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Memorias de investigación
Ponencias en congresos:
Aerodynamic Optimization of High-Speed Trains Nose using a Genetic Algorithm and Artificial Neural Network
Año:2011
Áreas de investigación
  • Ingenieria mecanica
Datos
Descripción
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.
Internacional
Si
Nombre congreso
ECCOMAS Thematic Conference
Tipo de participación
960
Lugar del congreso
Antalya, Turquía
Revisores
Si
ISBN o ISSN
978-605-61427-4-1
DOI
Fecha inicio congreso
23/05/2011
Fecha fin congreso
25/05/2011
Desde la página
1
Hasta la página
19
Título de las actas
CFD & OPTIMIZATION
Esta actividad pertenece a memorias de investigación
Participantes
  • 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: Grupo de Investigación: Mecánica de fluidos aplicada a la Ingeniería Industrial
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