Using algorithms to provide bridge managers with consistent and complete early estimates of possible future maintenance interventions: Project STABILITY under the ETH Mobility Initiative

Abstract

It is advantageous in the development of train schedules to know far in advance when interventions are required on bridges, as well as the types of intervention and the extent of track possession required. So that SBB bridge managers can provide this information, it would be advantageous for them to obtain a consistent and complete overview of the required interventions and associated track possessions for all their bridges up to 25 years in advance. Generating this consistent and complete overview requires: • an understanding of the current condition of the components of each bridge and their likely evolution over time, subject to the multiple deterioration processes affecting them, • a general impression of the risk of failure related to the condition of the components, and • an understanding of the possible preventive interventions and which conditions trigger them, as well as the costs and impacts on service of executing them. As there is a large and growing amount of detailed information on these items within the SBB, SBB now has the chance to modify its intervention planning process to make even more consistent and complete estimates of the future required interventions and associated track possessions. With this in mind, this document proposes an algorithm that can be used to make initial complete and consistent estimates of the type and time of future deterioration-related interventions on all SBB bridges. The algorithm uses existing data, and expert opinion where there is not yet data available, to estimate both the future condition of bridge components and the required interventions, as well as the required possession times and approximate costs. An indication of the failure risks is obtained for each bridge using fault trees to capture the relationship between failure and the condition of the individual components, as well as how it changes over time. Having an indication of failure risks helps to determine how urgently an intervention needs to be executed. In addition to improving the consistency and completeness of the estimates, it is expected that embedding the algorithm in the SBB intervention planning process will improve the efficiency of the planning process. In this document, the algorithm is explained first at the bridge portfolio level, using the Brügg-Zollikofen railway line to demonstrate how it would be used to provide an overview of the upcoming interventions. The algorithm is then explained in more detail using individual bridges of four different types (a steel truss, a masonry, a concrete, and a composite railway bridge). It is shown that the algorithm can generate a complete and consistent overview of the type and time of interventions required in the future, an initial overview of the likely lengths and types of possession time required, and the likely costs of intervention. It is also shown that the algorithm can give an indication of the failure risks associated with each bridge and how they might evolve over time. In other words, the algorithm includes all the aspects normally considered by an SBB bridge manager in the early stages of the planning of deterioration-related interventions. It is expected that this consistent and complete overview of the upcoming required interventions will enable bridge managers to better communicate the needs for track possession times early in the train schedule planning process, which in turn will help ensure stable train schedules. Additionally, it generates a solid basis for the initiation of detailed investigations of the bridges by engineering offices, i.e., the investigations that result in the information required to decide as to when an intervention is required, as well as what type of intervention and track possession are required. The requirements in terms of data and computer support to use the algorithm, and the need for the results to be verified by bridge engineers are discussed, along with how new data is to be integrated into the models used to make the estimates.