London Underground (LUL) is one of the largest metro networks in the world and carried nearly 1.5 billion passengers in 2015. This increasing passenger demand leads to higher axle loads and shorter headways in the railway operations. However, this has a detrimental impact on the damage generated at the wheel-rail interface. In spite of the advances in rolling stock and track engineering, new developments in material manufacturing methods and rail inspection technology, cracking in rails still remains a major concern for infrastructure managers in terms of safety and maintenance costs. In this study, field data from two metro lines on the LUL network was analysed to identify the distribution and severity of the different damage types. Detailed vehicle dynamics route simulations were conducted for the lines and the calculated wheel-rail forces were investigated to assess the applicability current models for the prediction of rail damage on metro lines. These models include the Whole Life Rail Model (WLRM), previously developed for Great Britain (GB) main line tracks, and Shakedown theory. The influence of key factors such as curve radius, different friction conditions, track irregularities and wheel-rail profiles on the wheel-rail contact interface have been evaluated and compared with outputs from simulations on mainline routes. The study found that the contact patch energy (Tγ) and the interaction between wear and RCF in rails were highly influenced by the characteristics of metro tracks. It was also shown that both the Tγ and Shakedown methods can provide successful prediction of damage susceptibility of rails. However, in order to increase the accuracy of damage predictions and to ascertain the severity of different damage types, the duty conditions which are observed by the rail and the changes in contact conditions resulting from the successive vehicle passes should be considered in the modelling.
Rolling contact fatigue and wear are two key damage mechanisms that govern rail life. Although there are several different mechanisms affecting both their initiation and propagation, the trade-off between them is important and their accurate predictions can provide significant benefits when planning rail maintenance activities. Through integration with vehicle dynamics simulations, damage models based on the wheel-rail contact energy (Tγ) and Shakedown theory have often been used to predict damage. In this paper, the findings from previous studies are reviewed to identify their limitations. To assess the accuracy of the predictions, their input parameters were compared for sites with and without reported RCF defects from two lines on the London Underground network. The results indicated certain variations and hence, a new wear and RCF damage prediction method was developed using a combined Shakedown Map and Tγ approach. While the wear model predictions were validated by comparison with measured rail wear, the availability of field crack depth measurements enabled the validation of the new RCF crack depth prediction model. Reasonable predictions of crack depth and wear over consecutive intervals have been achieved on various sites which increases the confidence of the models to support future optimisation of maintenance planning.
London Underground is facing the challenge of increasing timetables against spending cuts across renewals and maintenance in all assets. In order to meet this challenge, it is reviewing all maintenance practices to make sure that they are appropriate for the current asset conditions. Management of the wheel–rail interface is critical to maximising the life of wheels and rails through preventative maintenance regimes that ensure all activities offer value for money and safe operation. Detailed monitoring of the asset condition using novel non-destructive techniques has allowed the identification of the problems which currently occur at the wheel–rail interface on the London Underground network. These problems are discussed in this paper along with some of the solutions proposed to manage them. Site observations from a range of rail rolling contact fatigue monitoring sites have also been compared to the outputs from vehicle dynamic simulations. These outputs were post-processed using a circle plotting technique, which illustrates the location, direction and severity of the forces, and the Whole Life Rail Model to predict the susceptibility to rail damage for two rail steel grades. The outputs from these comparisons have helped to illustrate the wheel–rail contact conditions and forces which are driving the observed damage and potential future enhancements to improve the accuracy of the models for predicting the observed rolling contact fatigue damage.
Infrastructure managers (IMs) endeavour to eliminate rail defects at an early stage since they impact on safety and quality of operation and increase system costs. London Underground (LUL) uses several non-destructive testing (NDT) techniques in rail inspection to detect the emerging defects and monitor the growth of previously recorded defects. This task mainly aims to prioritise maintenance and renewal activities and record their completion. However, when the high traffic demand and limited maintenance periods are considered, these requirements bring additional pressures to the maintenance team. To optimise maintenance planning, sufficient and reliable field data along with accurate damage prediction are required. Recent developments in NDT technology has seen the introduction of devices to measure crack depth which is a key parameter in the assessment of crack severity and rail life. Therefore, contrary to previous research which mainly utilised observations of rail surface condition, the use of new NDT techniques can support the development and validation of new rail damage models which will help to improve maintenance planning and move to condition-based maintenance strategy.
The railway industry has focused on the improvement of maintenance through the use of novel technologies. Recently, the utilisation of repair welding to restore the worn area on wheels has been investigated, as it can bring significant savings in wheelset maintenance. Under an Innovate UK AURORA project, a worn wheel that previously operated on London Underground (LUL) was restored using this process. To test its performance and compare with a new standard steel grade wheel, the HAROLD full scale test rig was used in which an LUL vehicle bogie equipped with both the restored and R9 grade wheels was operated under the representative lateral and yaw displacements computed from vehicle dynamics simulations. The wear measurements carried out at the end of test cycles showed that although the restored wheel suffered from initial higher wear, the levels reduced and became similar to the R9 grade wheel. Furthermore, the full-scale testing provided an opportunity to validate the wear model predictions which were conducted using the vehicle dynamics simulations utilised in testing inputs. It was found that while the flange wear predictions were higher, the tread wear estimations were smaller than the measurements on the R9 grade wheel.
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