High-speed vehicles are exposed to crosswinds that can result in the overturning of the vehicle. As part of the vehicle homologation process, the characteristic wind curve (CWC) must be calculated to determine the maximum vehicle velocity under different wind conditions. European Standard EN 14067-6 presents different approaches for studying this matter, from a two-dimensional (2D) model to a full multi-body model. The key to the problem rests in the uncertainties inherent in a multi-body model: characterizing its suspension elements and obtaining its aerodynamic coefficients. This paper compares a 2D model with a multi-body model of the same vehicle, and presents the advantages and disadvantages of each one. Results show that a 2D model is valid for graphing the CWC and sufficient for studying the basics of the overturning process. Furthermore, a wheel unloading time signal is also studied. It is concluded that the simplification process can modify the transitory response but that the maximum wheel unloading remains constant. Finally, a study of the wheel/rail contact is performed to check if the contact model has an influence on the calculation of the CWCs.
Rolling contact fatigue (RCF) is a common cause of rail failure due to repeated stresses at the wheel-rail contact. This phenomenon is a real problem that greatly affects the safety of train operation. Preventive and corrective maintenance tasks have a big impact on the Life Cycle Cost (LCC) of railway assets, and therefore cutting-edge strategies based on predictive functionalities are needed to reduce it. A methodology based on physical models is proposed to predict the degradation of railway tracks due to RCF. This work merges a crack initiation and a crack growth model along with a fully nonlinear multibody model. From a multibody assessment of the vehicle-track interaction, an energy dissipation method is used to identify points where cracks are expected to appear. At these points, crack propagation is calculated considering the contact conditions as a function of crack depth. The proposed methodology has been validated with field measurements, conducted using Eddy Currents provided by the infrastructure manager Network Rail. Validation results show that RCF behavior can be predicted for track sections with different characteristics without the necessity of previous on-track measurements.
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