A leakage risk assessment method for hazardous liquid pipeline based on Markov chain Monte Carlo

Zhengbing Li, Huixia Feng, Yongtu Liang, Ning Xu, Siming Nie and Haoran Zhang

International Journal of Critical Infrastructure Protection, 2019, vol. 27, issue C

Abstract: Pipeline is now a commonly-used transportation mode for hazardous liquid, whereas followed by frequent pipeline leakage accidents. Research on the leakage post-assessment of hazard liquid pipeline has received increasing attention, but the in-situ data are hard to be accurately captured, resulting in a series of uncertainties affecting the accuracy and practicality of the risk assessment. This paper puts forward a novel method, which is able to accurately achieve leakage detection, cause analysis and leakage volume forecast by avoiding deviation of in-situ data, model parameters and the uncertainties caused by method, thereby quickly assessing the impact on the surrounding environment. The Markov Chain Monte Carlo (MCMC) algorithm is employed for repeatedly sampling leakage position and coefficient, furthermore, the transient hydrothermal and the leakage risk assessment model are established for determining the leakage volume and the risk grade. The influence of real-time measurement data and the deviation of the method are taken into consideration through the frequency distribution statistics of numerous sampling data. Based on two real examples, it is verified that the risk assessment method has practical value for the in-situ analysis and emergency treatment.

Keywords: Hazardous liquid pipeline; MCMC; Real-time online risk assessment; Transient hydrothermal model; Frequency distribution statistics (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ijocip:v:27:y:2019:i:c:s1874548219301222

DOI: 10.1016/j.ijcip.2019.100325

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