{"title":"利用岩石性质估算LCPC耐磨系数的相关性","authors":"M. Ansari, M. Hosseini, A. Beydokhti","doi":"10.22044/JME.2020.9520.1863","DOIUrl":null,"url":null,"abstract":"Rock abrasivity, as one of the most important parameters affecting the rock drillability, significantly influences the drilling rate in mines. Therefore, rock abrasivity should be carefully evaluated prior to selecting and employing drilling machines. Since the tests for a rock abrasivity assessment require sophisticated laboratory equipment, empirical models can be used to predict rock abrasivity. Several indices based on five known methods have been introduced for assessing rock abrasivity including rock abrasivity index (RAI), Cerchar abrasivity index (CAI), Schimazek’s abrasivity factor (F-abrasivity), bit wear index (BWI), and LCPC abrasivity coefficient (LAC). In this work, 12 rock types with different origins were investigated using the uniaxial compressive strength (UCS), Brazilian test for tensile strength, and longitudinal wave velocity and LCPC tests, and microscopic observations were made to obtain a correlation for estimating the LCPC abrasivity coefficient by conducting the conventional rock mechanics tests. Using the equivalent quartz content, velocity of longitudinal waves, and rock brittleness index, a linear correlation was obtained with a coefficient of determination (R2) of 93.3% using SPSS in order to estimate LAC.","PeriodicalId":45259,"journal":{"name":"Journal of Mining and Environment","volume":"11 1","pages":"799-808"},"PeriodicalIF":1.1000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Correlation for Estimating LCPC Abrasivity Coefficient using Rock Properties\",\"authors\":\"M. Ansari, M. Hosseini, A. Beydokhti\",\"doi\":\"10.22044/JME.2020.9520.1863\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Rock abrasivity, as one of the most important parameters affecting the rock drillability, significantly influences the drilling rate in mines. Therefore, rock abrasivity should be carefully evaluated prior to selecting and employing drilling machines. Since the tests for a rock abrasivity assessment require sophisticated laboratory equipment, empirical models can be used to predict rock abrasivity. Several indices based on five known methods have been introduced for assessing rock abrasivity including rock abrasivity index (RAI), Cerchar abrasivity index (CAI), Schimazek’s abrasivity factor (F-abrasivity), bit wear index (BWI), and LCPC abrasivity coefficient (LAC). In this work, 12 rock types with different origins were investigated using the uniaxial compressive strength (UCS), Brazilian test for tensile strength, and longitudinal wave velocity and LCPC tests, and microscopic observations were made to obtain a correlation for estimating the LCPC abrasivity coefficient by conducting the conventional rock mechanics tests. Using the equivalent quartz content, velocity of longitudinal waves, and rock brittleness index, a linear correlation was obtained with a coefficient of determination (R2) of 93.3% using SPSS in order to estimate LAC.\",\"PeriodicalId\":45259,\"journal\":{\"name\":\"Journal of Mining and Environment\",\"volume\":\"11 1\",\"pages\":\"799-808\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Mining and Environment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22044/JME.2020.9520.1863\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MINING & MINERAL PROCESSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mining and Environment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22044/JME.2020.9520.1863","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MINING & MINERAL PROCESSING","Score":null,"Total":0}
A Correlation for Estimating LCPC Abrasivity Coefficient using Rock Properties
Rock abrasivity, as one of the most important parameters affecting the rock drillability, significantly influences the drilling rate in mines. Therefore, rock abrasivity should be carefully evaluated prior to selecting and employing drilling machines. Since the tests for a rock abrasivity assessment require sophisticated laboratory equipment, empirical models can be used to predict rock abrasivity. Several indices based on five known methods have been introduced for assessing rock abrasivity including rock abrasivity index (RAI), Cerchar abrasivity index (CAI), Schimazek’s abrasivity factor (F-abrasivity), bit wear index (BWI), and LCPC abrasivity coefficient (LAC). In this work, 12 rock types with different origins were investigated using the uniaxial compressive strength (UCS), Brazilian test for tensile strength, and longitudinal wave velocity and LCPC tests, and microscopic observations were made to obtain a correlation for estimating the LCPC abrasivity coefficient by conducting the conventional rock mechanics tests. Using the equivalent quartz content, velocity of longitudinal waves, and rock brittleness index, a linear correlation was obtained with a coefficient of determination (R2) of 93.3% using SPSS in order to estimate LAC.