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Memorias de investigación
Communications at congresses:
Aerodynamic Optimization of High-Speed Trains Nose using a Genetic Algorithm and Artificial Neural Network
Year:2011
Research Areas
  • Mechanical engineering
Information
Abstract
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.
International
Si
Congress
ECCOMAS Thematic Conference
960
Place
Antalya, Turquía
Reviewers
Si
ISBN/ISSN
978-605-61427-4-1
Start Date
23/05/2011
End Date
25/05/2011
From page
1
To page
19
CFD & OPTIMIZATION
Participants
  • Autor: Jorge Muñoz Paniagua (UPM)
  • Autor: Javier Garcia Garcia (UPM)
  • Autor: Antonio Crespo Martinez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Mecánica de fluidos aplicada a la Ingeniería Industrial
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