Abstract
Thorough and realistic performance predictions are among the main requisites for estimating excavation costs and time of the tunneling projects. Also, NTNU/SINTEF rock drillability indices, including the Drilling Rate Index™ (DRI), Bit Wear Index™ (BWI), and Cutter Life Index™ (CLI), are among the most effective indices for determining rock drillability. In this study, brittleness value (S20), Sievers’ J-Value (SJ), abrasion value (AV), and Abrasion Value Cutter Steel (AVS) tests are conducted to determine these indices for a wide range of Iranian hard igneous rocks. In addition, relationships between such drillability parameters with petrographic features and index properties of the tested rocks are investigated. The results from multiple regression analysis revealed that the multiple regression models prepared using petrographic features provide a better estimation of drillability compared to those prepared using index properties. Also, it was found that the semiautomatic petrography and multiple regression analyses provide a suitable complement to determine drillability properties of igneous rocks. Based on the results of this study, AV has higher correlations with studied mineralogical indices than AVS. The results imply that, in general, rock surface hardness of hard igneous rocks is very high, and the acidic igneous rocks have a lower strength and density and higher S20 than those of basic rocks. Moreover, DRI is higher, while BWI is lower in acidic igneous rocks, suggesting that drill and blast tunneling is more convenient in these rocks than basic rocks.
Similar content being viewed by others
Abbreviations
- g :
-
Index of interlocking
- t :
-
Index of grain size homogeneity
- IS:
-
Saturation Index
- IF:
-
Feldspathic Index
- IC:
-
Coloration Index
- ρ :
-
Dry density
- ϕ :
-
Porosity
- V p :
-
P-wave velocity
- R N :
-
Schmidt rebound number
- Is(50) :
-
Point load strength index
- S20 :
-
Brittleness value
- SJ:
-
Sievers’ J-Value
- AV:
-
Abrasion Value
- AVS:
-
Abrasion Value Cutter Steel
- DRI:
-
Drilling Rate Index
- BWI:
-
Bit Wear Index
- CLI:
-
Cutter Life Index
- VHNR:
-
Vickers Hardness Number Rock
- ™:
-
Trademark
References
Aligholi S, Khajavi R, Razmara M (2015) Automated mineral identification algorithm using optical properties of crystals. Comput Geosci 85:175–183
Aligholi S, Lashkaripour GR, Khajavi R, Razmara M (2017a) Automatic mineral identification using color tracking. Pattern Recognit 65:164–174
Aligholi S, Lashkaripour GR, Ghafoori M (2017b) Strength/Brittleness classification of igneous intact rocks based on basic physical and dynamic properties. Rock Mech Rock Eng 50(1):45–65
Altindag R (2010) Assessment of some brittleness indexes in rock drilling efficiency. Rock Mech Rock Eng 43:361–370
Anon (1995) The description and classification of weathered rocks for engineering purposes. Geological Society Engineering Group Working Party Report. Q J Eng Geol 28:207–242
Asmussen P, Conrad O, Günther A, Kirsch M, Riller U (2015) Semi-automatic segmentation of petrographic thin section images using a “seeded-region growing algorithm” with an application to characterize weathered subarkose sandstone. Comput Geosci 83:89–99
Aydin A (2009) ISRM Suggested method for determination of the Schmidt hammer rebound hardness: revised version. Int J Rock Mech Min Sci 46:627–634
Azimian A, Ajalloeian R, Fatehi L (2014) An empirical correlation of uniaxial compressive strength with P-wave velocity and point load strength index on marly rocks using statistical method. Geotech Geol Eng 32(1):205–214
Barla G, Pelizza S (2000) TBM tunneling in difficult ground conditions, Proceedings of GeoEng 2000. Proceedings of the International Conference on Geotechnical & Geological Engineering. Technomic Publishing Company, Lancaster, Melbourne, pp 329–354
Barton N (2000) TBM tunnelling in jointed and faulted rock. A.A. Balkema, Rotterdam. ISBN 9058093417
Blindheim OT, Grov E, Nilsen B (2002) The effect of mixed face conditions (MFC) on hard rock TBM performance. In: AITES-ITA word tunnel congress, Sydney, pp 24–32
