| 摘要 |
tOver the past several decades, the high frequency of oil pipeline accidents has drawn substantial attention around the world. Many oil pipeline accident analysis models have been established based on theevent tree method, the Bayesian network method and Computational Fluid Dynamics (CFD) simulationmodels. Considering the disadvantages of current models for comprehensively representing the incidentevolution process and quantitative analysis for consequences, this paper proposes a probabilistic analysismodel for oil pipeline accidents that integrates three methods the event tree (E), the incident evolutiondiagram (E) and the Bayesian network (B). Therefore, the model is called the “EEB model”. The EEB modelcan identify the initial event and secondary events, illustrate the accident evolution path, identify the keyinfluencing factors, analyze their effects, and calculate the probabilities of different consequences of oilpipeline network accidents. Compared with other models, the EEB model considers more factors, suchas key environmental conditions and the emergency response. Probabilistic analysis of different conse-quences, including casualties, economic losses, environmental pollution and the influence on social order,can be obtained. For a general scenario of an oil pipeline network accident, the probabilities for different consequences are 71.3% for “less than 5 persons affected”, 68.2% for “less than 10 million RMB lost”, 50.4%for “less than 1 km2of water pollution” and 59.5% for “influence on social order of less than 100 persons”.The risk for the accident can be estimated by assuming the probability of the initial event as P. The modelalso denotes the emergency targets to be achieved and the response missions to be executed. Based onthis information, a response plan can be developed for decision making. Since the incident evolution pro-cess is complex, the effects of the influencing factors should be analyzed. The EEB model highlights thesignificant influences of the water area (e.g., the probability of “10–50 km2of water pollution” decreasesfrom 38.7% for “near and large” water bodies to 17.4% for “far and small” water bodies) and the emer-gency response (e.g., the probability of “50–100 million RMB economic loss” increases from 11.5% foran “effective” response to 29.3% for a “poor” response). The probabilistic analysis obtained by the EEB ismore comprehensive than those of other models, and the results can be used for risk analysis, decisionmaking and effect analysis of oil pipeline networks. |