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Details of Grant 

EPSRC Reference: GR/S07292/01
Title: An Intelligent Safety Prediction System For Rail Design And Maintenance
Principal Investigator: An, Professor M
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Railway Safety Ltd
Department: Civil Engineering
Organisation: University of Birmingham
Scheme: First Grant Scheme Pre-FEC
Starts: 01 September 2003 Ends: 30 June 2006 Value (£): 125,842
EPSRC Research Topic Classifications:
Intelligent & Expert Systems Transport Ops & Management
EPSRC Industrial Sector Classifications:
Information Technologies Transport Systems and Vehicles
Related Grants:
Panel History:  
Summary on Grant Application Form
To improve railway safety, the new Railway (Safety Case) Regulation requires railway operators to prepare a comprehensive safety case and to secure its acceptance by the Health & Safety Executive (HSE). Therefore, railway safety analysts need to develop and employ safety assessment approaches for their safety case preparation. However, in many circumstances, the application of traditional tools may not give satisfactory results due to the lack of safety data or the high level of uncertainty involved in the safety data available. It is therefore essential to develop new safety analysis methods to identify major hazards and assess the associated risks in an acceptable way in various environments where such traditional tools cannot be effectively or efficiently applied. In this project, the primary aim is to investigate the principal safety issues in the railway infrastructure, devise and test a model and process for appraising new designs and maintenance schedules, also diagnosing, using artificial neural networks and approximate logic techniques. This will provide railway safety analysts, operators and infrastructure managers with a method and tool to improve their design and maintenance, and set safety standards. This safety prediction system could be applied to defining risks and the numerical levels of expectation. This will support the industry's efforts to run the rail network with normal service while keeping risks as low as reasonably practicable (ALARP). A secondary aim is to investigate how the intelligent safety analysis can provide insight into how risks contribute to accidents. The project will also provide an opportunity to transfer technologies already in the offshore, nuclear and aviation industries to rail.
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Further Information:  
Organisation Website: http://www.bham.ac.uk