experimental lift and drag coefficient data of a NACA 0012 airfoil is included. The propeller geometry is generated using a recently introduced Class/Shape function methodology to allow for efficient use of a wide design space. Optimizing the angle of attack, the chord, the sweep and the local airfoil sections, produced blades with favorable tradeoffs between single and multiple point optimizations of propeller performance and acoustic noise signatures. Optimizations using a binary encoded IMPROVE© Genetic Algorithm (GA) and a real encoded GA were obtained after optimization runs with some premature convergence. The newly developed real encoded GA was used to obtain the majority of the results which produced generally better convergence characteristics when compared to the binary encoded GA. The optimization trade-offs show that single point optimized propellers have favorable performance, but circulation distributions were less smooth when compared to dual point or multiobjective optimizations. Some of the single point optimizations generated propellers with proplets which show a loading shift to the blade tip region. When noise is included into the objective functions some propellers indicate a circulation shift to the inboard sections of the propeller as well as a reduction in propeller diameter. In addition the propeller number was increased in some optimizations to reduce the acoustic blade signatureen_US
dc.language.isoen_USen_US
dc.subjectAerospace Engineeringen_US
dc.titlePropeller Performance Analysis and Multidisciplinary Optimization Using a Genetic Algorithmen_US
dc.typeDissertationen_US
dc.embargo.lengthNO_RESTRICTIONen_US
dc.embargo.statusNOT_EMBARGOEDen_US


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