Nuclear electric propulsion (NEP) vehicles will be needed for future manned missions to Mars and beyond. Candidate designs must be identified for further detailed design from a large array of possibilities. Genetic algorithms have proven their utility in conceptual design studies by effectively searching a large design space to pinpoint unique optimal designs. This research combined analysis codes for NEP subsystems with a genetic algorithm. The use of penalty functions with scaling ratios was investigated to increase computational efficiency. Also, the selection of design variables for optimization was considered to reduce computation time without losing beneficial design search space. Finally, trend analysis of a reference mission to the asteroids yielded a group of candidate designs for further analysis.
Preliminary Design of a Manned Nuclear Electric Propulsion Vehicle Using Genetic Algorithms
SPACE TECHNOLOGY AND APPLICATIONS INT.FORUM-STAIF 2005: Conf.Thermophys in Micrograv;Conf Comm/Civil Next Gen.Space Transp; 22nd Symp Space Nucl.Powr Propuls.;Conf.Human/Robotic Techn.Nat'l Vision Space Expl.; 3rd Symp Space Colon.; 2nd Symp.New Frontiers ; 2005 ; Albuquerque, New Mexico (USA)
AIP Conference Proceedings ; 746 , 1 ; 983-990
06.02.2005
8 pages
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Preliminary Design of a Manned Nuclear Electric Propulsion Vehicle Using Genetic Algorithms
British Library Conference Proceedings | 2005
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