Bruland A (1998a) Hard rock tunnel boring. PhD thesis, Department of Civil and Transport Engineering, NTNU, Trondheim, Norway
Bruland A (1998b) Prediction model for performance and costs, in Norwegian TBM Tunnelling, Publication No. 11, Norwegian Tunnelling Society
Bruland A (1998c) Hard rock tunnel boring—Vol. 1—Background and discussion. NTNU Trondheim, p 49
Bruland A (1998d) Hard rock tunnel boring: drillability—test methods. Project report 13A-98, NTNU Trondheim
Bruland A (1998e) Hard rock tunnel boring: drillability—statistics of drillability test results. Project report 13C-98, NTNU Trondheim
Dahl F (2003) DRI, BWI, CLI Standards. NTNU, Angleggsdrift, Trondheim, Norway, p 20
Dahl F, Grov E, Breivik T (2007) Development of a new direct test method for estimating cutter life, based on the Sievers’ J miniature drill test. Tunn Undergr Space Technol 22:106–116
Dahl F, Bruland A, Grov E, Nilsen B (2010) Trademarking the NTNU/SINTEF drillability test indices. Tunn Tunn Int (June), 44–46
Dahl F, Bruland A, Jakobsen PD, Nilsen B, Grov E (2012) Classifications of properties influencing the drillability of rocks, based on the NTNU/SINTEF test method. Tunn Undergr Space Technol 28:150–158
Davis JC (1973) Statistics and data analysis in geology. Wiley, New York, p 550
Deere DU, Miller RP (1966) Engineering classification and index properties for intact rocks. Tech Rep no. AFNL-TR-65-116, Air Force Weapons Laboratory, New Mexico, p 300
Dursun AE, Gokay MK (2016) Cuttability assessment of selected rocks through different brittleness values. Rock Mech Rock Eng 49(4):1173–1190
Ellecosta P, Schneider S, Kasling H, Thuro K (2015) Hardness—a new method for characterising the interaction of TBM disc cutters and rocks?. In: Proceedings of the 13th congress on rock mechanics, ISRM Congress 2015. In-novation in applied and theoretical rock mechanics, Palais des Congres der Montre al, Canada, Paper 688, p 10. (ISBN: 978-1926872-25-4)
Ersoy A, Waller MD (1995) Textural characterisation of rocks. Eng Geol 39:123–136
Espallargas N, Jakobsen PD, Langmaack L, Macias FJ (2015) Influence of corrosion on the abrasion of cutter steels used in TBM tunnelling. Rock Mech Rock Eng 48(1):261–275
Farrokh E, Rostami J, Laughton C (2011) Analysis of unit supporting time and support installation time for Open TBMs. Rock Mech Rock Eng 44(4):431–445
Fueten F, Mason J (2007) An artificial neural net assisted approach to editing edges in petrographic images collected with the rotation polarizer stage. Comput Geosci 33:1176–1188
Gong QM, Zhao J (2009) Development of a rock mass characteristics model for TBM penetration rate prediction. Int J Rock Mech Min Sci 46(1):8–18
Hashemnejad A, Ghafoori M, Tarigh Azali S (2016) Utilizing water, mineralogy and sedimentary properties to predict LCPC abrasivity coefficient. Bull Eng Geol Environ 75(2):841–851
Hassanpour J (2009) Investigation of the effect of engineering geological parameters on TBM performance and Modifications to existing prediction models. Ph.D. Thesis, Tarbiat Modares University, Tehran, Iran
Hassanpour J, Rostami J, Tarigh Azali S, Zhao J (2014) Introduction of an empirical TBM cutter wear prediction model for pyroclastic and mafic igneous rock; a case history of Karaj water conveyance tunnel, Iran. Tunn Undergr Space Technol 43(2014):222–231
Howarth DF, Rowlands JC (1987) Quantitative assessment of rock texture and correlation with drillability and strength properties. Rock Mech Rock Eng 20:57–85
Hugman RH, Friedman M (1979) Effects of texture and composition on mechanical behavior of experimentally deformed carbonate rocks. Am Assoc Pet Geol Bull 63(9):1478–1489
ISRM (1981) Rock characterization, testing and monitoring. Pergamon, Oxford, ISRM suggested methods, p 211
ISRM (1985) Suggested methods for determining point load strength. Int J Rock Mech Min Sci Geomech Abstr 22(2):51–60
ISRM (2007) The complete ISRM suggested methods for rock characterization, testing and monitoring: 1974–2006. In: Ulusay R, Hudson JA (eds) Suggested methods prepared by the commission on testing methods. International Society for Rock Mechanics. Compilation Arranged by the ISRM Turkish National Group, Ankara, p 293
