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Memorias de investigación
Aerodynamic Optimization of High-Speed Trains Nose using a Genetic Algorithm and Artificial Neural Network
Áreas de investigación
  • Ingenierías
An aerodynamic optimization of the train aerodynamic characteristics in term of front wind action sensitivity is carried out in this paper. In particular, a genetic algorithm (GA) is used to perform a shape optimization study of a high-speed train nose. The nose is parametrically defined via Bézier Curves, including a wider range of geometries in the design space as possible optimal solutions. Using a GA, the main disadvantage to deal with is the large number of evaluations need before finding such optimal. Here it is proposed the use of metamodels to replace Navier-Stokes solver. Among all the posibilities, Rsponse Surface Models and Artificial Neural Networks (ANN) are considered. Best results of prediction and generalization are obtained with ANN and those are applied in GA code. The paper shows the feasibility of using GA in combination with ANN for this problem, and solutions achieved are included.
Entidad relacionada
ECCOMAS Thematic Conference
Nacionalidad Entidad
Sin nacionalidad
Lugar del congreso
Antalya, Turquía
Esta actividad pertenece a memorias de investigación
  • Autor: Jorge Muñoz Paniagua (UPM)
  • Autor: Javier Garcia Garcia (UPM)
  • Autor: Antonio Crespo Martinez (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Ingeniería Energética y Fluidomecánica
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