Predicting corrosion remaining life of underground pipelines with a mechanically-based probabilistic model

被引:107
作者
Li, Shu-Xin [1 ]
Yu, Shu-Rong [1 ]
Zeng, Hai-Long [1 ]
Li, Jian-Hua [1 ]
Liang, Rui [1 ]
机构
[1] Lanzhou Univ Technol, Sch PetroChem Engn, Lanzhou 730050, Peoples R China
关键词
pipeline; corrosion; probabilistic model; remaining life; cumulative distribution function; PITTING CORROSION; STATISTICAL CHARACTERIZATION; RELIABILITY; SUBJECT;
D O I
10.1016/j.petrol.2008.12.023
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
A methodology is presented for predicting corrosion remaining life of underground pipelines with a mechanically-based probabilistic model by taking effect of randomness into account in pipeline corrosion. Monte Carlo simulation technique is employed to calculate the remaining life and its cumulative distribution function (CDF). The sensitivity analysis is performed to identify the most important parameters that affect pipeline failure. The results show that the corrosion defect depth and radial corrosion rate are the key factors influencing pipeline failure probability and remaining life. The pipeline remaining life can be prolonged greatly by reducing mean value of corrosion defect depth and radial corrosion rate. CDF is more appropriate to characterize the pipeline failure probability compared to probability density function (PDF) and reliability index. (c) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:162 / 166
页数:5
相关论文
共 17 条
[11]   Probabilistic models for steel corrosion loss and pitting of marine infrastructure [J].
Melchers, R. E. ;
Jeffrey, R. J. .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2008, 93 (03) :423-432
[12]   The effect of corrosion on the structural reliability of steel offshore structures [J].
Melchers, RE .
CORROSION SCIENCE, 2005, 47 (10) :2391-2410
[13]   Statistical characterization of pitting corrosion - Part 1: Data analysis [J].
Melchers, RE .
CORROSION, 2005, 61 (07) :655-664
[14]   Statistical characterization of pitting corrosion - Part 2: Probabilistic modeling for maximum pit depth [J].
Melchers, RE .
CORROSION, 2005, 61 (08) :766-777
[15]   Probabilistic models for condition assessment of oil and gas pipelines [J].
Pandey, MD .
NDT & E INTERNATIONAL, 1998, 31 (05) :349-358
[16]   Probability-based safety analysis - value and drawbacks [J].
Sexsmith, RG .
STRUCTURAL SAFETY, 1999, 21 (04) :303-310
[17]   STATISTICAL MODELING OF PITTING CORROSION AND PIPELINE RELIABILITY [J].
SHEIKH, AK ;
BOAH, JK ;
HANSEN, DA .
CORROSION, 1990, 46 (03) :190-197