Subset simulation-based reliability analysis of the corroding natural gas pipeline

Abstract In this study, a subset simulation-based methodology is developed to evaluate the time-dependent reliability of the corroding pipeline with multiple correlated corrosion defects. Two competing failure modes, namely small leak and burst, are considered in the methodology. Firstly, the time-dependent structural reliability model of the two competing failure modes is established. Then, the computational framework for implementing subset simulation for failure probability estimation of the individual corrosion defect is presented. Thereafter, a procedure to calculate the system reliability of the entire pipeline with correlated corrosion defects is proposed. Moreover, a numerical example based on a real natural gas pipeline is proposed, and the time-dependent failure probabilities of both the small leak and burst are predicted, which are compared with the evaluation results produced by the direct Monte Carlo simulation and Kriging method. By means of numerical example, the accuracy and efficiency of our methodology are demonstrated. Furthermore, a sensitivity analysis is performed to investigated the effect of the correlation of the corrosion defects on the system reliability, and the results indicate that the correlation exert great impact on system reliability.

[1]  Wenxing Zhou,et al.  System reliability of corroding pipelines considering stochastic process-based models for defect growth and internal pressure , 2013 .

[2]  Jie Zhang,et al.  Gas supply reliability analysis of a natural gas pipeline system considering the effects of underground gas storages , 2019, Applied Energy.

[3]  Jieyun Chen,et al.  Corrosion failure probability analysis of buried gas pipelines based on subset simulation , 2019, Journal of Loss Prevention in the Process Industries.

[4]  David Kennedy,et al.  Reliability analysis of subsea pipelines under spatially varying ground motions by using subset simulation , 2018, Reliab. Eng. Syst. Saf..

[5]  Hong-Shuang Li,et al.  Matlab codes of Subset Simulation for reliability analysis and structural optimization , 2016, Structural and Multidisciplinary Optimization.

[6]  Theodoro A. Netto,et al.  Pipeline Remaining Life Estimation Based on Concepts of Structural Reliability and Bayesian Inference , 2014 .

[7]  Wenxing Zhou,et al.  Reliability Evaluation of Corroding Pipelines Considering Multiple Failure Modes and Time-Dependent Internal Pressure , 2011 .

[8]  Curtis Smith,et al.  Bayesian Inference for Probabilistic Risk Assessment , 2011 .

[9]  Wenxing Zhou,et al.  Improvement of equivalent component approach for reliability analyses of series systems , 2017 .

[10]  Wei Dong Chen,et al.  A hybrid Kriging-based reliability method for small failure probabilities , 2019, Reliab. Eng. Syst. Saf..

[11]  Carlos Soares,et al.  Uncertainty quantification of burst pressure models of corroded pipelines , 2020 .

[12]  M. Witek.  Life cycle estimation of high pressure pipeline based on in-line inspection data , 2019, Engineering Failure Analysis.

[13]  M. Witek,et al.  An integrated risk assessment of onshore gas transmission pipelines based on defect population , 2018, Engineering Structures.

[14]  J. Beck,et al.  Estimation of Small Failure Probabilities in High Dimensions by Subset Simulation , 2001 .

[15]  C. Guedes Soares,et al.  Reliability of pipelines with corrosion defects , 2008 .

[16]  Siu-Kui Au,et al.  Application of subset simulation methods to reliability benchmark problems , 2007 .

[17]  Markus R. Dann,et al.  Stochastic corrosion growth modeling for pipelines using mass inspection data , 2018, Reliab. Eng. Syst. Saf..

[18]  W. Xiang,et al.  Sensitivity of system reliability of corroding pipelines to modeling of stochastic growth of corrosion defects , 2017, Reliab. Eng. Syst. Saf..

[19]  Jing Gong,et al.  Gas supply reliability assessment of natural gas transmission pipeline systems , 2018, Energy.

[20]  Enrico Zio,et al.  Subset Simulation of a reliability model for radioactive waste repository performance assessment , 2012, Reliab. Eng. Syst. Saf..

[21]  Kong Fah Tee,et al.  Bayesian analysis of small probability incidents for corroding energy pipelines , 2018, Engineering Structures.

[22]  Nicolas Gayton,et al.  AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation , 2011 .

[23]  Maciej Witek,et al.  Validation of in-line inspection data quality and impact on steel pipeline diagnostic intervals , 2018, Journal of Natural Gas Science and Engineering.

[24]  Jie Yuan,et al.  Probabilistic dynamics of mistuned bladed disc systems using subset simulation , 2015 .

[25]  Jing Gong,et al.  A methodology to quantify the gas supply capacity of natural gas transmission pipeline system using reliability theory , 2018, Reliab. Eng. Syst. Saf..

[26]  Dong Yuhua,et al.  Estimation of failure probability of oil and gas transmission pipelines by fuzzy fault tree analysis , 2005 .

[27]  Curtis L. Smith,et al.  Bayesian Inference for Probabilistic Risk Assessment: A Practitioner's Guidebook , 2011 .

[28]  Won Bo Lee,et al.  Comprehensive framework for underground pipeline management with reliability and cost factors using Monte Carlo simulation , 2020 .

[29]  Junho Song,et al.  Evaluation of multivariate normal integrals for general systems by sequential compounding , 2010 .

[30]  Zhenzhou Lu,et al.  Subset simulation for structural reliability sensitivity analysis , 2009, Reliab. Eng. Syst. Saf..

[31]  Wenxing Zhou,et al.  Statistical analyses of incidents on onshore gas transmission pipelines based on PHMSA database , 2016 .

[32]  Kong Fah Tee,et al.  Risk-Cost Optimization of Buried Pipelines Using Subset Simulation , 2016 .

[33]  Wenxing Zhou,et al.  System reliability of corroding pipelines , 2010 .

[34]  Jie Zhang,et al.  A novel methodology to update the reliability of the corroding natural gas pipeline by introducing the effects of failure data and corrective maintenance , 2019, International Journal of Pressure Vessels and Piping.

[35]  Wang Jian,et al.  Two accuracy measures of the Kriging model for structural reliability analysis , 2017 .

[36]  Jian-Hua Li,et al.  Predicting corrosion remaining life of underground pipelines with a mechanically-based probabilistic model , 2009 .

[37]  J. L. Alamilla,et al.  Probabilistic modelling of a corroded pressurized pipeline at inspection time , 2009 .

[38]  André T. Beck,et al.  Optimal inspection and design of onshore pipelines under external corrosion process , 2014 .

[39]  Changqing Gong,et al.  Importance sampling-based system reliability analysis of corroding pipelines considering multiple failure modes , 2018, Reliab. Eng. Syst. Saf..

[40]  Carlos Guedes Soares,et al.  Adaptive surrogate model with active refinement combining Kriging and a trust region method , 2017, Reliab. Eng. Syst. Saf..

[41]  Kong Fah Tee,et al.  Application of subset simulation in reliability estimation of underground pipelines , 2014, Reliab. Eng. Syst. Saf..

[42]  Wenyuan Li,et al.  Extracting rare failure events in composite system reliability evaluation via subset simulation , 2015, 2015 IEEE Power & Energy Society General Meeting.

[43]  Kong Fah Tee,et al.  Statistical model and structural reliability analysis for onshore gas transmission pipelines , 2017 .

[44]  John Dalsgaard Sørensen,et al.  Stochastic dynamic stiffness of a surface footing for offshore wind turbines: Implementing a subset simulation method to estimate rare events , 2014 .

[45]  Changqing Gong,et al.  First-order reliability method-based system reliability analyses of corroding pipelines considering multiple defects and failure modes , 2017 .