{"title":"应用模糊逻辑-可能性方法分析油气平台管道及设备主要腐蚀损伤机理","authors":"Giraldes Luis Nathan Leal, Haddad Assed Naked","doi":"10.11648/J.IJSQA.20190501.13","DOIUrl":null,"url":null,"abstract":"Industrial accidents in recent years, particularly in the 1980s, have contributed significantly to the attention of government authorities, industry and society as a whole, in order to seek mechanisms to prevent such episodes that compromise safety of people and the quality of the environment. Currently one of the most discussed topics in various industries is process safety. Not all hazards and risks are the same or can have the same consequences. Process hazards and risks can cause major accidents, involving the release of potentially hazardous materials, fires, and explosions, or both. Accident studies have shown that equipment malfunctions are one of the major causes of unexpected and undesirable events, and so the inspection has been a technique to examine the actual condition of equipment exposed to corrosion damage mechanisms. One of the outputs from the inspection process is the observation of which damage mechanism is acting more intensely on the equipment or the piping. Having this information can help in forecasting the corrosion rates, which consequently assists in the design of a better inspection and maintenance plan. This work presents a methodology based on the Fuzzy logic, to analyze which are the corrosion damages mechanisms that contribute most to the deterioration of the equipment and pipes in an oil platform.","PeriodicalId":377638,"journal":{"name":"International Journal of Science and Qualitative Analysis","volume":"427 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Fuzzy Logic-Possibilistic Methodology to Analyze the Main Corrosion Damages Mechanisms in Pipes and Equipment Installed in an Oil and Gas Platform\",\"authors\":\"Giraldes Luis Nathan Leal, Haddad Assed Naked\",\"doi\":\"10.11648/J.IJSQA.20190501.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Industrial accidents in recent years, particularly in the 1980s, have contributed significantly to the attention of government authorities, industry and society as a whole, in order to seek mechanisms to prevent such episodes that compromise safety of people and the quality of the environment. Currently one of the most discussed topics in various industries is process safety. Not all hazards and risks are the same or can have the same consequences. Process hazards and risks can cause major accidents, involving the release of potentially hazardous materials, fires, and explosions, or both. Accident studies have shown that equipment malfunctions are one of the major causes of unexpected and undesirable events, and so the inspection has been a technique to examine the actual condition of equipment exposed to corrosion damage mechanisms. One of the outputs from the inspection process is the observation of which damage mechanism is acting more intensely on the equipment or the piping. Having this information can help in forecasting the corrosion rates, which consequently assists in the design of a better inspection and maintenance plan. This work presents a methodology based on the Fuzzy logic, to analyze which are the corrosion damages mechanisms that contribute most to the deterioration of the equipment and pipes in an oil platform.\",\"PeriodicalId\":377638,\"journal\":{\"name\":\"International Journal of Science and Qualitative Analysis\",\"volume\":\"427 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Science and Qualitative Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11648/J.IJSQA.20190501.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Science and Qualitative Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/J.IJSQA.20190501.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Fuzzy Logic-Possibilistic Methodology to Analyze the Main Corrosion Damages Mechanisms in Pipes and Equipment Installed in an Oil and Gas Platform
Industrial accidents in recent years, particularly in the 1980s, have contributed significantly to the attention of government authorities, industry and society as a whole, in order to seek mechanisms to prevent such episodes that compromise safety of people and the quality of the environment. Currently one of the most discussed topics in various industries is process safety. Not all hazards and risks are the same or can have the same consequences. Process hazards and risks can cause major accidents, involving the release of potentially hazardous materials, fires, and explosions, or both. Accident studies have shown that equipment malfunctions are one of the major causes of unexpected and undesirable events, and so the inspection has been a technique to examine the actual condition of equipment exposed to corrosion damage mechanisms. One of the outputs from the inspection process is the observation of which damage mechanism is acting more intensely on the equipment or the piping. Having this information can help in forecasting the corrosion rates, which consequently assists in the design of a better inspection and maintenance plan. This work presents a methodology based on the Fuzzy logic, to analyze which are the corrosion damages mechanisms that contribute most to the deterioration of the equipment and pipes in an oil platform.