A risk-informed decision support tool for the strategic asset management of railway track infrastructure

The provision of safe, efficient, reliable and affordable railway transport requires the railway track infrastructure to be maintained to an appropriate condition. Given the constrained budgets under which the infrastructure is managed, maintenance needs to be predicted in advance of track failure, prioritized and identified risks and uncertainties need to be considered within the decision-making process. This paper describes a risk-informed approach that can be used to economically justify railway track infrastructure conditions by comparing on a life-cycle basis infrastructure maintenance costs, train operating costs, travel time costs, safety, social and environmental impacts. The approach represents a step-change for the railway industry as it will enable economic maintenance standards to be derived which considers the needs of the infrastructure operator, but also those of users, train operating companies and the environment. Further, the risk-informed capability of the tool enables asset managers to deal with uncertainties associated with forecasting costs and the effects of track maintenance, and unavailability of data. The Monte Carlo simulation technique and a Fuzzy reasoning approach are used to address safety data uncertainties through probabilistic risk assessment allied to expert opinion. The approach is illustrated using data from three routes on the UK mainline railway network. The results demonstrate that the approach can be used to support strategic and tactical levels of railway asset management to inform plausible design and maintenance strategies that realise the maximum benefit for the available budget. </jats:p

A whole life cycle approach under uncertainty for economically justifiable ballasted railway track maintenance

Historically, railway track maintenance strategies have been based on engineering judgement taking into account available budgets and operational safety. This has led to insufficient concern of the socio-economic and environmental costs and benefits of track maintenance. Given the pressure to increase track utilisation, the ageing infrastructure of railway networks, constrained maintenance budgets, the vertical separation of the ownership and operation of railway track infrastructure and rolling stock in many countries, and concerns about the environmental impacts of transport, there is a need to implement economically justifiable maintenance strategies. To this end, this paper presents for the first time an approach to appraise the investment in railway track maintenance. The approach uses a whole life cycle cost analysis under uncertainty approach which considers the costs and benefits of track maintenance to train operators, users and the environment. Monte Carlo simulation technique is used to address data uncertainties associated with the costs and benefits of track and train operation and maintenance. The proposed approach is applied to three different route types on the UK main-line railway network to compare a number of alternative maintenance strategies. In all the three cases more economically beneficial strategies were identified in comparison to those currently adopted

Using Probabilistic Fault Tree Analysis and Monte Carlo Simulation to Examine the Likelihood of Risks Associated with Ballasted Railway Drainage Failure

Inadequate track drainage can lead to a variety of issues, including flooding, accelerated track degradation, and progressive or sudden failure of railway track, slope, or embankment. These can result in unplanned track maintenance, additional passenger travel costs, and damage to third party property. However, railway drainage asset management is challenging because it involves the consideration of large interconnected assets, limited maintenance budgets, and unknown failure probabilities. To address this issue, this paper introduces a risk-informed approach for railway drainage asset management that uses fault tree analysis to identify the factors that contribute to railway drainage flood risk and quantifies the likelihood of the occurrence of these factors using Monte Carlo simulation. This rational approach enables drainage asset managers to evaluate easily the factors that affect the likelihood of railway track drainage failure, thereby facilitating the prioritization of appropriate mitigation measures and in so doing improve the allocation of scarce maintenance resources. The analysis identified 46 basic and 49 intermediate contributing factors associated with drainage failure of ballasted railway track (undesired event). The usefulness of the approach is demonstrated for three sites on the UK railway network, namely, Ardsley Tunnel, Clay Cross Tunnel, and Draycott. The analysis shows that the Clay Cross Tunnel had the highest probability of drainage failure and should be prioritized for maintenance over the other two sites. The maintenance required should focus on blockages because of vegetation overgrowth or debris accumulation. </jats:p

A rational framework for post-flood road network condition recovery

Heavy-precipitation events can lead to widespread flooding and prolonged inundation of road pavement, which in turn would weaken its structural performance and accelerate its deterioration. A major challenge for road authorities is to prepare a suitable and swift recovery programme to restore the road network in the event of flood-related disruptions. Furthermore, widespread damage caused by flooding and other competing needs for recovery resources imposes additional constraints. The situation is exacerbated by the uncertainty and complexity of the post-flood situation. To address this challenge, a methodology for the formulation of a strategic post-flood pavement recovery programme based on life-cycle analysis is proposed in this paper. The resultant road conditions associated with the choice of work standards, the timing of implementation and funding constraints were evaluated in a case study, and a cost-effective recovery programme was formulated. The case study also demonstrated the use of output data to assist road authorities in strategic decision making. This study serves as a guide for road administration to develop a post-disaster recovery programme and provides insights for further research into post-disaster management of infrastructure systems. </jats:p