ABSTRACT

Bridges play a pivotal role in the connectivity of the road networks. Australia’s ageing infrastructure requires an ongoing maintenance program to sustain a reliable and accessible road network. Regular inspection strategies on bridge infrastructure inform the authorities of any probable risk to the bridges and identify necessary repair works required to rectify the deteriorated or damaged bridge components. Budget limitations often initiate creation of strategies for optimisation of rehabilitation works. The paper presents a probabilistic methodology to predict the deterioration of concrete bridge components over the useful life of the bridge. The risk of deteriorated bridge components have been investigated and therefore a methodology to optimise level of service criteria has been suggested. The inspection intervals have also been investigated and based on the deterioration of components, an optimised inspection interval strategy has been suggested.

A discrete Markov chain model was used in this study to suit the qualitative nature of level 2 bridge condition inspection data. The quantitative data can be used with this methodology if their continuous values are converted into discrete states by using some thresholds as shown in published studies of bridges, pavements and sewer pipes. The results of the case study shows that inspection interval for level 2 inspection could be twice longer than the recommended inspection interval by the road authority. The level of service criteria could be iterated optimised further to achieve organisational level of acceptable risk.

This study provides a computational procedure to not only find the inspection interval with lowest cost for asset management of bridge components, but also intervention criteria program to allow for the highest acceptable risk level. The Markov chain theory is adequately used to model the change of discrete condition states and Monte Carlo simulation is used to find optimal inspection interval with the lowest cost; and also to find intervention criteria with highest acceptable risk. A case study with actual inspection data shows that next inspection time for precast concrete girder and slab being in condition 1 and 2 could be 10 years as compared to the recommended 2–5 years by the road authority. Due to relatively low rate of deterioration for bridge girder and slab of the case study, the penalty factor shows relatively mild and non-linear effect on inspection interval while and annual interest rate show significant impact on the annual cost rate (Figure 1). For keeping slab components within the category of medium risk significance, 100%, 100%, 60% and 27% intervention criteria have been suggested for the components being in conditions 1, 2, 3 and 4 respectively (Table 1). Annual cost rate for condition 3 and annual number of undetected poor condition (condition 4) girder with no penalty. https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781315207681/cd556cd4-4dcf-4efe-8e29-56fc67b8bfbd/content/fig53_1.tif"/> Resulted optimised Level of service criteria for slab component.

Intervention Criteria

C*

If Probability (%) Greater Than

Rehab to Condition

C1

100%

1

C2

100%

2

C3

60%

2

C4

27%

1

Condition state