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A modified method for the safety factor parameter: The use of big data to improve petroleum pipeline reliability assessment
•A modification method of the safety factor parameters in ASME B31G for pipeline.•Combination of two methods to justify the weights: MIPCA and WASPAS.•Assess pipeline safety parameter to help efficient and cost effective maintenance. Due to the potential severity of oil and gas pipeline accidents, a...
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Published in: | Reliability engineering & system safety 2020-06, Vol.198, p.106892-8, Article 106892 |
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description | •A modification method of the safety factor parameters in ASME B31G for pipeline.•Combination of two methods to justify the weights: MIPCA and WASPAS.•Assess pipeline safety parameter to help efficient and cost effective maintenance.
Due to the potential severity of oil and gas pipeline accidents, accurate assessments on the reliability and viability of pipelines in the petroleum industry is of paramount importance. Nevertheless, the safety factor (SF) parameter in some well-established assessment standards are limited in their applications. This paper proposes a modified method for the SF parameter to better assess petroleum pipeline reliability. The proposed method improves upon current methods in that the SF is derived from multiple critical factors based on pipeline big data rather than the calculation of only the pressure of the pipeline. Data from an in-service pipeline is used as a case study to demonstrate how the proposed modified SF parameter is calculated. Comparative analysis with the existing method's results provide clear evidence that the proposed modification method is more accurate as it shows how the SF parameter changes according to different regional levels. This modified method, which incorporates Correlation Analysis, Mutual Information Principal Component Analysis (MIPCA), and Weighted Aggregated Sum Product Assessment (WASPAS), is in accordance with the widely accepted American Society of Mechanical Engineers (ASME) Manual for Determining the Remaining Strength of Corroded Pipelines (B31G-2012). With that said, the effectiveness of our modified method is directly related to the factors and case-based values being used. Therefore, although generally applicable to any pipeline, any form of SF analytics must be on a case-by-case basis. |
doi_str_mv | 10.1016/j.ress.2020.106892 |
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Due to the potential severity of oil and gas pipeline accidents, accurate assessments on the reliability and viability of pipelines in the petroleum industry is of paramount importance. Nevertheless, the safety factor (SF) parameter in some well-established assessment standards are limited in their applications. This paper proposes a modified method for the SF parameter to better assess petroleum pipeline reliability. The proposed method improves upon current methods in that the SF is derived from multiple critical factors based on pipeline big data rather than the calculation of only the pressure of the pipeline. Data from an in-service pipeline is used as a case study to demonstrate how the proposed modified SF parameter is calculated. Comparative analysis with the existing method's results provide clear evidence that the proposed modification method is more accurate as it shows how the SF parameter changes according to different regional levels. This modified method, which incorporates Correlation Analysis, Mutual Information Principal Component Analysis (MIPCA), and Weighted Aggregated Sum Product Assessment (WASPAS), is in accordance with the widely accepted American Society of Mechanical Engineers (ASME) Manual for Determining the Remaining Strength of Corroded Pipelines (B31G-2012). With that said, the effectiveness of our modified method is directly related to the factors and case-based values being used. Therefore, although generally applicable to any pipeline, any form of SF analytics must be on a case-by-case basis.</description><identifier>ISSN: 0951-8320</identifier><identifier>EISSN: 1879-0836</identifier><identifier>DOI: 10.1016/j.ress.2020.106892</identifier><language>eng</language><publisher>Barking: Elsevier Ltd</publisher><subject>ASME B31G-2012 ; Big Data ; Comparative analysis ; Correlation analysis ; Gas pipelines ; Mathematical analysis ; Mechanical engineers ; Multiple criteria decision making (MCDM) ; Mutual information principal component analysis (MIPCA) ; Natural gas ; Parameter modification ; Petroleum ; Petroleum industry ; Petroleum pipelines ; Pipelines ; Principal components analysis ; Reliability analysis ; Reliability aspects ; Reliability engineering ; Safety factor ; Safety factors ; Weighted aggregated sum product assessment (WASPAS)</subject><ispartof>Reliability engineering & system safety, 2020-06, Vol.198, p.106892-8, Article 106892</ispartof><rights>2020 Elsevier Ltd</rights><rights>Copyright Elsevier BV Jun 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c328t-500b8944e1ad812a5b9998478a1200c6838ed05fcf1024368596cca79dcac2453</citedby><cites>FETCH-LOGICAL-c328t-500b8944e1ad812a5b9998478a1200c6838ed05fcf1024368596cca79dcac2453</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Zhang, Hewei</creatorcontrib><creatorcontrib>Dong, Shaohua</creatorcontrib><creatorcontrib>Ling, Jiatong</creatorcontrib><creatorcontrib>Zhang, Laibin</creatorcontrib><creatorcontrib>Cheang, Brenda</creatorcontrib><title>A modified method for the safety factor parameter: The use of big data to improve petroleum pipeline reliability assessment</title><title>Reliability engineering & system safety</title><description>•A modification method of the safety factor parameters in ASME B31G for pipeline.•Combination of two methods to justify the weights: MIPCA and WASPAS.•Assess pipeline safety parameter to help efficient and cost effective maintenance.
