The rail infrastructure and the track components are expensive assets with long life spans and high maintenance costs. The cost efficiency, performance and punctuality of train operations heavily depend on the track conditions. Ideally, the railway track would be completely smooth providing continuous support to the rolling stock running on it. In practice, however, the infrastructure cannot be installed without irregularities. These defects will increase over time due to the service loads imposed by the railway vehicles. The aim of this work is to use advanced computational tools to predict how the vehicles will respond to changing levels of track defects. For this purpose, the track and its maintenance conditions are characterized in realistic operation scenarios and modelled with detail in order to enable studying the interaction loads that are imposed to the vehicles by the track conditions. The presented methodology enables to identify the track health indexes that have higher influence on the dynamic loads transmitted to the rolling stock. It was observed that the track layout, track irregularities and degradation of the rails have the larger influence on the vehicle-track interaction loads with consequences in terms of safety and maintenance costs. In this way, this work contributes to the development of solutions with technological relevance, giving answer to the industry’s most recent needs in terms of reducing the maintenance costs and decreasing the incidents that cause traffic disruptions, contributing to improve the competitiveness of the railway transport.
|Number of pages||16|
|Journal||Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science|
|Early online date||29 Sep 2020|
|Publication status||Published - 1 Aug 2021|