Abstract
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.
Highlights
When passing through highly populated areas, the noise emitted by railway vehicles can cause severe nuisance and prejudice to nearby inhabitants
Regarding Sound poWer Level (SWL) simulations, the following elements are considered: UIC54 rail with concrete bibloc sleeper separated 0.6 m, roughness defined by standard (DIN 2017), train speed of V = 80 km/h and contact filter applied to the roughness (which takes into account the force attenuation due to the contact patch size (Thompson 2010))
A procedure for the geometric optimization of the railway wheel cross section has been presented by means of a Genetic Algorithms (GAs)-based optimizer with the aim of reducing acoustic radiation
Summary
When passing through highly populated areas, the noise emitted by railway vehicles can cause severe nuisance and prejudice to nearby inhabitants. It is estimated that about 12 million people during the day and 6 million during the night are affected daily in Europe by this phenomenon (Clausen et al 2012) and it is well known that a prolonged exposure to the levels emitted by railway vehicles is associated with major health problems, such as cardiovascular diseases and difficulties when falling asleep (WHO 2011) This makes it a necessity to adopt expensive measures to mitigate noise that limit the growth of the railway network, a problem that is increasingly relevant with the advance of climate change, the railway being the least polluting mass transport. Previous works have covered various mitigation measures applied in the wheel for rolling noise, such as the implementation of bogie shrouds (Jones et al 1996), retrofitting of freights with composite brake blocks (Buhler 2006), damping solutions developments like friction damping rings (Wang et al 2019), resilient wheels (Bouvet et al 2000; Cigada et al 2008) and sandwich-type dampers (Merideno et al 2014)
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