收藏切换
Analysis of failure probability for in-service pipelines based on inverse Gaussian stochastic processes
收藏切换
PDF
Kaikai CHENG1, Kewei LI1, Xing WANG1, Nana SUN1, Gao LYU1, Guangyuan WENG2
China Safety Science Journal | 2026, 36(1) : 112 - 120
Less
收藏切换
China Safety Science Journal | 2026, 36(1): 112-120
Safety Technology and Engineering
Analysis of failure probability for in-service pipelines based on inverse Gaussian stochastic processes
Full
Kaikai CHENG1, Kewei LI1, Xing WANG1, Nana SUN1, Gao LYU1, Guangyuan WENG2
Affiliations
  • 1College of Pipeline Engineering, Xi′an Shiyou University, Xi′an Shaanxi 710065, China
  • 2College of Mechanical Engineering, Xi′an Shiyou University, Xi′an Shaanxi 710065, China
Published: 2026-01-28 doi: 10.16265/j.cnki.issn1003-3033.2026.01.0278
Outline
收藏切换

In-service pipelines are subject to complex stresses, and their performance degradation over time constitutes a dynamic, time-varying stochastic process. To address the challenge that traditional deterministic functions struggle to accurately capture its inherent randomness, a dynamic analysis method for failure probability of in-service pipelines based on a dual stochastic process was proposed. The degradation of pipeline performance was simulated using an inverse Gaussian stochastic process, while the variation of internal pressure loads within the pipeline was described by an equal-interval stationary binomial rectangular wave process probability model. A dual stochastic process probability model for pipeline bearing capacity and internal pressure load was then constructed. Based on statistical parameters and performance degradation data from a specific pipeline's service period, inverse Gaussian distribution was used to fit the performance degradation models at six distinct time points, enabling dynamic failure probability prediction. The results show that the pipeline's service life is predicted to be 16 and 14 years using degradation data from 2 and 4 years, respectively. When utilizing degradation data from 6, 8, and 10 years, the predicted service lives are 12, 11, and 10 years, respectively. Sensitivity analysis indicates that wall thickness, yield strength, pipe diameter, and operating pressure have the most significant impacts on the pipeline's failure probability, followed by the initial depth of defects. In contrast, the initial length of defects, depth corrosion rate, and length corrosion rate have relatively minor effects.

inverse Gaussian stochastic process  /  in-service pipeline  /  failure probability  /  service life  /  degradation data
Kaikai CHENG, Kewei LI, Xing WANG, Nana SUN, Gao LYU, Guangyuan WENG. Analysis of failure probability for in-service pipelines based on inverse Gaussian stochastic processes[J]. China Safety Science Journal, 2026 , 36 (1) : 112 -120 . DOI: 10.16265/j.cnki.issn1003-3033.2026.01.0278
Year 2026 volume 36 Issue 1
PDF
59
9
Cite this Article
BibTeX
Article Info
doi: 10.16265/j.cnki.issn1003-3033.2026.01.0278
  • Receive Date:2025-08-10
  • Online Date:2026-07-08
  • Published:2026-01-28
Article Data
Affiliations
History
  • Received:2025-08-10
  • Revised:2025-11-05
Funding
Affiliations
    1College of Pipeline Engineering, Xi′an Shiyou University, Xi′an Shaanxi 710065, China
    2College of Mechanical Engineering, Xi′an Shiyou University, Xi′an Shaanxi 710065, China
References
Share
https://castjournals.cast.org.cn/joweb/zgaqkxxb/EN/10.16265/j.cnki.issn1003-3033.2026.01.0278
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT