Broad Research

Notable Projects

In2Track3

Purpose: Predicting track degradation rates.
What We Did: Collaborated with Network Rail to build machine learning models (XGBoost) predicting Top 35m degradation rates on the LEC1 and LTN1 lines using New Measurement Train data and other sources like weather and network reports. Outcomes: Achieved an R2 value of 93.4% and a root mean squared error of 0.19mm, improving prediction accuracy by 11% and 0.12mm respectively.
Problem Solved: Enhanced predictive maintenance for railway tracks.

System for Ticketing Ubiquity with Blockchain (STUB)

Purpose: Improving data sharing in the ticketing industry.
What We Did: Explored distributed ledger technology to enable cross-party consensus and improve data sharing. Outcomes: Developed concepts using distributed knowledge graphs.
Problem Solved: Addressed inefficiencies in ticketing data sharing.

Wildfire

Purpose: Assessing wildfire threats to rail infrastructure.
What We Did: Investigated current and future wildfire threats, building machine learning models to predict fire probability near rail networks.
Outcomes: Identified high-risk areas for better resilience planning.
Problem Solved: Mitigated risks of track buckling, overhead line sag, and visibility issues from wildfires.

TravelXR

Purpose: Enhancing internal routing at rail stations.
What We Did: Developed a dynamic routing model using the A* algorithm and Delaunay triangulation to map spaces from PDFs.
Outcomes: Improved customer navigation within stations.
Problem Solved: Streamlined passenger movement and station management.

TransiT

Purpose: Creating a digital twin for the West Midlands.
What We Did: Built models combining transport network ontologies with real data streams to enhance regional simulations.
Outcomes: Provided detailed insights into transport layers and operations.
Problem Solved: Improved transport planning and management.

Industry Challenges Addressed

• Digital Railway: Tackling unclean and inaccessible transport data, and ensuring pragmatic AI implementation.

Research Capabilities

• Computer/Data Science
• Artificial Intelligence
• Machine Learning
• Blockchain/Distributed Ledger Technology
• Ontologies

Project Interests

• Building ML/AI models for rail contexts (condition monitoring, passenger data)
• Using climate data for adaptation planning
• Secure and economical data sharing in rail environments
• Deploying STUB and TravelXR algorithms in real scenarios

Research Categories

• Data Science & Cyber-Security
• Environment & Climate Action
• Mobility & Transportation

For inquiries, please email: railway@contacts.bham.ac.uk.

Notable Projects

West Midlands Digital Twin: This project aims to create a digital replica of the West Midlands railway network. By simulating real-time operations, we can optimise performance, predict maintenance needs, and enhance passenger experience. The outcomes include improved efficiency and reduced operational costs, addressing the challenge of modernising railway infrastructure.

PERFORMINGRAIL: Focused on integrating advanced simulation and control systems to enhance railway performance. This project tackles issues like energy efficiency and operational reliability. Our team developed algorithms and software tools that have been implemented to streamline operations and reduce energy consumption.

SMRT Power Simulation: In collaboration with Singapore’s SMRT, this project involves simulating power usage and optimising energy consumption for metro systems. The goal is to achieve significant energy savings and support sustainable urban transport. The outcomes include reduced carbon footprint and operational costs.

Industry Challenges Addressed

Our research addresses the challenges of the Digital Railway, focusing on modernising railway operations through advanced simulation, optimisation, and data analysis. We aim to enhance energy efficiency, operational reliability, and sustainability.

Research Capabilities

Our team excels in:

• Simulation
• Optimisation
• Analysis
• Software development
• Big data analytics

Project Interests

We are particularly interested in industrial projects, European Commission (EC) initiatives, and Innovate UK collaborations. Our goal is to apply our research in real-world environments to drive innovation and efficiency in railway systems.

For inquiries, please email: railway@contacts.bham.ac.uk.

If you would like to get in touch, please email: railway@contacts.bham.ac.uk.

Extreme weather events of many types regularly affect railway infrastructure and the provision of train services across the UK.

If the UK is due to have hotter, drier summers and warmer, wetter winters in the future, how will this affect the railway network and how can we adapt to these changes?

These are the two key questions that lead our research.

Resilience is the ability of a system, the railway network, to reliably resist and recover from the effects of external disrupting factors such as weather and climate change. This includes having sufficient redundancy to absorb the impact and recover quickly, resuming normal operations; or being able to reroute and redeploy workers and equipment to make repairs wherever required.

The physical resilience of rail infrastructure is a topic that has been investigated here at BCRRE for over ten years. By improving our understanding of the effects of extreme weather on rail infrastructure we can begin to develop ways of redesigning and adapting the railways to resist the impact of weather, creating reliable railway infrastructure for the future. The operational resilience of train services in the UK focuses particularly on investigating delay propagations. If one train is affected by one incident and is delayed, this can affect the whole network.

Research areas include:

• TRaCCA – investigating the risks associated with extreme weather events and climate change and the impact these will have on our railway networks in the future.
• Rail Adapt project – developed a comprehensive adaptation framework, to support the rail industry in improving their processes for adapting its infrastructure.
• SIRMA – to develop risk models, mitigation, and resilience-based decision support tools utilising a systems of systems approach. This ensures that transport infrastructure along Atlantic coastlines is resilient under future climates to a variety of fast-acting (e.g., storm) and slow-acting (e.g., corrosion) hazards.

If you would like to get in touch, please email: railway@contacts.bham.ac.uk.

The railway infrastructure significantly contributes to rail’s carbon footprint, offering opportunities to consider lower-carbon materials and designs, manage assets more effectively, use AI and data science for decision-making, and apply whole-systems-thinking.

