Modeling, simulation and hybrid optimization method as design tools for range extension kit of a subsonic flying body

dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorElsherbiny A.M.
dc.contributor.authorBayoumy A.M.
dc.contributor.authorElshabka A.M.
dc.contributor.authorAbdelrahman M.M.
dc.contributor.otherAeronautical Department
dc.contributor.otherMilitary Technical College
dc.contributor.otherCairo
dc.contributor.otherEgypt; Aeronatuical department
dc.contributor.otherMechatronics Department
dc.contributor.otherMSA University
dc.contributor.otherGiza
dc.contributor.otherEgypt; Aeronautical Department
dc.contributor.otherCairo university
dc.contributor.otherCairo
dc.contributor.otherEgypt
dc.date.accessioned2020-01-09T20:41:07Z
dc.date.available2020-01-09T20:41:07Z
dc.date.issued2018
dc.descriptionScopus
dc.description.abstractIn this paper a hybrid optimization method is introduced to convert the aerodynamic shape of a conventional aerial subsonic flying body into a glide one by providing a range extension kit and fins. The selections of configuration and airfoils are described depending on the tactical requirements and flight regimes. The wing and fins sizing is obtained using four different methods subjected to geometric constraints. The first method is an iterative optimization method using linear aerodynamic coefficients and derivatives. The second method is a multi-objective function genetic algorithm aims to maximize stability, controllability and lift-drag ratio within certain weights using linear aerodynamic data. The third method is a genetic algorithm optimization function integrated with MISSILE DATCOM aims to maximize lift-drag ratio. The fourth method is a hybrid optimization method that integrate MISSILE DATCOM with both genetic algorithm and gradient-based optimization method. Then perform a direct uncontrolled six degree of freedom simulation for the four designs and the conventional flying body. Comparing the results of ranges for these bodies reveals that the hybrid optimization method has the best range over the other designs including the conventional flying body. � 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.en_US
dc.identifier.doihttps://doi.org/10.2514/6.2018-0429
dc.identifier.isbn9.78E+12
dc.identifier.otherhttps://doi.org/10.2514/6.2018-0429
dc.identifier.urihttps://arc.aiaa.org/doi/abs/10.2514/6.2018-0429
dc.language.isoEnglishen_US
dc.publisherAmerican Institute of Aeronautics and Astronautics Inc, AIAAen_US
dc.relation.ispartofseriesAIAA Modeling and Simulation Technologies Conference, 2018
dc.subjectAerodynamic dragen_US
dc.subjectAerodynamic stabilityen_US
dc.subjectAerodynamicsen_US
dc.subjectAntennasen_US
dc.subjectAviationen_US
dc.subjectDegrees of freedom (mechanics)en_US
dc.subjectDragen_US
dc.subjectFins (heat exchange)en_US
dc.subjectGenetic algorithmsen_US
dc.subjectLiften_US
dc.subjectLift drag ratioen_US
dc.subjectMissilesen_US
dc.subjectOptimizationen_US
dc.subjectVertical stabilizersen_US
dc.subjectGenetic-algorithm optimizationsen_US
dc.subjectGeometric constrainten_US
dc.subjectGradient-based optimization methoden_US
dc.subjectHybrid optimization methoden_US
dc.subjectIterative Optimizationen_US
dc.subjectMulti-objective functionsen_US
dc.subjectRange-extension kiten_US
dc.subjectSix degree-of-freedomen_US
dc.subjectIterative methodsen_US
dc.titleModeling, simulation and hybrid optimization method as design tools for range extension kit of a subsonic flying bodyen_US
dc.typeConference Paperen_US
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dcterms.sourceScopus

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