کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4980687 | 1453329 | 2017 | 36 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Study on corrosion reliability of oil/gas pipelines based on enhanced Hamacher Operator and Bayesian Assessment
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
بهداشت و امنیت شیمی
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چکیده انگلیسی
Using integration of Bayesian Assessment with Hamacher Operator, corrosion reliability of oil & gas pipelines is thoroughly studied in this paper. With the Fussell-Vesely method, 106 minimal cut sets (MCS) of the fault tree are worked out. Based on attributes & correlation levels of events, the middle events and key bottom events are divided into three categories. For the basic events affiliated to the combined events with “Strong” correlation, correction factor is set, meanwhile taking amplification/reduction factor into account. The failure probability of each basic event is calculated using Hamacher Operator considering correlation. Based on Boolean Algorithms, disjoint calculation is adopted, whereby the first and second order of reliability of the corrosion system are obtained. Respectively, adopting Beta Distribution Function (Pass-Fail Type) and Negative Log-gamma Distribution Function (Exponential Type) to fit the first & second order of system reliability, finally the first lower approximate limit and the second lower approximate limit are obtained. Integrating corrosion reliability study with failure correlation, this paper establishes a more solid & precise basis for quantitative risk assessment on oil & gas systems. With a specific case study, the model established in this paper is verified, and the confidence interval proves to be [95%, 100%].
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Process Safety and Environmental Protection - Volume 111, October 2017, Pages 569-581
Journal: Process Safety and Environmental Protection - Volume 111, October 2017, Pages 569-581
نویسندگان
Xingyu Peng, Dongchi Yao, Guangchuan Liang, Lin Qin, Jiansheng Yu, Sha He,