Decarbonising the Railway

Sustainable Smart Materials: development of eco-friendly construction and railway materials, such as high-damping and self-healing concrete, 3D printing composites, and self-sensing materials. Advanced simulations, AI, and data science help understand vibration problems.

Lifecycle Performance and Forensics: sustainability-based management of infrastructures throughout their lifecycle, including forensic investigations during design, construction, operation, maintenance, and disposal. This research supports decarbonisation and has led to a new ISO Standard for recycling rolling stock.

Infrastructure Engineering, Resilience, Reliability, and Risk: analysing and quantifying design reliability, safety, risk, and uncertainty to ensure operational readiness and resilience. Innovative solutions to extreme events combine theory with practice to determine robustness, vulnerability, and resilience of materials and structures.

Research Areas

• Sustainable and smart materials
• Infrastructure engineering and resilience
• Reliability, risk, and uncertainties
• AI and data sciences
• Net zero buildings
• Noise and vibration mitigation
• Systems thinking for greener infrastructures

Railway Geotechnical Engineering and Asset Management

Our research involves lifecycle assessment under uncertainty of railway track designs, maintenance schemes, and strategies. We develop novel approaches for building and maintaining tracks, and tools for asset management decision-making. Our life cycle analysis considers costs and benefits to infrastructure owners, train operators, users, and the environment.

We also focus on innovative solutions for track design and maintenance, understanding the effects of dynamic train loads, and developing solutions like micro-piling, sand grips, under-sleeper pads, and geotextiles. Effective drainage asset management is addressed through low-carbon products and risk analysis decision support systems.

For inquiries, please email: railway@contacts.bham.ac.uk.

Improvement in aerodynamic efficiency of a train can lead to significant reductions in the amount of fuel required, helping to meet decarbonisation targets.

These effects are not only apparent for high-speed passenger trains but also slower moving freight trains, which are traditionally highly bluff-shaped vehicles with little aerodynamic consideration. Better understanding of these key aerodynamic parameters can improve train modelling simulations, leading to better train pathing diagrams and timetables. This will undoubtedly improve train management leading to less fuel consumption and greater efficiency.

Unlike other vehicles, it is not only the aerodynamic drag that is important for trains, however. The highly turbulent aerodynamic flows created with large velocity and pressure magnitudes can create safety issues when interacting with passengers waiting on platforms or trackside workers, railway infrastructure when passed by the train (such as noise barriers and hoardings), or through interactions with local wind conditions which may result in train instabilities, which in the worst case scenario can lead to overturning. There are also issues related to pressure waves created as a train enters into a tunnel, which can cause effects ranging from aural discomfort for passengers to micro-pressure waves exiting the tunnel as sonic booms.

Related to the theme of decarbonisation is that of pollution dispersion.

Exhaust emissions from diesel rolling stock will be directly influenced by the aerodynamic flow surrounding moving vehicles, potentially leading to the intake of pollutants back into the train through the air conditioning intakes.

The lead academic for Areodynamics is Dr David Soper.

Research areas include:

• Aerodynamic drag and slipstream velocity measurements
• Static pressure pulse measurements and sonic boom
• Pressures acting on the train
• The effects of crosswinds at various yaw angles, train effects and local wind environment analysis
• Aerodynamic pressures acting on trackside structures, effects of a train passing through a tunnel and effects due to train design and size
• Design optimisation
• Aerodynamic loads affecting ballast flight and slab track running
• Pollutant dispersion

If you would like to get in touch, please email: railway@contacts.bham.ac.uk.

We are delving deeper to understand the factors affecting train energy use. Our researchers are experts in railway traction and propulsion systems, focusing on projects like the HydroFLEX train, the UK’s first hydrogen-powered train using electricity from hydrogen fuel cells.

Our research uses basic physics and low-cost energy principles. Energy is transferred, not created, allowing efficient energy use in trains. Regenerative braking collects energy to return to the electricity supply network or store in batteries for reuse.

The railway uses electricity and diesel for traction, but diesel will decline as governments meet climate commitments. Sustainable Traction Systems research explores low-carbon energy for railways. Hydrogen, produced via electrolysis using renewable electricity, can be zero-carbon, aiding global decarbonisation.

Research Areas:

• Novel Traction Systems for Sustainable Railway Futures in low-income countries (LICs)
• HydroFLEX Mainline Testing and Approvals
• Optimisation of train traction energy reduction (OTTER)
• Network Rail Remote Earth Monitoring
• Metro energy saving technology in Singapore SMRT
• Dual fuelling locomotives for carbon and emissions reduction

The lead academic for Sustainable Traction Systems is Dr Stuart Hillmansen.

Rail decarbonisation requires electric trains and improved energy efficiency. The rail industry’s carbon footprint comes from traction and non-traction equipment, using fossil fuel-generated electricity. Energy consumption can be reduced by controlling power flows between networks, utilising regenerative braking, and supporting traction networks with renewable energy.

We investigate high voltage DC for rail electrification, embedding electric railways in micro grids fed by renewable power. Integrating electric railways with road transport can achieve 100% clean journeys, facilitated by charging points at stations and solar photovoltaics.

Research Areas:

• Boost-inverters for fuel cell trains
• Hybrid power trains with fuel cells and batteries
• Power converters for battery trains
• Traction substations with static frequency converters
• Medium voltage DC railways
• Smart Soft Open Points for electric railways
• Rail-to-grid energy management systems
• Fast charging of electric vehicles from traction power supply

The lead academic for Power electronics and energy is Dr Pietro Tricoli. 

For inquiries, please email: railway@contacts.bham.ac.uk.