Network Rail Limited is the owner (via its subsidiary Network Rail Infrastructure Limited, which was known as Railtrack plc before 2002) and infrastructure manager of most of the railway network in Great Britain. Network Rail is an "arm's length" public body of the Department for Transport with no shareholders, which reinvests its income in the railways.Network Rail's main customers are the private train operating companies (TOCs), responsible for passenger transport, and freight operating companies (FOCs), who provide train services on the infrastructure that the company owns and maintains. Since 1 September 2014, Network Rail has been classified as a "public sector body".To cope with fast-increasing passenger numbers, (as of 2021[update]) Network Rail has been undertaking a £38 billion programme of upgrades to the network, including Crossrail, electrification of lines and upgrading Thameslink.In May 2021, the Government announced its intent to replace Network Rail in 2023 with a new public body called Great British Railways.
Railway overhead line systems play a critical role in national railway infrastructure. However, climate change driven by anthropogenic activities has increasingly affected the construction and operation of such systems. Railway overhead lines must therefore be designed and managed to withstand a range of climate-related hazards, including storms, extreme rainfall, natural erosion, high temperatures, snow events, etc. This paper aims to enhance resilience management by developing a 6D Building Information Modelling (BIM) framework for a railway overhead line along the Market Harborough to Wigston located at the East Midland, U.K., and integrating it with a structured risk assessment process aligned with ISO 31000:2018. The proposed process encompasses risk identification, analysis, evaluation, treatment, and continuous monitoring of detailed components to assure public safety. Note that lesser or simplified information could endanger the systems and the public. Our results are the first to demonstrate that implementing a 6D BIM-based approach significantly improves the resilience of railway overhead line systems against climate change impacts by supporting informed decision-making, lifecycle cost analysis, and proactive risk mitigation. This study advances resilience management practices in railway systems and provides a systematic approach to addressing climate-related risks in critical infrastructure.
This paper presents an advanced Petri Net (PN) modelling framework for the risk-based management of ageing reinforced concrete (RC) transportation infrastructure under climate change. The proposed framework introduces a modular PN architecture that decomposes infrastructure systems into interconnected submodules encompassing deterioration mechanisms, inspection policies, and maintenance strategies. These submodules are integrated into component, system and network-level PN modules, enabling holistic simulation and optimisation of asset-level decisions. A probabilistic degradation process is embedded within each submodule, incorporating climate-dependent parameters and allowing seamless integration of regional/national climate projections. Additionally, a multivariate statistical formulation is employed to capture interdependencies between component deterioration rates, enabling system-level reliability assessment.To demonstrate the framework’s application, the model is implemented for a case-study RC bridge using the UKCP18 climate projection dataset, which includes 28 distinct climate scenarios. Monte Carlo simulations are conducted for three environmental trajectories: baseline ageing, expected and pessimistic climate change. Results indicate that climate change accelerates corrosion-induced deterioration, highlighting the need for adaptive inspection and maintenance strategies.The proposed PN framework provides a generalised, data-driven tool for long-term infrastructure durability and life-cycle risk management under uncertainty.
Railway electrification is emerging worldwide as a key enabler of high-capacity, low-carbon transport. However, this transition introduces substantially more inflexible traction loads while leaving much of the regenerative braking energy underutilized. This may further place additional strain on already stretched power grids, degrading traction voltage stability and the overall system energy performance. This paper presents a novel dynamic and economic energy management solution for railway power supply systems, which integrates a railway microgrid at the terminal station of a feeding zone of the traction network and coordinates on-site energy storage systems, renewable generation, and local utility grid resources to enhance the overall system efficiency while sustaining desired traction voltage levels. A hierarchical reinforcement learning framework is designed to determine the optimal strategies. In this framework, the upper-level agent provides time varying allowable voltage ranges to the lower-level agent, which serve as reference guidance for energy management. Subsequently, the lower-level agent treats these received voltage bands as operational limits, enabling it to coordinate energy scheduling while maintaining voltage regulation performance. Case studies conducted on a representative UK feeding zone demonstrate that the proposed solution can effectively improve the traction voltage level at a weak node in the traction network while cutting the grid electricity procurement costs by as much as 35.2%, highlighting its practical significance for railway electrification.
Rail transit expansion, particularly in cold climates, has raised practical concerns about ice accumulation on overhead catenary systems, which can cause severe asset failure and service disruption. Recent studies have primarily modeled linear pantograph-catenary dynamics under icing conditions. This study aims to investigate the influence of geometric non-linearities and increased ice formation on the dynamic performance of a validated pantograph-catenary system. Ice formation was modeled by increasing the contact wire’s density, and the catenary system was modeled using nonlinear finite elements for the droppers, contact, and messenger wires. Unlike linear models, contact loss occurred at lower ice thicknesses and exhibited a stronger nonlinear relationship. Although greater ice thicknesses generally increased contact wire displacement, acceleration trends showed high variation. Modal analysis of damped frequencies suggested that pantograph vibrations induced these variations rather than changes in catenary modes. These novel findings reveal a more pronounced nonlinear dynamic response than previously reported and emphasize the importance of further developing ice formulation and modeling methods to mitigate failures such as those seen in Slovenia’s 2014 icing event.
Between January and April 2016, three cutting slope failures occurred at Farnley Haugh, Prudhoe and Wylam Scar, along the Newcastle to Carlisle railway line in the Tyne Valley, Northumberland, UK. The valley's superficial geology comprises a complex sequence of Devensian tills, granular glaciofluvial deposits and laminated high-plasticity clays, causing spatial variability in slope stability due to differing soil shear strengths and groundwater conditions. The Farnley Haugh failure was the most significant, severely damaging the railway and causing a line blockage. All three failures occurred during periods of heavy rainfall. Geomorphological and geotechnical assessments showed the original cutting slopes were over-steep with thick granular glaciofluvial deposits exposed on their faces. Forensic slope stability analyses using data from site works, laboratory testing and historical records indicated that before failure, the slopes possessed only marginal stability and low resilience to extreme weather linked to climate change. Existing drainage and vegetation root systems provided insufficient protection. This study demonstrates that substantial sections of Northumberland's aging rail infrastructure remain vulnerable. As climate change intensifies, earthwork deterioration rates will continue to increase. Long-term investment is therefore essential to monitor, maintain and ensure the future safety and resilience of the UK rail infrastructure.
