Wheel shape optimization approaches to reduce railway rolling noise

[EN] A wheel shape optimization of a railway wheel cross section by means of Genetic Algorithms (GAs) is presented with the aim of minimizing rolling noise radiation. Two different approaches have been implemented with this purpose, one centred on direct Sound poWer Level (SWL) minimization, calcula...

Descripción completa

Detalles Bibliográficos
Autores: García-Andrés, Francesc Xavier, Gutiérrez-Gil, Jorge, Martínez Casas, José|||0000-0001-5706-4951, F. D. Denia|||0000-0003-4536-8610
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/176427
Acceso en línea:https://riunet.upv.es/handle/10251/176427
Access Level:acceso abierto
Palabra clave:Railway wheel
Geometric optimization
Genetic algorithms
Rolling noise
Finite element method
TWINS
Response surface
INGENIERIA MECANICA
09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación
Descripción
Sumario:[EN] A wheel shape optimization of a railway wheel cross section by means of Genetic Algorithms (GAs) is presented with the aim of minimizing rolling noise radiation. Two different approaches have been implemented with this purpose, one centred on direct Sound poWer Level (SWL) minimization, calculated using TWINS methodology, and another one emphasizing computational efficiency, focused on natural frequencies maximization. Numerical simulations are carried out with a Finite Element Method (FEM) model using general axisymmetric elements. The design space is defined by a geometric parametrization of the wheel cross section with four parameters: wheel radius, a web thickness factor, fillet radius and web offset. For all wheel candidates a high-cycle fatigue analysis has been performed according to actual standards, in order to assure structural feasibility. Rolling noise reductions have been achieved, with a decrease of up to 5 dB(A) when considering the wheel component. Response surfaces have been also computed to study the dependency of the objective functions on the geometric parameters and to test the adequacy of the optimization algorithm applied.