Risk analysis methodology for ship-bridge allisions – A combined probability and consequence analysis
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| Title: | Risk analysis methodology for ship-bridge allisions – A combined probability and consequence analysis |
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| Authors: | Hörteborn, Axel, 1986, Sha, Yanyan, Ringsberg, Jonas, 1971, Lundbäck, Olov, 1971, Mao, Wengang, 1980 |
| Source: | Engineering Structures. 347:1-13 |
| Subject Terms: | Allisions, Maritime risk analysis, Automatic identification system data, Monte Carlo simulations |
| Description: | Ship-bridge allision risk assessments often address either probability or consequence; integrations of both in a unified methodology are rare. This paper fills that gap by introducing Ship Traffic Allision Probability using Monte Carlo Simulations – consequence (STAPS-cons), a methodology where a mid-fidelity simulation meth-odology developed for probability assessment is used together with the results of Finite Element Analysis (FEA) simulations to include consequence assessments. Using Automatic Information System (AIS) data and the pro-posed methodology, a potential bridge over Norway’s Bjørnafjorden is analysed in a case study to determine the risk of structural collapse. The case study also illustrates how the risk is affected by different input parameters, both related to probability and consequence estimations. Five scenarios were analysed in this case study; three passed and two failed the Norwegian criterion for the probability of structural collapse, which is lessfrequent than 10-4 per year. A 20 % increase in the duration of a ship’s miss of turning point notably raised both the allision frequencies and the necessary levels of energy the bridge must withstand. Inanother scenario, where a less stiff bridge structure was analysed, the demand on the global structure decreased. In conclusion, the STAPS-cons methodology represents a significant advancement in the field of ship-bridge allision risk assessment. By integrating probability and consequence assessments, this methodology offers a more robust and comprehensive tool for managing the risks associated with increased shipping traffic and bridge construction in navigational waters. |
| File Description: | electronic |
| Access URL: | https://research.chalmers.se/publication/549290 https://research.chalmers.se/publication/549290/file/549290_Fulltext.pdf |
| Database: | SwePub |
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Nájsť tento článok vo Web of Science | Abstract: | Ship-bridge allision risk assessments often address either probability or consequence; integrations of both in a unified methodology are rare. This paper fills that gap by introducing Ship Traffic Allision Probability using Monte Carlo Simulations – consequence (STAPS-cons), a methodology where a mid-fidelity simulation meth-odology developed for probability assessment is used together with the results of Finite Element Analysis (FEA) simulations to include consequence assessments. Using Automatic Information System (AIS) data and the pro-posed methodology, a potential bridge over Norway’s Bjørnafjorden is analysed in a case study to determine the risk of structural collapse. The case study also illustrates how the risk is affected by different input parameters, both related to probability and consequence estimations. Five scenarios were analysed in this case study; three passed and two failed the Norwegian criterion for the probability of structural collapse, which is lessfrequent than 10-4 per year. A 20 % increase in the duration of a ship’s miss of turning point notably raised both the allision frequencies and the necessary levels of energy the bridge must withstand. Inanother scenario, where a less stiff bridge structure was analysed, the demand on the global structure decreased. In conclusion, the STAPS-cons methodology represents a significant advancement in the field of ship-bridge allision risk assessment. By integrating probability and consequence assessments, this methodology offers a more robust and comprehensive tool for managing the risks associated with increased shipping traffic and bridge construction in navigational waters. |
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| ISSN: | 18737323 01410296 |
| DOI: | 10.1016/j.engstruct.2025.121731 |