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A 3S_BN Based Approach for the Quantitative Risk Assessment of Third-Party Damage on Pipelines

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Proceedings of the 13th International Conference on Damage Assessment of Structures

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Abstract

Third-party damage (TPD) is identified as the greatest threat to the safe operation of pipelines in different countries. The traditional TPD risk assessment methods cannot calculate the failure probability quantitatively and ignore the conditional dependence between risk influence factors (RIFs). In view of this, a theoretical system called 3S_BN is proposed based on Statistics, Scenario analysis, Safety barrier, and Bayesian network to realize the quantitative risk analysis of TPD. According to the 3S_BN, RIFs and their causal relationships are analyzed firstly. After that, a BN model including multi-state risk is developed and historical data and experts’ opinions are used for the computation of conditional probability table. Besides, evidence theory is adopted in order to improve experts’ belief. And then, the proposed approach is verified by a fire and explosion accident. Through sensitivity analysis and posterior probability reversal, the key influence factors and possible paths of the incident are confirmed. Finally, as discussed, the model can be applied to the TPD risk management of pipelines to continuously improve the safety level of pipelines.

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Acknowledgements

This research was supported by the National Key R&D Program of China (Grant No.2018YFC0809300) and the Major scientific and technological innovation projects of Shandong (Grant No. 2018YFJH0802). The authors are grateful for the valuable suggestions of reviewers.

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Correspondence to Xiaoyan Guo .

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Guo, X., Zhang, G., Wang, Y., Zhang, L., Liang, W. (2020). A 3S_BN Based Approach for the Quantitative Risk Assessment of Third-Party Damage on Pipelines. In: Wahab, M. (eds) Proceedings of the 13th International Conference on Damage Assessment of Structures. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-8331-1_54

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  • DOI: https://doi.org/10.1007/978-981-13-8331-1_54

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-8330-4

  • Online ISBN: 978-981-13-8331-1

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