{"title":"输油管内压力的不确定性及其对可靠性分析的影响","authors":"Yue Liu, Wenxing Zhou","doi":"10.1016/j.jpse.2022.100055","DOIUrl":null,"url":null,"abstract":"<div><p>This study addresses a significant knowledge gap in the reliability-based fitnessfor-service assessment of pipelines, namely the statistical information of the internal operating pressure. To this end, probabilistic characteristics of the internal pressure of an in-service oil transmission pipeline are derived based on minute-by-minute pressure records collected from the discharge and suction ends of a pump station on the pipeline. The arbitrary-point-in-time discharge and suction pressures are found to follow the Johnson SB distribution; the monthly and annual maximum discharge pressures are found to be well represented by a deterministic quantity equal to 90% of the maximum operating pressure, and the monthly and annual maximum suction pressures follow the beta distributions. The autocorrelation and power spectral density functions of the discharge and suction pressures characterized as stationary stochastic processes are also derived from the pressure records. Furthermore, the statistics of the pressure ranges obtained from the rainflow counting analysis of the pressure records are obtained. Two example pipelines are used to examine the implications of the uncertainty in the internal pressure for the reliability analysis of corroding pipelines.</p></div>","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"2 2","pages":"Article 100055"},"PeriodicalIF":4.8000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667143322000270/pdfft?md5=18423a08b84b5fcf5120f64b04bba449&pid=1-s2.0-S2667143322000270-main.pdf","citationCount":"3","resultStr":"{\"title\":\"Uncertainties in internal pressure of oil transmission pipelines and implications for the reliability analysis\",\"authors\":\"Yue Liu, Wenxing Zhou\",\"doi\":\"10.1016/j.jpse.2022.100055\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study addresses a significant knowledge gap in the reliability-based fitnessfor-service assessment of pipelines, namely the statistical information of the internal operating pressure. To this end, probabilistic characteristics of the internal pressure of an in-service oil transmission pipeline are derived based on minute-by-minute pressure records collected from the discharge and suction ends of a pump station on the pipeline. The arbitrary-point-in-time discharge and suction pressures are found to follow the Johnson SB distribution; the monthly and annual maximum discharge pressures are found to be well represented by a deterministic quantity equal to 90% of the maximum operating pressure, and the monthly and annual maximum suction pressures follow the beta distributions. The autocorrelation and power spectral density functions of the discharge and suction pressures characterized as stationary stochastic processes are also derived from the pressure records. Furthermore, the statistics of the pressure ranges obtained from the rainflow counting analysis of the pressure records are obtained. Two example pipelines are used to examine the implications of the uncertainty in the internal pressure for the reliability analysis of corroding pipelines.</p></div>\",\"PeriodicalId\":100824,\"journal\":{\"name\":\"Journal of Pipeline Science and Engineering\",\"volume\":\"2 2\",\"pages\":\"Article 100055\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2022-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2667143322000270/pdfft?md5=18423a08b84b5fcf5120f64b04bba449&pid=1-s2.0-S2667143322000270-main.pdf\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Pipeline Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667143322000270\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Pipeline Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667143322000270","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Uncertainties in internal pressure of oil transmission pipelines and implications for the reliability analysis
This study addresses a significant knowledge gap in the reliability-based fitnessfor-service assessment of pipelines, namely the statistical information of the internal operating pressure. To this end, probabilistic characteristics of the internal pressure of an in-service oil transmission pipeline are derived based on minute-by-minute pressure records collected from the discharge and suction ends of a pump station on the pipeline. The arbitrary-point-in-time discharge and suction pressures are found to follow the Johnson SB distribution; the monthly and annual maximum discharge pressures are found to be well represented by a deterministic quantity equal to 90% of the maximum operating pressure, and the monthly and annual maximum suction pressures follow the beta distributions. The autocorrelation and power spectral density functions of the discharge and suction pressures characterized as stationary stochastic processes are also derived from the pressure records. Furthermore, the statistics of the pressure ranges obtained from the rainflow counting analysis of the pressure records are obtained. Two example pipelines are used to examine the implications of the uncertainty in the internal pressure for the reliability analysis of corroding pipelines.