天然气管道不同孔径泄漏失效概率量化方法研究*

为研究不同孔径泄漏下天然气管道失效概率，首先基于EGIG数据库和UKOPA数据库天然气管道历史失效数据，计算由不同失效原因导致3种孔径泄漏所占比例；然后将我国管道各原因基础失效概率按照对应比例分别进行修正，获得较适用于我国天然气管道特点的不同孔径泄漏基础失效概率；最后分别考虑第三方破坏、腐蚀、施工缺陷/材料失效、误操作、自然力破坏5种失效原因，完成对天然气管道不同孔径泄漏基础失效概率的修正计算。研究结果表明:小孔泄漏、中孔泄漏和破裂泄漏的基础失效概率分别为0.173，0.128，0.048次/（103 km·a）；修正因子包括管径、埋深、壁厚、管龄、防腐层类型、管道所处区域，上述因子能够满足不同场景下天然气管道失效概率的修正计算；概率量化方法综合考虑失效原因、泄漏孔径以及管道本体信息，能够定量化预测天然气管道失效概率，为天然气管道定量风险评价提供数据支撑。

Research on quantitative method of failure probability of natural gas pipelines with different leakage hole diameters

In order to study the failure probability of natural gas pipelines with different leakage hole diameters,firstly,based on the historical failure data of natural gas pipelines in EGIG database and UKOPA database,the proportions of three kinds of leakage hole diameters caused by different failure causes were calculated.Then，the basic failure probabilities of each cause of the pipelines in China were modified according to the corresponding proportions,and the basic failure probabilities of different leakage hole diameters which were more suitable for the characteristics of China’s natural gas pipelines were obtained.Finally,considering five failure causes such as the third-party damage,corrosion,construction defect or material failure,incorrect operation and natural force damage respectively,the modification calculation of the basic failure probabilities under different leakage hole diameters of natural gas pipelines was completed.The results showed that the basic failure probabilities of small hole leakage,medium hole leakage and rupture leakage were 0.173,0.128 and 0.048 times/(103 km·a) respectively.The modification factors included the pipe diameter,cover depth,wall thickness,pipe age,coating type and area where the pipeline was located,which could meet the modification calculation of failure probability of natural gas pipelines under different scenarios.The probability quantification method comprehensively considered the failure causes,leakage hole diameters and pipeline body information,which could quantitatively predict the failure probability of natural gas pipelines and provide data support for the quantitative risk assessment.