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Estimation of Cerchar abrasivity index of granitic rocks in Turkey by geological properties using regression analysis

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Abstract

The estimation of abrasivity on granitic rocks is very important in mechanical excavators. The mineralogical composition and physico-mechanical properties of the rock affects of abrasivity properties such as the type and size of the mineral grains and strength. Tool wear is an important parameter in hard rock tunnelling and mining applications that are highly affected by rock abrasivity. The estimation of the Cerchar abrasivity index (CAI) from geological properties is useful for excavation costs. For this purpose, CAI, chemical, petrographical, physical and mechanical tests were carried out on 12 granitic rocks taken from different regions of Turkey. The test results were analysed using the method of least squares regression. Multiple regression models having good correlation coefficients were obtained for the granitic rocks. The CAI tests were correlated with chemical compound and a weak relation was determined. The regression analysis was also repeated for petrographical, physical, and mechanical properties. Statistically meaningful correlations were determined between all geological properties and CAI. Then multiple regression analysis was applied to all geological properties to find the more significant relations. Results show that shore scleroscope hardness, water absorption, and the waveness average prove to be the best for estimating CAI of granitic rocks.

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References

  • Al-Ameen SL, Waller MD (1994) The influence of rock strength and abrasive mineral content on the CERCHAR abrasive index. Eng Geol 36:293–301

    Article  Google Scholar 

  • Alber M (2008) Stress dependency of the Cerchar abrasivity index (CAI) and its effects on wear of selected rock cutting tools. Tunn Undergr Space Technol 23:351–359

    Article  Google Scholar 

  • Alber Michael, Yaralı Olgay, Dahl Filip, Bruland Amund, Käsling Heiko, Michalakopoulos Theodore N, Cardu Marilena, Hagan Paul, Aydın Hamit, Özarslan Ahmet (2014) ISRM suggested method for determining the abrasivity of rock by the CERCHAR abrasivity test. Rock Mech Rock Eng 47:261–266

    Article  Google Scholar 

  • ASTM (2001) Standard test method for splitting tensile strength of intact rock core specimens. D3967. 95(a)

  • ASTM (2010) Standard test method for compressive strength and elastic module of intact rock core specimens under varying states of stress and temperatures D7012

  • Chambers M, Dinsmore TW (2014) Advanced analytics methodologies: driving business value with analytics. Pearson Education

  • Davis JC (1973) Statistics and data analysis in geology. Wiley, New York, p 550

  • Deliormanlı A (2011) Cerchar abrasivitiy index (CAI) and its relation to strength and abrasion test methods for marble stones. Constr Building Mat 30:16–21

    Article  Google Scholar 

  • Demirdag S, Yavuz H, Altindag R (2009) The effect of sample size on Schmidt rebound hardness value of rocks. Int J Rock Mech Min Sci 46(4):725–730

    Article  Google Scholar 

  • ISRM (2007) The Complete ISRM suggested methods for rock characterization, testing and monitoring: 1974–2006. In: Ulusay and Hudson (eds)

  • ISRM (2014) Rock characterization. testing and monitoring–ISRM suggested methods. Springer Press. Reşat Ulusay (ed). p 293

  • Johnson RB, De Graff JV (1988) Principles of engineering geology. John Wiley and Sons, NewYork , p 497

    Google Scholar 

  • Kahraman S, Alber M, Fener M, Gunaydin O (2010) The usability of Cerchar abrasivity index for the prediction of UCS and E of Misis Fault Breccia: regression and artificial neural networks analysis. Expert Syst Appl 37(2010):8750–8756

    Article  Google Scholar 

  • Kahraman S, Alber M, Fener M, Gunaydin O, Fener M (2015) The usability of Cerchar abrasivity index for the evaluation of the triaxial strength of Misis Fault Breccia. Bull Eng Geol Environ 74:163–170

    Article  Google Scholar 

  • Lassnig K, Latal C, Klima K (2008) Impact of grain size on the Cerchar abrasiveness test. Ernst and Sohn Verlag für Architektur und technische Wissenschaften GmbH and Co. KG. Berlin Geomechanik und Tunnelbau 1. Heft 1

  • Michalakopoulos TN, Anagnostou VG, Bassanou ME, Panagiotou GN (2005) The influence of steel styli hardness on the Cerchar abrasiveness index value. Inter J Rock Mech Mining Sci Geomechan Abstracts 43:321–327

    Article  Google Scholar 

  • Moradizadeh M, Ghafoori M, Lashkaripour GR, Tarigh Azali S (2013) Utilizing geological properties for predicting cerchar abrasiveness index (CAI) in sandstones. Int J Emerg Technol Advan Eng 3(9):99–109

    Google Scholar 

  • Plinninger R, Kasling H, Thuro K, Spaun G (2003) Testing conditions and geomechanical properties in influencing the CERCHAR abrasiveness index (CAI) value. J Rock Mech Mining Sci 40(2003):159–263

    Google Scholar 

  • Rostami J, Ghasemi A, Gharahbagh AE, Dogruoz C, Dahl F, Rock (2014) Study of dominant factors affecting cerchar abrasivity index. Mech Rock Eng 47:1905–1919

    Article  Google Scholar 

  • Streckeisen A (1979) To each plutonic rock its proper name: eart-Sci. Reviews 12:1–33

    Google Scholar 

  • Suana M, Peters T (1982) The CERCHAR abrasivity index and its relation to rock mineralogy and petrography. Rock Mech Rock Eng 15:1–7

    Article  Google Scholar 

  • Thuro K (1997) Prediction of drillability in hard rock tunneling by drilling and blasting, tunnels for people. pp 103–108

  • Thuro K, Singer J, Käsling H, Bauer M (2007) Determining abrasivity with the LCPC Test. In: Eberhardt E, Stead D, Morrison T (eds) Proceedings of the 1st Canada–US Rock Mechanics Symposium, 27.-31.05.2007, Taylor and Francis, Vancouver BC

  • Tumac D (2014) Predicting the performance of chain saw machines based on shore scleroscope hardness. Rock Mech Rock Eng 47(2):703–715

    Article  Google Scholar 

  • Tumac D (2015) Predicting the performance of large diameter circular saws based on schmidt hammer and other properties for some Turkish carbonate rocks. Int J Rock Mech Min Sci 75:159–168

    Google Scholar 

  • Turkish Standard EN 14157 (2005) Natural stone—determination of the abrasion resistance. Ankara. p 16

  • Yaralı O, Yaşar E, Bacak G, Ranjith PG (2008) A study of rock abrasivity and tool wear in coal measures Rocks. Int J Coal Geol 74:53–66

    Article  Google Scholar 

  • Zorlu K, Gokceoglu C, Ocakoglu F, Nefeslioglu HA, Acikalin S (2008) Prediction of uniaxial compressive strength of sandstones using petrography-based models. Eng Geol 96(3):141–158

    Article  Google Scholar 

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Correspondence to Selman Er.

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Er, S., Tuğrul, A. Estimation of Cerchar abrasivity index of granitic rocks in Turkey by geological properties using regression analysis. Bull Eng Geol Environ 75, 1325–1339 (2016). https://doi.org/10.1007/s10064-016-0853-y

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  • DOI: https://doi.org/10.1007/s10064-016-0853-y

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