| Issue |
E3S Web Conf.
Volume 38, 2018
2018 4th International Conference on Energy Materials and Environment Engineering (ICEMEE 2018)
|
|
|---|---|---|
| Article Number | 01010 | |
| Number of page(s) | 6 | |
| Section | Environmental Science and Environmental Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/20183801010 | |
| Published online | 04 June 2018 | |
Quantitative analysis of factors that affect oil pipeline network accident based on Bayesian networks: A case study in China
1
China National Institute of Standardization, 100191 Beijing, China
2
School of Resources and Safety Engineering, China University of Mining and Technology, 100083 Beijing, China
* Corresponding author: zhangchao@cnis.gov.cn
Some factors can affect the consequences of oil pipeline accident and their effects should be analyzed to improve emergency preparation and emergency response. Although there are some qualitative analysis models of risk factors’ effects, the quantitative analysis model still should be researched. In this study, we introduce a Bayesian network (BN) model of risk factors’ effects analysis in an oil pipeline accident case that happened in China. The incident evolution diagram is built to identify the risk factors. And the BN model is built based on the deployment rule for factor nodes in BN and the expert knowledge by Dempster-Shafer evidence theory. Then the probabilities of incident consequences and risk factors’ effects can be calculated. The most likely consequences given by this model are consilient with the case. Meanwhile, the quantitative estimations of risk factors’ effects may provide a theoretical basis to take optimal risk treatment measures for oil pipeline management, which can be used in emergency preparation and emergency response.
© The Authors, published by EDP Sciences, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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