Izadi H, Sadri J, Mehran NA (2015) A new intelligent method for minerals segmentation in thin sections based on a novel incremental color clustering. Comput Geosci 81:38–52
Jakobsen PD, Bruland A, Dahl F (2013) Review and assessment of the NTNU/SINTEF Soil Abrasion Test (SAT™) for determination of abrasiveness of soil and soft ground. Tunn Undergr Space Technol 37:107–114
Jin X (2012) Filed Nov. 14, 2007, and issued Sept. 4 (2012) Segmentation-based image processing system. U.S. Patent 8,260,048
Jung J, Brousse R (1959) Classification modale des roches éruptive.s: roches éruptive.s utilizant les données fournies par le compteur de points. Paris: Masson & Cie
Kahraman S, Fener M, Kasling H, Thuro K (2016) The influences of textural parameters of grains on the LCPC abrasivity of coarse-grained igneous rocks. Tunn Undergr Space Technol 58:216–223
Karakus M, Kumral M, Kilic O (2005) Predicting elastic properties of intact rocks from index tests using multiple regression modeling. Int J Rock Mech Min Sci 42:323–330
Katz O, Reches Z, Roegiers JC (2000) Evaluation of mechanical rock properties using a Schmidt hammer. Int J Rock Mech Min Sci 37:723–728
Larsen ES, Miller FS (1935) The Rosiwal method and the modal determination of rocks. Am Mineral 20:260–273
Lashkaripour GR (2002) Predicting mechanical properties of mudrock from index parameters. Bull Eng Geol Environ 61(1):73–77
Liu Z, Shao J, Xu W, Wu Q (2015) Indirect estimation of unconfined compressive strength of carbonate rocks using extreme learning machine. Acta Geotech 10(5):651–663
Macias FJ, Jakobsen PD, Bruland A (2014a) Rock mass variability and TBM prediction. ISRM Regional Symposium - EUROCK 2014, 27-29 May, Vigo, Spain
Macias FJ, Jakobsen PD, Seo Y, Bruland A (2014b) Influence of rock mass fracturing on the net penetration rates of hard rock TBMs. Tunn Undergr Space Technol 44:108–120
Macias FJ, Dahl F, Bruland A (2016) New rock abrasivity test method for tool life assessments on hard rock tunnel boring: the rolling indentation abrasion test (RIAT). Rock Mech Rock Eng 49(5):1679–1693
Middleton A, Freestone IC, Leese MN (1985) Textural analysis of ceramic thin sections: evaluation of grain sampling procedures. Archaeometry 27(1):64–74
Johannessen O, Jacobsen K, Ronn PE, Moe, HL (1995) Project Report 2C-95 tunnelling costs for drill and blast. NTNU Trondheim, Department of Building and Construction Engineering
Moradizadeh M, Cheshomi A, Ghafoori M, TrighAzali S (2016) Correlation of equivalent quartz content, Slake durability index and Is50 with Cerchar abrasiveness index for different types of rock. Int J Rock Mech Min Sci 86:42–47
Nilsen B, Dahl F, Holzhauser J, Raleigh P (2007) The new test methodology for estimating the abrasiveness of soils for TBM tunnelling. In: Rapid excavation and tunneling conference (RETC), pp 104–116
NTH (1983) Hard Rock Tunnel Boring, Project Report 1-83. Div. of Construction Engineering, Trondheim, Norwegian Institute of Technology, p 94
Petruk W (1989) Short course on image analysis applied to mineral and earth sciences. Mineralogical Association of Canada, Ottawa
Prikryl R (2006) Assessment of rock geomechanical quality by quantitative rock fabric coefficients: limitations and possible source of misinterpretations. Eng Geol 87:149–162
Reedy CL (2006) Review of digital image analysis of petrographic thin sections in conservation research. J Am Inst Conserv 45(2):127–146
Rostami J (1997) Development of a force estimation model for rock fragmentation with disc cutters through theoretical modeling and physical measurement of crushed zone pressure. Ph. D. Thesis, Colorado School of Mines, Golden, Colorado, USA, p. 249
Rostami J, Ozdemir L, Bruland A, Dahl F (2005) Review of issues related to Cerchar abrasivity testing and their implications on geotechnical investigations and cutter cost estimates. In: Proceedings of the RETC, pp 738–751
Rostami J, Ghasemi A, Gharahbagh E, Dogruoz C, Dahl F (2014) Study of dominant factors affecting Cerchar abrasivity index. Rock Mech Rock Eng 47(5):1905–1919
