An Implementation of Self-Organizing Maps for Airfoil Design Exploration via Multi-Objective Optimization Technique
| Autor: | Won Choi, Luiz S. Martins-Filho, Sung-Ki Jung, Fernando Madeira |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Self-organizing map
Airfoil 020301 aerospace & aeronautics Mathematical optimization lcsh:T Computer science Adaptive Range Multi-Object Genetic Algorithm lcsh:Motor vehicles. Aeronautics. Astronautics Evolutionary algorithm Aerospace Engineering 02 engineering and technology Self-Organizing Map Computational Fluid Dynamics PARSEC lcsh:Technology Multi-objective optimization Evolutionary computation Aerodynamics 020303 mechanical engineering & transports Surrogate model 0203 mechanical engineering Genetic algorithm lcsh:TL1-4050 Engineering design process |
| Zdroj: | Journal of Aerospace Technology and Management, Volume: 8, Issue: 2, Pages: 193-202, Published: JUN 2016 Journal of Aerospace Technology and Management v.8 n.2 2016 Journal of Aerospace Technology and Management Departamento de Ciência e Tecnologia Aeroespacial (DCTA) instacron:DCTA Journal of Aerospace Technology and Management, Vol 8, Iss 2, Pp 193-202 (2016) |
| Popis: | Design candidates obtained from optimization techniques may have meaningful information, which provides not only the best solution, but also a relationship between object functions and design variables. In particular, trade-off studies for optimum airfoil shape design involving various objectives and design variables require the effective analysis tool to take into account a complexity between objectives and design variables. In this study, for the multiple-conflicting objectives that need to be simultaneously fulfilled, the real-coded Adaptive Range Multi-Objective Genetic Algorithm code, which represents the global and stochastic multi-objective evolutionary algorithm, was developed for an airfoil shape design. Furthermore, the PARSEC method reflecting geometrical properties of airfoil is adopted to generate airfoil shapes. In addition, the Self-Organizing Maps, based on the neural network, are used to visualize trade-offs of a relationship between the objective function space and the design variable space obtained by evolutionary computation. The Self-Organizing Maps that can be considered as data mining of the engineering design generate clusters of object functions and design variables as an essential role of trade-off studies. The aerodynamic data for all candidate airfoils is obtained through Computational Fluid Dynamics. Lastly, the relationship between the maximum lift coefficient and maximum lift-to-drag ratio as object functions and 12 airfoil design parameters based on the PARSEC method is investigated using the Self-Organizing Maps method. |
| Databáze: | OpenAIRE |
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