Novel approach for dynamic safety analysis of natural gas leakage in utility tunnel

Title

Novel approach for dynamic safety analysis of natural gas leakage in utility tunnel

Subject

Natural gas
Risk analysis
Risk assessment
Fuzzy set theory
Sensitivity analysis
Natural gas pipelines
Monitoring
Safety engineering
Systems engineering
Gases
Bayesian networks
Risk perception
Natural gas wells

Description

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. 2020 American Society of Civil Engineers.
1
12

Publisher

Journal of Pipeline Systems Engineering and Practice

Date

2021

Contributor

Hu, Q.J.
Tang, S.
He, L.P.
Cai, Q.J.
Ma, G.L.
Bai, Y.
Tan, J.

Type

journalArticle

Identifier

19491190
10.1061/(ASCE)PS.1949-1204.0000498

Collection

Citation

“Novel approach for dynamic safety analysis of natural gas leakage in utility tunnel,” Lamar University Midstream Center Research, accessed May 14, 2024, https://lumc.omeka.net/items/show/26659.

Output Formats