首页> 外文期刊>Quarterly Journal of Engineering Geology and Hydrogeology >A study to correlate LCPC rock abrasivity test results with petrographic and geomechanical rock properties
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A study to correlate LCPC rock abrasivity test results with petrographic and geomechanical rock properties

机译:将LCPC岩石磨探性试验结果与岩体和地质力学岩石特性相关联

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摘要

Rock abrasivity is very much influenced by the petrographic and physico-mechanical properties of rock and hence its assessment from common geomechanical rock properties is helpful for rock engineers in estimating excavation costs. In this paper LCPC and CERCHAR abrasivity tests, as well as a complete suite of mechanical and physical rock properties tests, were conducted on 51 rock samples collected from different locations in Pakistan. Moreover, petrographical studies of 48 rock specimens were performed along with the computation of Schimazek's F-value (F-value) and Rock Abrasivity Index (RAI). For the analysis of test results least square regression was employed. Initially the LCPC abrasivity coefficient (ABR) values were correlated with CERCHAR abrasivity index tests and reasonable relationships were observed. Statistically meaningful relationships were found between ABR and geotechnical wear indices (F-value and RAI). Possible correlations of LCPC test results with rock properties are also discussed. Finally multiple regression analysis was applied to find statistically significant correlation of ABR with petrographical and physico-mechanical rock properties. Test results show that RAI, Brazilian tensile strength and mean quartz grain size ((sic)-qtz) prove to be the statistically best predictors of ABR from the rock properties determined. The developed correlations are specifically intended for rock engineers involved in designing excavation projects.
机译:岩石磨料非常受岩石和物理机械性能的影响,因此对普通地质力学岩石属性的评估有助于岩石工程师估算挖掘成本。在本文中,在从巴基斯坦的不同地点收集的51个岩石样品上进行LCPC和CERCHAR磨料试验以及完整的机械和物理岩石性质试验。此外,对48个岩石标本的岩体研究随着史利亚兹克的F值(F值)和岩石磨料指数(RAI)的计算进行了计算。为了分析测试结果,使用最小二乘回归。最初,LCPC磨料系数(ABR)值与Cerchar磨料指数试验相关,并且观察到合理的关系。 ABR和岩土工程磨损指数(F值和RAI)之间发现了统计上有意义的关系。还讨论了LCPC测试结果与岩石属性的可能相关性。最后应用了多元回归分析,以找到ABR与岩体和物理机械岩石特性的统计上显着的相关性。测试结果表明,rai,巴西拉伸强度和平均石英粒度((siC)-qtz)被证明是来自确定的岩石特性的统计最佳预测因子。发达的相关性专门用于涉及设计挖掘项目的岩石工程师。

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