Multi-Objective Optimization for Aerodynamic Designs by Using ARMOGAs

  • Authors:
  • Shigeru Obayashi;Daisuke Sasaki

  • Affiliations:
  • Tohoku University;Tohoku University

  • Venue:
  • HPCASIA '04 Proceedings of the High Performance Computing and Grid in Asia Pacific Region, Seventh International Conference
  • Year:
  • 2004

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Abstract

Global trade-offs for aerodynamic design of Supersonic Transport (SST) have been investigated by Multi-Objective Evolutionary Algorithms (MOEAs). The objectives are to reduce both drag and sonic boom to make next-generation SST more feasible. Adaptive Range Multi-Objective Genetic Algorithms (ARMOGAs) are utilized for the efficient search. The trade-offs are analysed by Self-Organizing Map (SOM), which provides a topology preserving mapping from the high dimensional space to two dimensions. ARMOGAs and SOM can be good design tools to conduct aerodynamic design optimizations and analyse the results.