Other language title :
اراﺋﻪ راﺑﻄﻪاي ﺑﺮاي ﺗﺨﻤﯿﻦ ﺿﺮﯾﺐ ﺳﺎﯾﺶ LCPC ﺑﺎ اﺳﺘﻔﺎده از ﺧﻮاص ﺳﻨﮓ
Title of article :
A Correlation for Estimating LCPC Abrasivity Coefficient using Rock Properties
Author/Authors :
Ansari, M Department of Mining Engineering - Faculty of Technical and Engineering - Imam Khomeini International University - Qazvin, Iran , Hosseini. M Department of Mining Engineering - Faculty of Technical and Engineering - Imam Khomeini International University - Qazvin, Iran , Taleb Beydokhti, A.R Department of Geology - Faculty of Science - Imam Khomeini International University - Qazvin, Iran
Pages :
10
From page :
799
To page :
808
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 (Fabrasivity), 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.
Farsi abstract :
ﺳﺎﯾﻨﺪﮔﯽ ﺑﻪ ﻋﻨﻮان ﯾﮑﯽ از ﻣﻬﻢﺗﺮﯾﻦ ﭘﺎراﻣﺘﺮﻫﺎي ﻣﺆﺛﺮ در ﻗﺎﺑﻠﯿﺖ ﺣﻔﺎري ﺳﻨﮓﻫﺎ، ﺳﺮﻋﺖ ﺣﻔﺎري در ﻣﻌﺎدن را ﺑﻪ ﺷــﺪت ﺗﺤــﺖ ﺗــﺄﺛﯿﺮ ﺧــﻮد ﻗــﺮار ﻣﯽدﻫــﺪ. ﺑﻨــﺎﺑﺮاﯾﻦ ﻻزم اﺳﺖ ﮐﻪ ﻗﺒﻞ از اﻧﺘﺨﺎب و ﺑﻪ ﮐﺎرﮔﯿﺮي ﻣﺎﺷﯿﻦ ﺣﻔﺎري، ﻣﯿﺰان ﺳﺎﯾﻨﺪﮔﯽ ﺳﻨﮓ ﺑﺮرﺳﯽ ﺷﻮد. ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ اﯾﻨﮑﻪ آزﻣﺎﯾﺶﻫﺎي ﺗﻌﯿﯿﻦ ﺳــﺎﯾﻨﺪﮔﯽ ﺳــﻨﮓ ﻧﯿﺎزﻣﻨــﺪ ﺑــﻪ اﻣﮑﺎﻧــﺎت ﭘﯿﭽﯿﺪه آزﻣﺎﯾﺸﮕﺎﻫﯽ اﺳﺖ، ﻣﯽﺗﻮان از ﻣﺪلﻫﺎي ﺗﺠﺮﺑﯽ ﺑﺮاي ﭘﯿﺶ ﺑﯿﻨﯽ آﻧﻬﺎ اﺳﺘﻔﺎده ﻧﻤﻮد. ﺗﺎ ﮐﻨﻮن ﺷﺎﺧﺺﻫــﺎﯾﯽ ﺑــﺮ اﺳــﺎس ﭘــﻨﺞ روش ﺷــﻨﺎﺧﺘﻪ ﺷــﺪه ﺑــﺮاي ارزﯾــﺎﺑﯽ ﺳﺎﯾﻨﺪﮔﯽ ﺳﻨﮓﻫﺎ اراﺋﻪ ﺷﺪه اﺳﺖ، ﮐﻪ از ﺟﻤﻠﻪ اﯾﻦ ﺷﺎﺧﺺﻫﺎ ﻣﯽﺗﻮان ﺑﻪ ﺷﺎﺧﺺ ﺳﺎﯾﻨﺪﮔﯽ ﺳﻨﮓ )RAI(، اﻧﺪﯾﺲ ﺳﺎﯾﺶ ﺳﺮﺷــﺎر )CAI(، ﻓــﺎﮐﺘﻮر ﺳــﺎﯾﺶ ﺷــﯿﻤﺎزك )F-abrasivity(، اﻧﺪﯾﺲ ﺳﺎﯾﺶ ﺳﺮﻣﺘﻪ )BWI( و ﺿﺮﯾﺐ ﺳﺎﯾﺶ LCPC اﺷﺎره ﮐﺮد. در اﯾﻦ ﺗﺤﻘﯿﻖ روي 12 ﻧﻮع ﺳﻨﮓ ﮐﻪ ﻣﻨﺸــﺄ ﻣﺘﻔــﺎوت دارﻧــﺪ، آزﻣــﻮن ﻣﻘﺎوﻣــﺖ ﺗﺮاﮐﻢ ﺗﮏ ﻣﺤﻮري، آزﻣﻮن ﺑﺮزﯾﻠﯽ، آزﻣﻮن ﺗﻌﯿﯿﻦ ﺳﺮﻋﺖ اﻣﻮاج ﻃﻮﻟﯽ و آزﻣﻮن LCPC ﺑﻪ ﻫﻤﺮاه ﻣﻄﺎﻟﻌﺎت ﻣﯿﮑﺮوﺳﮑﻮﭘﯽ اﻧﺠﺎم ﺷﺪه اﺳــﺖ ﺗــﺎ ﯾــﮏ راﺑﻄــﻪ ﺑــﺮاي ﺗﺨﻤــﯿﻦ ﺿﺮﯾﺐ ﺳﺎﯾﺶ LCPC ﺑﺎ اﺳﺘﻔﺎده از آزﻣﺎﯾﺸﺎت ﻣﺮﺳﻮم در ﻣﮑﺎﻧﯿﮏ ﺳﻨﮓ ﺑﺪﺳﺖ آﯾﺪ. در ﻧﻬﺎﯾﺖ ﺑﺎ ﻧﺮم اﻓــﺰار آﻣــﺎري SPSS و ﺑــﺎ اﺳــﺘﻔﺎده از ﭘــﺎراﻣﺘﺮﻫــﺎي ﻣﯿــﺰان ﮐــﻮارﺗﺰ ﻣﻌﺎدل، ﺳﺮﻋﺖ اﻣﻮاج ﻃﻮﻟﯽ و ﺷﺎﺧﺺ ﺷﮑﻨﻨﺪﮔﯽ ﺳﻨﮓﻫﺎ راﺑﻄﻪاي ﺧﻄﯽ ﺑﺮاي ﺗﺨﻤﯿﻦ ﺿﺮﯾﺐ ﺳﺎﯾﺶ LCPC ﺑﺎ ﺿﺮﯾﺐ ﺗﻌﯿﯿﻦ 93/3 درﺻﺪ اراﺋﻪ ﺷﺪه اﺳت
Keywords :
Statistical analysis , Abrasivity index , Rock properties , LCPC test , SPSS software
Journal title :
Journal of Mining and Environment
Serial Year :
2020
Record number :
2529759
Link To Document :
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