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- Prediction of mechanical properties of rail pads under in-service conditions through machine learning algorithmsPublication . Ferreño, Diego; Sainz-Aja, Jose Adolfo; Carrascal, Isidro; Cuartas, Miguel; Pombo, João; Casado, José A.; DIEGO, SORAYATrain operations generate high impact and fatigue loads that degrade the rail infrastructure and the vehicle components. Rail pads are installed between the rails and the sleepers in order to damp the transmission of vibrations and noise and to provide flexibility to the track. These components play a crucial role in maximizing the durability of the railway assets and minimizing maintenance costs. Rail pads can be fabricated with different polymeric materials that exhibit non-linear mechanical behaviours, which strongly depend on the service conditions. Therefore, it is extremely difficult to estimate their mechanical properties, in particular the dynamic stiffness. In this work, several machine learning methodologies (multilinear regression, K nearest neighbours, regression tree, random forest, gradient boosting, multi-layer perceptron and support vector machine) were used to determine the dynamic stiffness of rail pads depending on their in-service conditions (temperature, frequency, axle load and toe load). 720 experimental tests, under different realistic operating conditions, were performed to produce a dataset that was then used for the training and testing of the machine learning methods. The optimal algorithm was gradient boosting for EPDM (R2 of 0.995 and mean absolute percentage error of 5.08% in the test dataset), TPE (0.994 and 2.32%) and EVA (0.968 and 4.91%) pads. This model was implemented in an application, available for the readers of this journal, developed on the Microsoft .Net platform that allows the dynamic stiffness of the pads study to be estimated as a function of the temperature, frequency, axle load and toe load.
- Influence of the operational conditions on static and dynamic stiffness of rail padsPublication . Sainz-Aja, Jose A.; Carrascal, Isidro; Ferreño, Diego; Pombo, João; Casado, José A.; DIEGO, SORAYAThe track has a crucial role in the performance of the rail network as it provides support and guidance to the rolling stock. During train operation, the vehicle-track interaction generates high impact loads and fatigue, which lead to degradation of vehicle components and rail infrastructure. These loads tend to increase the maintenance needs and, consequently, the life-cycle-costs of the rail assets. In order to minimize these consequences, rail pads are generally used between the rails and the sleepers in order to provide flexibility to the track and to damp the transmission of noise and vibrations. In ballasted tracks, this flexibility is a combination of the mechanical properties of the ballast and the rail pads. However, in slab tracks, the flexibility of the infrastructure is almost exclusively dependant on the rail pads. These materials exhibit non-linear, dissipative characteristics that are affected by the service conditions such as temperature, frequency, toe load and axle load. This work aims to investigate experimentally different pad materials widely used in the rail industry in order to characterize the influence of these factors on the mechanical characteristics of the rail supporting elements. The detailed characterization of the rail pads enables not only better understanding of their performance in realistic service conditions, but also provides good perspectives for use of these well quantified mechanical properties in studying the vehicle-track dynamic behaviour in different scenarios and predicting the long-term performance of the infrastructure components.