Abstract
A large-scale, real-world application of Evolutionary Multi- Criterion Optimization (EMO) is reported in this paper. The Multidisciplinary Design Optimization among aerodynamics, structures and aeroelasticity for the wing of a transonic regional jet aircraft has been performed using high-.delity models. An Euler/Navier-Stokes (N-S) Computational Fluid Dynamics (CFD) solver is employed for the aerodynamic evaluation. The NASTRAN, a commercial software, is coupled with a CFD solver for the structural and aeroelastic evaluations. Adaptive Range Multi-Objective Genetic Algorithm is employed as an optimizer. The objective functions are minimizations of block fuel and maximum takeo. weight in addition to di.erence in the drag between transonic and subsonic .ight conditions. As a result, nine non-dominated solutions have been generated. They are used for tradeo. analysis among three objectives. One solution is found to have one percent improvement in the block fuel compared to the original geometry designed in the conventional manner. All the solutions evaluated during the evolution are analyzed by Self-Organizing Map to extract key features of the design space.
Keywords
- Computational Fluid Dynamics
- Design Variable
- Design Space
- Aerodynamic Performance
- Multidisciplinary Design Optimization
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Chiba, K., Obayashi, S., Nakahashi, K., Morino, H. (2005). High-Fidelity Multidisciplinary Design Optimization of Wing Shape for Regional Jet Aircraft. In: Coello Coello, C.A., Hernández Aguirre, A., Zitzler, E. (eds) Evolutionary Multi-Criterion Optimization. EMO 2005. Lecture Notes in Computer Science, vol 3410. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31880-4_43
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DOI: https://doi.org/10.1007/978-3-540-31880-4_43
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