A risk ranking strategy for network level bridge management

Abstract

This paper presents the development of a qualitative risk ranking strategy for characterising a network of bridges into groups with similar risk levels, which can form the basis for developing a risk based inspection regime over a bridge network. The factors affecting risk are identified and rationally combined to present various attributes of bridges. A qualitative scoring system is then introduced that uses the attributes to rank bridges in terms of their relative risk. Sensitivity analysis is performed to quantify the effect of relative weights of the attributes on the risk scores. The methodology is demonstrated through its application on the UK's Network Rail bridge stock and a random sample of bridges is ranked according to the proposed method. One of the factors used to evaluate the risk scores is comparable with the bridge condition index. A reasonable agreement between them is observed within the sample bridges. The proposed method will be beneficial to bridge owners in identifying the bridges according to their risk levels in a simple and systematic manner. Inspections and interventions can be planned based on this risk ranking strategy to maintain a consistent risk level across the network

Railway bridge structural health monitoring and fault detection: State-of-the-art methods and future challenges

“…19 This process should be based on the analysis of how the degradation mechanism of the bridge influences the bridge behaviour. 67–69 Furthermore, a preventive maintenance strategy can be adopted by knowing the probability of failure of the bridge and its components, and through an optimization process maintenance actions can be investigated, by considering their maintenance cost and probability of failure. 70 Finally, it should be noted that the modal parameters of real bridges are strongly influenced by environmental changes (such as increase in air temperature), and therefore, an optimal SHM method is required to be adaptive to environmental changes in order to detect only actual changes to the bridge health state, without activating false alarms due to changes in environmental conditions.…”

A Multi-Level Asset Management Decision Method Considering the Risk and Value of Bridges

“…Baker (2009) suggested a method to calculate the priority order considering cost changes according to the definition of risk cases from various viewpoints and risk reduction. Sathananthan et al (2010) suggested a method to decide the risk for each bridge at the network-level and calculate the relative importance.…”

Bridge condition modelling and prediction using dynamic Bayesian belief networks

“…Using DBN the model is then extended to incorporate time dependent characteristics in order to obtain deterioration profiles for the group under different environmental exposure conditions. These profiles together with a risk ranking strategy for the bridge group, as presented in Sathananthan, Onoufriou, and Rafiq, (2008), can be utilised to develop group/stock level risk-based inspection plans (Sathananthan, 2010). The sensitivity of the results towards various assumptions and input parameters is also discussed in this paper.…”