Abstract Summary
In the field of railway ground-borne noise and vibration, emission levels are strongly dependent on the track and ground properties so that measurements at different sites cannot be directly compared. Therefore, to compare the ground-borne noise and vibration performance of different vehicles, it is desirable to define a vehicle indicator that is track independent. The SILVARSTAR project aims to provide the railway community with proven software tools and methodologies to assess the ground-borne noise and vibration environmental impact of railway traffic on a system level. Within the project, a track-independent vehicle indicator (TVI) is proposed, based on the SILVARSTAR modelling approach, that can be used to identify railway vehicles which generate low ground-borne vibration and noise levels. The proposed TVI is based on applying a frequency weighting to the force density obtained at a site from the measured ground vibration velocity levels due to train passages and the measured line source transfer mobility. Unlike the vibration levels during train passages, the force density is relatively independent of the track and ground properties and the distance from the track at which it is calculated, and hence it is suitable to be used for the track-independent classification of railway vehicles. Two different formulations of TVI are proposed; one related to ground-borne vibration and the other to ground-borne noise. For both formulations, it is assumed that the starting point is the force density determined from the measured vibration response. Each TVI is a single number quantity, defined as a sum over all frequency bands of the frequency-weighted force density levels. The selected weighting functions are chosen to represent the vibration for a nominal track, ground and building. Nonetheless, they are shown to be representative of the changes in vibration and ground-borne noise that will occur when changing from one vehicle type to another, even when the track, ground, building and receiver distance do not correspond to the chosen nominal conditions. The proposed performance classification of different vehicles can be achieved by comparing the relative differences of their TVIs. A series of test cases is devised to demonstrate the calculation of the TVIs and the TVI-based classification of different vehicles at the same site. To replicate practical situations, the TVIs for each vehicle are calculated from force density levels obtained by numerical models. The simulations are performed using generic models of passenger and freight trains and the most important parameters of the vehicle that affect ground vibration and noise are investigated: wheel unevenness, unsprung mass, primary and secondary suspension stiffness, train speed and the number of axles per unit length and axle spacing. The study shows that although the values of the TVIs for each vehicle may vary due to the different modelling approaches and detail or due to the limited knowledge of the input parameters used for the target site, the TVI-based classification of different vehicles is insensitive to this model and parameter uncertainty.
