Network Deterioration Prediction for Reinforced Concrete Pipe and Box Culverts Using Markov Model: Case Study
Article
Article Title | Network Deterioration Prediction for Reinforced Concrete Pipe and Box Culverts Using Markov Model: Case Study |
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ERA Journal ID | 4237 |
Article Category | Article |
Authors | Tran, Huu (Author), Lokuge, Weena (Author), Setunge, Sujeeva (Author) and Karunasena, Warna (Author) |
Journal Title | Journal of Performance of Constructed Facilities |
Journal Citation | 36 (6), pp. 1-12 |
Article Number | 04022047 |
Number of Pages | 12 |
Year | 2022 |
Place of Publication | United States |
ISSN | 0887-3828 |
1943-5509 | |
Digital Object Identifier (DOI) | https://doi.org/10.1061/(ASCE)CF.1943-5509.0001766 |
Web Address (URL) | https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CF.1943-5509.0001766 |
Abstract | Reinforced concrete (RC) pipe and box culverts are widely used as an alternative to bridge structures in road transport networks around the world. The deterioration of the RC culverts is a complex problem caused by combined humanmade and natural processes with various influential factors. Visual inspection is often used to monitor the deterioration of culverts, and the inspection results are used to rate condition of culverts by using a discrete condition rating system. The objective of this case study was to investigate the deterioration of RC culverts at the network and cohort levels by using a Markov model and culverts’ influential factors and inspected condition data. The Markov deterioration model can forecast the future deterioration of a culvert network, which can be used for asset management planning of the culvert network. A real case study with a regional local government in Australia was used to demonstrate the application of this study. The results of network deterioration modeling showed that the deterioration rates of culverts varied with culvert type (pipe and box culvert), built year, demographic location, and pipe size. However, annual average daily traffic (AADT) affected only box culverts. Deterioration prediction was found to be sensitive to the time length of evidence data, which highlights the importance of keeping records of maintenance and rehabilitation activities for producing accurate modeling data. |
Keywords | Culverts; Rehabilitation; Markov deterioration; Failure; Inspection |
ANZSRC Field of Research 2020 | 400508. Infrastructure engineering and asset management |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Royal Melbourne Institute of Technology (RMIT) |
Centre for Future Materials | |
Institution of Origin | University of Southern Queensland |
Funding source | Grant ID Bushfire and Natural Hazard CRC |
https://research.usq.edu.au/item/q7qv6/network-deterioration-prediction-for-reinforced-concrete-pipe-and-box-culverts-using-markov-model-case-study
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