Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103235
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Title: A review of failure prediction models for oil and gas pipelines
Authors: Zakikhani, K
Nasiri, F
Zayed, T 
Issue Date: Feb-2020
Source: Journal of pipeline systems engineering and practice, Feb. 2020, v. 11, no. 1, 03119001, p. 1-12
Abstract: Over 10,000 failures have occurred in US oil and gas pipelines in the past 15 years, highlighting the significance of safety measures for such facilities. Various models have been proposed by researchers to predict different failure parameters. Despite such efforts, no comprehensive review has yet been conducted in this domain. The objective of this study is to provide a detailed review of the methodologies proposed to predict failure parameters for oil and gas pipelines. Such a review gathers, organizes, classifies, and analyzes previous contributions in this domain and highlights the gaps associated with different failure prediction models. In addition, the current code-based methodologies for predicting the failure of oil and gas pipelines and their corresponding limitations are discussed. As such, this study provides pipeline operators and researchers with a comprehensive overview of the research and practices in oil and gas pipeline failure and safety. In conclusion, several avenues for future research are discussed. In particular, a maintenance planning procedure directed by pipeline availability analysis is proposed to address the existing gaps and limitations.
Keywords: Asset management
Cause
Condition assessment
Failure prediction
Inspection
Oil and gas
Pipelines
Probability
Reliability
Risk
Publisher: American Society of Civil Engineers
Journal: Journal of pipeline systems engineering and practice 
ISSN: 1949-1190
EISSN: 1949-1204
DOI: 10.1061/(ASCE)PS.1949-1204.0000407
Rights: © 2019 American Society of Civil Engineers.
This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://doi.org/10.1061/(ASCE)PS.1949-1204.0000407.
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