Novel Approach for Dynamic Safety Analysis of Natural Gas Leakage in Utility Tunnel
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 12, Issue 1
Abstract
This paper proposes a systemic framework for dynamic safety risk analysis for natural gas pipeline leakage in a utility tunnel, which merges the bow-tie model (BT), Bayesian network (BN), and fuzzy set theory (FST) combined with monitoring data. Firstly, the hazard factors that cause natural gas leakage in a utility tunnel are identified to establish a BT model for simulating the causal relationship under specific accident scenes. Subsequently, the BT model is mapped to the BN model via a logic relationship for probabilistic reasoning, in which the prior probability of basic event is obtained through multiexpert scoring and FST. Then, the critical events can be obtained by using sensitivity analysis. Finally, combined with the monitoring data, the prior probabilities are updated to obtain the dynamic analysis result. A case study relating to safety risk analysis of overhead natural gas pipelines in a utility tunnel in the city of Liupanshui, China, is used to verify the feasibility of the approach as well as its application potential. The proposed method not only reduces the subjectivity of expert estimations, but also provides dynamic guidance for the risk analysis of utility tunnel gas pipelines.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This research was funded by the National Natural Science Foundation of China (Grant No. 51574201), Research and Innovation Team of Provincial Universities in Sichuan (No. 18TD0014), and Excellent Youth Foundation of Sichuan Scientific Committee (No. 2019JDJQ0037).
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Published In
Journal of Pipeline Systems Engineering and Practice
Volume 12 • Issue 1 • February 2021
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Oct 30, 2019
Accepted: Jun 8, 2020
Published online: Oct 13, 2020
Published in print: Feb 1, 2021
Discussion open until: Mar 13, 2021
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