The advent of high-speed trains led to new issues and constraints for railway network manufacturers and operators. This is the case of crosswind effect, that occurs when train is running in strong wind conditions. The combination of train speed and wind speed generates a relative flow that affects the train stability. Wind tunnel tests on still railway vehicles (relative wind-train velocity in coincidence with absolute wind velocity) are mandatory according to Technical Specification for Interoperability (TSI) to ensure high-speed train safety. However, issues related to the correct evaluation of the full-scale aerodynamic behaviour of the trains can arise. In the present work, aerodynamic force and pressure coefficients measured in wind tunnel tests on a scaled model of ETR1000 high-speed train on single track ballast and rails are presented. The tests were performed in the GVPM wind tunnel of Politecnico di Milano. Results show that different flow behaviours can occur at high yaw angles when the train behaves like a bluff body depending on wind speed used during the test.

The condition monitoring of railway vehicles and of the infrastructure (track and overhead equipment) through the use of vehicle-based sensors is becoming a major trend for the railway industry and, to this aim, new rolling stock generations are often natively fitted with numerous sensors. However, older vehicles are not equipped with sensors and monitoring systems so that, considering the long service life of the rolling stock, advanced monitoring and condition-based maintenance techniques can only be applied to a relatively minor portion of the in-service railway fleets. This paper presents results from a research programme aimed at designing and testing an innovative monitoring system based on wireless sensor nodes, suitable for the retrofitting of older rolling stock generations, not natively equipped with advanced sensing and monitoring capabilities. The prototype monitoring system was used to detect the incipient bogie instability, which can be related to degradation in some suspension components or to increase of the equivalent conicity at wheel/rail contact. Different vehicle conditions and the influence of the track were considered in the study. Experimental tests have shown that is possible to identify not only how the vehicle condition is evolving in time but also the effect that maintenance operations like wheel reprofiling may have on the bogie lateral dynamics.

Infrastructure managers rely on diagnostic trains that periodically measure track geometry and vehicle accelerations to ensure the safety of the railway network. Their runs are scheduled depending on the line priority, in order to safely monitor the evolution of track defects. However, sudden and unpredictable defect growth may happen and be missed between successive runs. Therefore, condition monitoring systems have been installed on in-service vehicles. In fact, these trains run every day along the same line, so they can provide additional information useful for maintenance practices. When trains run along conventional lines, their speed significantly changes depending on the line characteristics, and vehicle accelerations strongly depend on speed. Therefore, monitoring systems that rely on vehicle accelerations should carefully take this effect into account. In this paper, a methodology to estimate the track longitudinal level using bogie accelerations from an in-service vehicle is presented. The recorded accelerations were double-integrated to account for the speed variation, and a model-based strategy was adopted to reduce the filtering action of the primary suspension. Data were recorded during a two-year monitoring campaign along an Italian railway line. The methodology allowed for the estimation of the longitudinal level along specific track sections, considering statistical measures like the peak value. A maximum error of 1 mm was found between the estimated values and those measured by the diagnostic train (considering a defect with magnitude of 7.5 mm). Therefore, the results showed that it is possible to estimate the peak longitudinal level between the two rails using one single vertical accelerometer installed on the bogie of an in-service vehicle. The results of this research may be used to support the current maintenance strategy with daily estimations of track longitudinal level. It should be noted that specific attention was given only to this type of track geometry parameter, since it often drives maintenance operations. In the future, the possibility to extend the methodology to the estimation of different type of defects, like cross-level and twist, could be considered.