Dynamic response of vehicle-track coupling system with an insulated rail joint

The dynamic behavior of vehicle and track systems is studied in the presence of an insulated rail joint through 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 through a half car body and a single bogie. These sub-systems are solved independently and coupled together through a Hertzian contact model, where the irregularity caused by the rail joint is modelled as a second order polynomial. A parametric study is carried out in order to understand the influence by the main track and vehicle parameters to the P1 and P2 peak forces. Finally, the results in terms of P2 force from the present model have been compared not only with measured values but also with both other simulated and analytical solutions and an excellent agreement between these values has been found

The interaction between railway vehicle dynamics and track lateral alignment

Track geometry deteriorates with traffic flow, thus it needs to be regularly restored using tamping or other method. As the deterioration is mainly in the vertical direction this aspect has been widely studied and models for its analysis developed, however, the lateral deterioration of track is not as well understood. This research aims to develop a method that can be used to analyse and predict the lateral deterioration of railway track caused by traffic flows, and investigate the influences of different railway vehicles, running speeds, traffic types and wheel/rail contact conditions

Prediction of wheel and rail wear under different contact conditions using artificial neural networks

Wheel and rail wear is a significant issue in railway systems. Accurate prediction of this wear can improve economy, ride comfort, prevention of derailment and planning of maintenance interventions. Poor prediction can result in failure and consequent delay and increased costs if it is not controlled in an effective way. However, prediction of wheel and rail wear is still a great challenge for railway engineers and operators. The aim of this paper is to predict wheel wear and rail wear using an artificial neural network. Nonlinear Autoregressive models with exogenous input neural network (NARXNN) have been developed for wheel and rail wear prediction. Testing with a twin disc rig, together with measurement of wear using replica material and a profilometer have been carried out for wheel and rail wear under dry, wet and lubricated conditions and after sanding. Tests results from the twin disk rig have been used to train, validate, and test the neural network. Wheel and rail profiles plus load, speed, yaw angle, and first and second derivative of the wheel and rail profiles were used as an inputs to the neural network, while the output of neural network was the wheel wear and rail wear. Accuracy of wheel and rail wear prediction using the neural network was investigated and assessed in term of mean absolute percentage error (MAPE). The results demonstrate that the neural network can be used efficiently to predict wheel and rail wear. The methods of collecting wear data using the replica material and the profilometer have also proved effective for wheel and rail wear measurements for training and validating the neural network. The laboratory tests have aimed to validate the wear predictions for realistic wheel and rail profiles and materials but they necessarily cover only a limited set of conditions. The next steps for this work will be to test the methods for rail and wheel data from field tests

Estimating the damage and marginal cost of different vehicle types on rail infrastructure: combining economic and engineering approaches

EU legislation requires that European infrastructure managers set access charges based on the marginal cost of running trains on their networks. Two methods have been used in the literature for this purpose. Top-down methods relate actual costs to traffic volumes. Bottom-up methods use engineering models to simulate damage and then translate damage into costs based on assumptions about interventions and their unit costs. Whilst top down methods produce sensible results for marginal cost overall, they have struggled to differentiate between traffic types. The challenge for bottom-up approaches is how to translate damage into cost, with numerous assumptions being required which may be invalid. This paper proposes a new, two stage approach to estimating the marginal cost of rail infrastructure usage. The first stage uses engineering models to simulate damage caused by vehicles on the network. The second stage seeks to establish a statistical relationship between actual costs and damage. It is thus possible to convert damage estimates into costs using actual cost data, rather than through a set of potentially invalid assumptions as in previous approaches. Only the first stage is implemented in this paper. We show that it possible to produce total (annualised) damage measures for three damage mechanisms on five actual track sections in Sweden. Once extended, it will be possible to model the relationship between damage and actual costs for the first time; and thus better understand the relative costs of the different damage mechanisms and in turn inform the level and structure of track access charges

A predictive model of energy savings from top of rail friction control

In this paper the authors present a predictive model of train energy requirements due to the application of a top of rail friction modifier (TOR-FM) versus dry wheel / rail conditions. Using the VAMPIRE® Pro simulation package, train energy requirements are modeled for two sets of TOR-FM frictional conditions, one using full Kalker coefficients and the other by using a Kalker factor of 18%. Both scenarios use a top of rail saturated coefficient of friction of 0.35. Under both TOR-FM frictional conditions, train energy savings are shown for complete laps of the Transportation Technology Center Inc.’s (TTCI) Transit Test Track (TTT) loop, and also when isolating only the tangent section of the loop. However, the magnitude of energy savings varies greatly depending on the Kalker coefficient factor used, highlighting the need to model this relationship as accurately as possible. These simulation results are compared with data obtained from a field study, in which train energy savings of 5.3% (lap) and 7.8% (tangent) are shown due to the application of TOR-FM

Dynanics 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 foun

Effect of the nonlinear displacement-dependent characteristics of a hydraulic damper on high-speed rail pantograph dynamics

A new simplified parametric model, which is more suitable for pantograph–catenary dynamics simulation, is proposed to describe the nonlinear displacement-dependent damping characteristics of a pantograph hydraulic damper and validated by the experimental results in this study. Then, a full mathematical model of the pantograph–catenary system, which incorporates the new damper model, is established to simulate the effect of the damping characteristics on the pantograph dynamics. The simulation results show that large F const (saturation damping force of the damper during compression) and C (initial damping coefficient of the damper during extension) in the pantograph damper model can improve both the raising performance and contact quality of the pantograph, whereas a large C has no obvious effect on the lowering time of the pantograph; the nonlinear displacement-dependent damping characteristics described by the second item in the new damper model have dominating effects on the total lowering time, maximum acceleration and maximum impact acceleration of the pantograph. Thus, within the constraint of total lowering time, increasing the nonlinear displacement-dependent damping coefficient of the damper will improve the lowering performance of the pantograph and reduce excessive impact between the pantograph and its base frame. In addition, damping performance of the new damper model would vary with the vehicle speeds, when operating beyond the nominal-speed range of the vehicle, the damping performance would deteriorate obviously. The proposed concise pantograph hydraulic damper model appears to be more adaptive to working conditions of the pantograph, and more complete and accurate than the previous single-parameter linear model, so it is more useful in the context of pantograph–catenary dynamics simulation and further parameter optimizations. The obtained simulation results are also valuable and instructive for further optimal specification of railway pantograph hydraulic dampers. </p