Abstract
Bridge Management Systems (BMS) are decision support tools that have gained widespread use across the transportation infrastructure management industry. The Whole Life Cycle Cost (WLCC) modelling in a BMS is typically composed of two main components: a deterioration model and a decision model. An accurate deterioration model is fundamental to any quality decision output.There are examples of deterministic and stochastic models for predictive deterioration modelling in the literature, however the condition of a bridge in these models is considered as an ‘overall’ condition which is either the worst condition or some aggregation of all the defects present. This research proposes a predictive bridge deterioration model which computes deterioration profiles for several distinct deterioration mechanisms on a bridge.The predictive deterioration model is composed of multiple Markov Chains, estimated using a method of maximum likelihood applied to panel data. The data available for all the defects types at each inspection is incomplete. As such, the proposed method considers that only the most significant defects are recorded, and inference is required for the less severe defects. A portfolio of 9726 masonry railway bridges, with an average of 2.47 inspections per bridge, in the United Kingdom is the case study considered.
Highlights
The functional operation of transportation networks is contingent on diverse asset portfolios including civil infrastructure
The railway in Great Britain includes over 26,000 bridges, which are constructed out of many different materials and are of various ages
It is a significant challenge to achieve this within the budgetary constraints placed on railway infrastructure managers
Summary
The functional operation of transportation networks is contingent on diverse asset portfolios including civil infrastructure. Network Rail (NR) is the infrastructure asset manager for the railway network in England, Scotland, and Wales. NR is responsible for the inspection, assessment, maintenance, and repair of this portfolio of bridges. Ensuring the bridges are maintained to a suitable safety threshold is critical, as the consequence of structural failures would be enormous. The risk of structural failure is reduced by performing inspections and maintenance as per the industry guidelines [1]. It is a significant challenge to achieve this within the budgetary constraints placed on railway infrastructure managers. A decision support tool known as a Bridge Management System (BMS) is used to perform any required modelling and to prioritise and justify decisions to the regulator
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