Prediction of pipeline failure probability with multiple failure modes and variable correlation

doi:10.16265/j.cnki.issn1003-3033.2024.05.1216

Abstract

Abstract:

Aiming at the problem of competing multiple failure modes and dependent variables of corroded pipelines, and low efficiency of predicting the probability of small failures, a time-varying failure probability prediction method for corrosive pipelines based on SS method is proposed. Based on the limit state function of leakage and burst failure, considering the competition between leakage and burst failure, a prediction model for the pipeline competitive failure probability was constructed. In order to solve the above model, the Nataf transformation method was used to describe the correlation between the depth and length of the defects in the simulated samples, and a method to solve the failure probability of corroded pipelines was proposed by considering the competitiveness of failure modes and the correlation of variables. Monte Carlo Simulation (MCS) was used to verify the above method. Finally, the above method was applied to investigate the effect of the weak correlation (correlation coefficient 0-0.3) between defect depth and length on the probability of failure within 15 years of pipeline service. The results show that when the failure probability is greater than 10^-6, the calculation results of this method are basically consistent with those of MCS, and the calculation efficiency is higher than that of MCS, and the minimal probability events with the probability level of 10^-12 can be predicted. Within 15 years of pipeline service, the greater the correlation coefficient of defect variables is, the greater the probability of pipeline burst failure is, and the earlier it reaches the threshold year of burst failure probability. As the correlation coefficient increases, the smaller the probability of leakage failure is, and the later it reaches the threshold year of leakage failure probability. At the later stage of the prediction, the effect of the correlation coefficient increase on the probability of the two kinds of failures is weakened.

Key words: failure mode, variable related, failure probability, corrosive pipelines, subset simulation (SS), Nataf transformation

CLC Number:

X944.4

LI Changjun, ZENG Jianghao, YANG Fan. Prediction of pipeline failure probability with multiple failure modes and variable correlation[J]. China Safety Science Journal, 2024, 34(5): 36-43.

