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Surrogate-based optimization of the nose shape of a high-speed train for lateral stability
Áreas de investigación
  • Ingenierías
Lateral stability of a high-speed train has been optimized in this paper by considering both crosswind and two trains passing by each other. The shape of the nose of the train has been optimized to minimize both the pressure peak when two trains pass by each other and the lateral force coefficient that might result into train derailment when the vehicle is subjected to crosswind. For this purpose, genetic algorithms (GA) have been used. This optimization method requires the parametereization of each optimal candidate as a design vector. The geometrical parameterization of the nose has been defined using three design variables that include the most characteristic geometrical factors affecting the compression wave generated when the two trains meet and the lateral force coefficient. A large set of three-dimensional, turbulent unsteady simulations of realistic train models have been done, and this information has been used to fit a metamodel. A multi-objective optimization has been developed, and a Pareto front has been obtained. The use of metamodels has permitted to analyze the influence of each design variable.
Nombre congreso
International Conference on Evolutionary and Deterministic Methods for Design Optimization and Control with Applications to Industrial and Societal Problems
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Título de las actas
Esta actividad pertenece a memorias de investigación
  • Autor: Jorge Muñoz Paniagua (UPM)
  • Autor: Javier Garcia Garcia (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
  • Departamento: Ingeniería Energética
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