New Modification Method for Safety Factor of ASME Considering Pipeline Big Data
Title
New Modification Method for Safety Factor of ASME Considering Pipeline Big Data
Subject
Risk assessment
Pipeline corrosion
Big data
Petroleum pipelines
Safety factor
Analytic hierarchy process
Description
Due to the potential severity of oil and gas pipeline accidents, the accurate assessment of defective pipelines is a critical focus in petroleum engineering. Some parameters in the assessment standards are, however, limited in their technologies. This essay provides a new modification method for the safety factor (SF) of the widely accepted ASME Manual for Determining the Remaining Strength of Corroded Pipelines (B31G-2012). In the provided method, the SF is modified considering critical factors based on pipeline big data, using two big data analysis techniques, namely, correlation analysis and the analytic hierarchy process (AHP), to improve the previous one in which only the pressure of the pipeline was used during calculation. In this paper, data from an in-service pipeline is manipulated as a case to show how the modified SF is calculated. Comparative analysis with the previous results provides clear evidence that the new results are more accurate and that the SF changes according to different risk levels. 2020 American Society of Civil Engineers.
3
11
Creator
Zhang, Hewei
Ling, Jiatong
Dong, Shaohua
Zhang, Laibin
Feng, Shulu
Publisher
Journal of Pipeline Systems Engineering and Practice
Date
2020
Type
journalArticle
Identifier
19491190
10.1061/(ASCE)PS.1949-1204.0000453
Citation
Zhang, Hewei et al., “New Modification Method for Safety Factor of ASME Considering Pipeline Big Data,” Lamar University Midstream Center Research, accessed May 4, 2024, https://lumc.omeka.net/items/show/29398.