ABSTRACT
Bridges are critical assets for the safe, reliable, and functional operation of transportation networks. Estimating future safety and reliability measures through predicting changes to asset condition, forecasting required interventions, and developing equitable resource allocations from limited budgets is a challenging task. Network Rail (NR) is the infrastructure manager for the railway in Great Britain and is responsible for the management of over 26,000 bridges. NR uses a strategic model (Bridges Forecasting Model) to forecast the work volumes, expenditure, and condition outputs for its bridge portfolio in different funding scenarios. In this paper a ‘hindcast’ exercise is presented. A hindcast has been employed to refine model parameters by calibrating the modelled bridge condition against the portfolio’s observed condition profile between 2010 and 2023. This has enabled key decision makers (Government, regulators, central and regional asset engineers in NR) to have greater confidence in the outputs of the forecasting model.
