Gas transmission pipeline failure probability estimation and defect repairs activities based on in-line inspection data
AbstractDegradation of an underground pipeline during its service life leads to reduction of the pipe wall thickness. Periodic in-line inspections are performed by onshore pipelines operators to detect corrosion anomalies and size their depth and width. In the paper, a simple analytical method of burst pressure calculation for a straight pipeline repaired with a composite sleeve was investigated. Repair activities after an in-line inspection of a gas transmission pipeline were considered in this research to assess the pressure of a pipe with a flaw reinforced with a different number of layers of a fiber-based polymer sleeve. Det Norske Veritas criteria and formulation of a limit state function were applied to determine the burst pressure and corresponding failure probability of a pipeline with a large number of single and non-interacting part-wall defects. The Monte Carlo method was selected for estimation of pipeline failure probability and cumulative failure probability due to the external corrosion considering fluid pressure fluctuations in dynamic flow effects with respect to statistical distribution of input parameters were examined in this research. The proposed novel 3-step approach was validated on the real data collected from an onshore high pressure gas pipeline DN 700, MOP 5.5 MPa provided by two magnetic flux leakage inspections repeated at an interval of twelve years. A probabilistic methodology was applied to evaluate the part-wall external corrosion defects and their deterministic linear growth with time and repair activities on gas transmission pipelines were analyzed. The results of this study shall help maintenance engineers solve the problems of an optimal strategy in reliability-based high pressure gas pipelines management.
|Journal series||Engineering Failure Analysis, ISSN 1350-6307|
|Publication size in sheets||0.85|
|Score|| = 30.0, 28-11-2017, ArticleFromJournal|
= 35.0, 28-11-2017, ArticleFromJournal
|Publication indicators||: 2016 = 1.676 (2) - 2016=1.748 (5)|
|Citation count*||3 (2018-02-20)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.