Due to the potential severity of oil and gas pipeline accidents, accurate assessments on the reliability and viability of pipelines in the petroleum industry is of paramount importance. Nevertheless, the safety factor (SF) parameter in some well-established assessment standards are limited in their applications. This paper proposes a modified method for the SF parameter to better assess petroleum pipeline reliability. The proposed method improves upon current methods in that the SF is derived from multiple critical factors based on pipeline big data rather than the calculation of only the pressure of the pipeline. Data from an in-service pipeline is used as a case study to demonstrate how the proposed modified SF parameter is calculated. Comparative analysis with the existing method's results provide clear evidence that the proposed modification method is more accurate as it shows how the SF parameter changes according to different regional levels. This modified method, which incorporates Correlation Analysis, Mutual Information Principal Component Analysis (MIPCA), and Weighted Aggregated Sum Product Assessment (WASPAS), is in accordance with the widely accepted American Society of Mechanical Engineers (ASME) Manual for Determining the Remaining Strength of Corroded Pipelines (B31G-2012). With that said, the effectiveness of our modified method is directly related to the factors and case-based values being used. Therefore, although generally applicable to any pipeline, any form of SF analytics must be on a case-by-case basis.</description><subject>ASME B31G-2012</subject><subject>Big Data</subject><subject>Comparative analysis</subject><subject>Correlation analysis</subject><subject>Gas pipelines</subject><subject>Mathematical analysis</subject><subject>Mechanical engineers</subject><subject>Multiple criteria decision making (MCDM)</subject><subject>Mutual information principal component analysis (MIPCA)</subject><subject>Natural gas</subject><subject>Parameter modification</subject><subject>Petroleum</subject><subject>Petroleum industry</subject><subject>Petroleum pipelines</subject><subject>Pipelines</subject><subject>Principal components analysis</subject><subject>Reliability analysis</subject><subject>Reliability aspects</subject><subject>Reliability engineering</subject><subject>Safety factor</subject><subject>Safety factors</subject><subject>Weighted aggregated sum product assessment (WASPAS)</subject><issn>0951-8320</issn><issn>1879-0836</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9UEtLAzEYDKJgffwBTwHPW5PsKxEvpfiCgpd6DmnyxabsNmuSLRT_vCnr2dPAfDPzDYPQHSVzSmjzsJsHiHHOCDsRDRfsDM0ob0VBeNmcoxkRNS14ycgluopxRwipRN3O0M8C994468DgHtLWG2x9wGkLOCoL6Yit0ikzgwoqCyA84nU-jhGwt3jjvrBRSeHkseuH4A-AB0jBdzD2eHADdG4POGRQG9e5nKdizFV72KcbdGFVF-H2D6_R58vzevlWrD5e35eLVaFLxlNRE7LhoqqAKsMpU_VGCMGrlivKCNENLzkYUlttKWFV2fBaNFqrVhitNKvq8hrdT7m53_cIMcmdH8M-v5SsalrelEK0WcUmlQ4-xgBWDsH1KhwlJfI0stzJ08jyNLKcRs6mp8kEuf_BQZBRO9hrMC6ATtJ495_9Fwskhok</recordid><startdate>202006</startdate><enddate>202006</enddate><creator>Zhang, Hewei</creator><creator>Dong, Shaohua</creator><creator>Ling, Jiatong</creator><creator>Zhang, Laibin</creator><creator>Cheang, Brenda</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TB</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>SOI</scope></search><sort><creationdate>202006</creationdate><title>A modified method for the safety factor parameter: The use of big data to improve petroleum pipeline reliability assessment</title><author>Zhang, Hewei ; Dong, Shaohua ; Ling, Jiatong ; Zhang, Laibin ; Cheang, Brenda</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c328t-500b8944e1ad812a5b9998478a1200c6838ed05fcf1024368596cca79dcac2453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>ASME B31G-2012</topic><topic>Big Data</topic><topic>Comparative analysis</topic><topic>Correlation analysis</topic><topic>Gas pipelines</topic><topic>Mathematical analysis</topic><topic>Mechanical engineers</topic><topic>Multiple criteria decision making (MCDM)</topic><topic>Mutual information principal component analysis (MIPCA)</topic><topic>Natural gas</topic><topic>Parameter modification</topic><topic>Petroleum</topic><topic>Petroleum industry</topic><topic>Petroleum pipelines</topic><topic>Pipelines</topic><topic>Principal components analysis</topic><topic>Reliability analysis</topic><topic>Reliability aspects</topic><topic>Reliability engineering</topic><topic>Safety factor</topic><topic>Safety factors</topic><topic>Weighted aggregated sum product assessment (WASPAS)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Hewei</creatorcontrib><creatorcontrib>Dong, Shaohua</creatorcontrib><creatorcontrib>Ling, Jiatong</creatorcontrib><creatorcontrib>Zhang, Laibin</creatorcontrib><creatorcontrib>Cheang, Brenda</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Environment Abstracts</collection><jtitle>Reliability engineering & system safety</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Hewei</au><au>Dong, Shaohua</au><au>Ling, Jiatong</au><au>Zhang, Laibin</au><au>Cheang, Brenda</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A modified method for the safety factor parameter: The use of big data to improve petroleum pipeline reliability assessment</atitle><jtitle>Reliability engineering & system safety</jtitle><date>2020-06</date><risdate>2020</risdate><volume>198</volume><spage>106892</spage><epage>8</epage><pages>106892-8</pages><artnum>106892</artnum><issn>0951-8320</issn><eissn>1879-0836</eissn><abstract>•A modification method of the safety factor parameters in ASME B31G for pipeline.•Combination of two methods to justify the weights: MIPCA and WASPAS.•Assess pipeline safety parameter to help efficient and cost effective maintenance.
Due to the potential severity of oil and gas pipeline accidents, accurate assessments on the reliability and viability of pipelines in the petroleum industry is of paramount importance. Nevertheless, the safety factor (SF) parameter in some well-established assessment standards are limited in their applications. This paper proposes a modified method for the SF parameter to better assess petroleum pipeline reliability. The proposed method improves upon current methods in that the SF is derived from multiple critical factors based on pipeline big data rather than the calculation of only the pressure of the pipeline. Data from an in-service pipeline is used as a case study to demonstrate how the proposed modified SF parameter is calculated. Comparative analysis with the existing method's results provide clear evidence that the proposed modification method is more accurate as it shows how the SF parameter changes according to different regional levels. This modified method, which incorporates Correlation Analysis, Mutual Information Principal Component Analysis (MIPCA), and Weighted Aggregated Sum Product Assessment (WASPAS), is in accordance with the widely accepted American Society of Mechanical Engineers (ASME) Manual for Determining the Remaining Strength of Corroded Pipelines (B31G-2012). With that said, the effectiveness of our modified method is directly related to the factors and case-based values being used. Therefore, although generally applicable to any pipeline, any form of SF analytics must be on a case-by-case basis.</abstract><cop>Barking</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.ress.2020.106892</doi><tpages>8</tpages></addata></record> |
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subjects | ASME B31G-2012 Big Data Comparative analysis Correlation analysis Gas pipelines Mathematical analysis Mechanical engineers Multiple criteria decision making (MCDM) Mutual information principal component analysis (MIPCA) Natural gas Parameter modification Petroleum Petroleum industry Petroleum pipelines Pipelines Principal components analysis Reliability analysis Reliability aspects Reliability engineering Safety factor Safety factors Weighted aggregated sum product assessment (WASPAS) |
title | A modified method for the safety factor parameter: The use of big data to improve petroleum pipeline reliability assessment |
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