Ilaria Grossoni

Dynamics of a vehicle–track coupling system at a rail joint

The dynamic behaviour at a rail joint is examined using a two-dimensional vehicle–track coupling model. The track system is described as a finite-length beam resting on a double-layer discrete viscous-elastic foundation. The vehicle is represented by a half car body and a single bogie. The influence of the number of layers considered, the number of elements between two sleepers, and the beam model is investigated. Parametric studies, both of the coupling model and the analytic formulae, are carried out in order to understand the influence of the main track and vehicle parameters on the P1 and P2 peak forces. Finally, the results in terms of P2 force from the proposed model are compared, not only with measured values but also with other simulated and analytical solutions. An excellent agreement between these values is found.

Optimisation of Support Stiffness at Railway Crossings

ABSTRACT Turnouts are a key element of the railway system. They are also the part of the system with the highest number of degradation modes and associated failures. There are a number of reasons for this, including high dynamic loads resulting from non-uniform rail geometry and track support stiffness. The main aim of this study is to propose a methodology to optimise the pad stiffness along a crossing panel in order to achieve a decrease in the indicators of the most common failure modes. A three-dimensional vehicle/track interaction model has been established, considering a detailed description of the crossing panel support structure. A genetic algorithm has been applied to two main types of constructions, namely direct and indirect fixing, to find the optimum combinations of resilient pad characteristics for various cases of travelling direction, travelling speed and support conditions.

The role of track stiffness and its spatial variability on long-term track quality deterioration

With rapid advances in sensor and condition monitoring technologies, railway infrastructure managers are turning their attention towards the promise that digital information and big data will help them understand and manage their assets more efficiently. In addition to the existing track geometry records, it is evident that track stiffness is a key physical quantity to help assess track quality and its long-term deterioration. The present paper analyses the role of track stiffness and its spatial variability through a set of computational experiments, varying other vehicle and track physical quantities such as vehicle unsprung mass, speed and track vertical irregularities. The support stiffness conditions are obtained using a sample procedure from an autoregressive integrated moving average model to generate a representative larger set of data from previously on-site measured data. A set of computational experiments is carefully designed, varying different physical variables, and a vehicle–track interaction model is used to estimate the track geometry deterioration rates. A series of log-linear regression models are then used to analyse the impact of the tested physical variables on the track deterioration. The main findings suggest that the spatial variability of track stiffness significantly contributes to the track deterioration rates, and thus it should be used in the future to better target the design and maintenance of railway track. Finally, a comparative study of some settlement models available in literature shows that they are very dependent on the test conditions under which they have been derived.