Figures/Tables 7

Table 1

Fig.1

Fig.2

Fig.3

Table 2

Fig.4

Fig.5

References 25

[1]	黄维和, 郑洪龙, 李明菲. 中国油气储运行业发展历程及展望[J]. 油气储运, 2019, 38(1):1-11.
	HUANG Weihe, ZHENG Honglong, LI Mingfei. Development history and outlook of China's oil and gas storage and transportation industry[J]. Oil and Gas Storage and Transportation, 2019, 38(1):1-11.
[2]	张新生, 蔡宝泉. 基于改进随机森林模型的海底管道腐蚀预测[J]. 中国安全科学学报, 2021, 31(8):69-74. doi: 10.16265/j.cnki.issn1003-3033.2021.08.010
	ZHANG Xinsheng, CAI Baoquan. Corrosion prediction of submarine pipelines based on improved random forest model[J]. China Safety Science Journal, 2021, 31(8):69-74. doi: 10.16265/j.cnki.issn1003-3033.2021.08.010
[3]	屈静, 张建彬, 李旭芳, 等. 基于贝叶斯网络的输油管道泄漏事故情景推演[J]. 中国安全科学学报, 2021, 31(1):192-198. doi: 10.16265/j.cnki.issn1003-3033.2021.01.028
	QU Jing, ZHANG Jianbin, LI Xufang, et al. Deduction of leakage accident scenarios of oil pipelines based on Bayesian network[J]. China Safety Science Journal, 2021, 31(1):192-198. doi: 10.16265/j.cnki.issn1003-3033.2021.01.028
[4]	CHAKRABORTY S, TESFAMARIAM S. Subset simulation based approach for space-time-dependent system reliability analysis of corroding pipelines[J]. Structural Safety, 2021, 90: DOI: 10.1016/j.strusafe.2020.102073.
[5]	ZHOU Weixing. Reliability evaluation of corroding pipelines considering multiple failure modes and time-dependent internal pressure[J]. Journal of Infrastructure Systems, 2011, 17(4):216-224.
[6]	GONG Changqing, ZHOU Weixing. Importance sampling-based system reliability analysis of corroding pipelines considering multiple failure modes[J]. Reliability Engineering & System Safety, 2018, 169:199-208.
[7]	李宏仲, 孔振宇. 考虑管道多种失效模式及结构参数相关性的电-气互联系统可靠性评估[J]. 中国电机工程学报, 2024, 44(3):948-960.
	LI Hongzhong, KONG Zhenyu. Reliability assessment of electric-gas interconnection system considering multiple failure modes of pipelines and structural parameter correlation[J]. Chinese Journal of Electrical Engineering, 2024, 44(3):948-960.
[8]	张杰, 薛一菡, 丁奕, 等. 考虑腐蚀缺陷的管道内检测周期优化方法[J]. 石油机械, 2020, 48(5):107-113.
	ZHANG Jie, XUE Yihan, DING Yi, et al. Optimization method of pipeline inspection period considering corrosion defects[J]. China Petroleum Machinery, 2020, 48(5):107-113.
[9]	张鹏, 彭杨. 考虑随机变量相关性的腐蚀管道失效概率[J]. 石油学报, 2016, 37(10):1293-1301. doi: 10.7623/syxb201610010
	ZHANG Peng, PENG Yang. Probability of failure of corroded pipelines considering correlation of random variables[J]. Journal of Petroleum, 2016, 37(10):1293-1301.
[10]	KEITH M. Statistical Power analysis for the behavioral sciences[J]. Technometrics, 1989, 31(4):499-500.
[11]	LI Changjun, YANG Fan, JIA Wenlong, et al. Pipelines reliability assessment considering corrosion-related failure modes and probability distributions characteristic using subset simulation[J]. Process Safety and Environmental Protection, 2023, 178:226-239.
[12]	孙春梅, 李琴, 黄志强, 等. 基于Monte Carlo方法的腐蚀管道可靠性分析[J]. 油气储运, 2015, 34(8):811-816.
	SUN Chunmei, LI Qin, HUANG Zhiqiang, et al. Reliability analysis of corroded pipelines based on Monte Carlo method[J]. Oil and Gas Storage and Transportation, 2015, 34(8):811-816.
[13]	SONG Shufang, LU Zhenzhou, QIAO Hongwei. Subset simulation for structural reliability sensitivity analysis[J]. Reliability Engineering & System Safety, 2009, 94(2):658-665.
[14]	YU Weichao, HUANG Weihe, WEN Kai, et al. Subset simulation based reliability analysis of the corroding natural gas pipeline[J]. Reliability Engineering & System Safety, 2021, 213: DOI: 10.1016/j.ress.2021.107661.
[15]	GOMES W, BECK A. Optimal inspection and design of onshore pipelines under external corrosion process[J]. Structural Safety, 2014, 47(1):48-58.
[16]	ZHOU Weixin. Sensitivity of system reliability of corroding pipelines to modeling of stochastic growth of corrosion defects[J]. Reliability Engineering & System Safety, 2017, 167:28-38.
[17]	VAN N J M. A survey of the application of gamma processes in maintenance[J]. Reliability Engineering & System Safety, 2009, 94(1):2-21.
[18]	DANN M R, MAES M A. Stochastic corrosion growth modeling for pipelines using mass inspection data[J]. Reliability Engineering & System Safety, 2018, 180:45-54.
[19]	VALOR A, CALEYO F, HALLEN J M, et al. Reliability assessment of buried pipelines based on different corrosion rate models[J]. Corrosion Science, 2013, 66:78-87.
[20]	ZHANG Shenwei, ZHOU Wenxing. Cost-based optimal maintenance decisions for corroding natural gas pipelines based on stochastic degradation models[J]. Engineering Structures, 2014, 74:74-85.
[21]	PESINIS K, TEE K F. Statistical model and structural reliability analysis for onshore gas transmission pipelines[J]. Engineering Failure Analysis, 2017, 82:1-15.
[22]	AU S K, BECK J L. Estimation of small failure probabilities in high dimensions by subset simulation[J]. Probabilistic Engineering Mechanics, 2001, 16(4):263-277.
[23]	DER K A, LIU Peiling. Structural reliability under incomplete probability information[J]. Journal of Engineering Mechanics, 1986, 112(1):85-104.
[24]	周金宇, 谢里阳, 韩文钦, 等. 基于Nataf变换的载荷相关系统风险预测方法[J]. 机械工程学报, 2009, 45(8):137-141.
	ZHOU Jinyu, XIE Liyang, HAN Wenqin, et al. Method for system risk prediction with load dependencybased on Nataf transformation[J]. Journal of Mechanical Engineering, 2009, 45(8):137-141.
[25]	AU S K, CHING J, BECK J. Application of subset simulation methods to reliability benchmark problems[J]. Structural Safety, 2007, 29(3):183-193.

变量及单位	分布形式	均值	标准差
管道直径/mm	正态分布	630	5.4
管壁厚度/mm	正态分布	8	0.4
操作压力/MPa	耿布尔分布	8	0.49
屈服强度/MPa	正态分布	345.00	10.40
腐蚀深度/mm	对数正态分布	0.24	0.175
腐蚀长度/mm	对数正态分布	15.99	8.67
腐蚀深度增长速率/ (mm·a^-1)	伽马分布	0.40	0.13
腐蚀长度增长速率/ (mm·a^-1)	对数分布	2.74	1.53