Selmer-Olsen R, Lien R (1960) Bergartens borbarhet og sprengbarhet, Teknisk Ukeblad, 34, Oslo, pp 3–11
Shalabi F, Cording EJ, Al-Hattamleh OH (2007) Estimation of rock engineering properties using hardness tests. Eng Geol 90:138–147
Shorey PR, Barat D, Das MN, Mukherjee KP, Singh B (1984) Schmidt hammer rebound data for estimation of large scale in situ coal strength. Int J Rock Mech Min Sci Geomech Abstr 21:39–42
Sievers H (1950) Die Bestimmung des Bohrwiderstandes von Gesteinen, Glückauf 86: 37/38, pp 776–784. Glückauf G.M.B.H., Essen
Streckeisen A (1976) To each plutonic rock its proper name. Earth Sci Rev 12:12–33
Tandon SR, Gupta V (2013) The control of mineral constituents and textural characteristics on the petrophysical & mechanical (PM) properties of different rocks of the Himalaya. Eng Geol 153:125–143
The Science of Rock Mechanics. Part I. The Strength Properties of Rocks. In: Series on Rock and Soil Mechanics, 2nd edn, vol. 1 (1971/73), No. 2. Trans Tech Publications, Clausthal
Thuro K (1997) Drillability Prediction: Geological Influences in Hard Rock Drill and Blast Tunneling, vol 86. Springer, Geol Rundsch, pp 426–438
Thuro K, Plinninger RJ (2003) Hard rock tunnel boring, cutting, drilling and blasting: rock parameters for excavatability. In: Proceedings of the 10th ISRM Int. Congress on Rock Mechanics, Johannesburg, South Africa, pp 1227–1234
Tugrul A, Zarif IH (1999) Correlation of mineralogical and textural characteristics with engineering properties of selected granitic rocks from Turkey. Eng Geol 51:303–317
Ulusay R, Tureli K, Ider MH (1994) Prediction of engineering properties of a selected litharenite sandstone from its petrographic characteristics using correlation and multivariate statistical techniques. Eng Geol 38(1–2):135–157
Villeneuve MC (2008) Examination of geological influence on machine excavation of highly stressed tunnels in massive hard rock. PhD thesis. Queen’s University, Kingston
Vincent L (1993) Morphological grayscale reconstruction in image analysis: applications and efficient algorithms. IEEE Trans Image Process 2(2):176–201
von Matern N, Hjelmer A (1943) Forsok med pagrus (‘‘Tests with Chippings’’), Medelande nr. 65, Statens vaginstitut, Stockholm, pp 65. (English summary, pp 56–60)
Yagiz S (2002) Development of rock fracture and brittleness indices to quantify the effects of rock mass features and toughness in the CSM model basic penetration for hard rock tunneling machines. Ph.D. Thesis, Department of Mining and Earth Systems Engineering, Colorado School of Mines, Golden, Colorado, USA, p 289
Yagiz S (2008) Utilizing rock mass properties for predicting TBM performance in hard rock condition. Tunn Undergr Space Technol 23(3):326–339
Yagiz S (2011) P-wave velocity test for assessment of geotechnical properties of some rock materials. Bull Mater Sci 34(4):947–953
Yarali O, Kahraman S (2011) The drillability assessment of rocks using the different brittleness values. Tunn Undergr Space Technol 26:406–414
Yilmaz I, Yuksek G (2009) Prediction of the strength and elasticity modulus of gypsum using multiple regression, ANN, and ANFIS models. Int J Rock Mech Min Sci 46(4):803–810
Zare S (2007) Prediction model and simulation tool for time and costs of drill and blast tunnelling. PhD thesis, Department of Civil and Transport Engineering, NTNU, Trondheim, Norway
Zare S, Bruland A (2013) Applications of NTNU/SINTEF drillability indices in hard rock tunneling. Rock Mech Rock Eng 46:179–187
Zare S, Bruland A, Rostami J (2016) Evaluating D&B and TBM tunnelling using NTNU prediction models. Tunn Undergr Space Technol 59:55–64
Zhao K, Janutolo M, Barla G (2012) A completely 3D model for the simulation of mechanized tunnel excavation. Rock Mech Rock Eng 45(4):475–497
Zhou Y, Starkey J, Mansinha L (2004) Segmentation of petrographic images by integrating edge detection and region growing. Comput Geosci 30:817–831
Acknowledgements
The authors gratefully acknowledge Mr. Filip Dahl (SINTEF, Norway) for his useful documents and guidance upon the NTNU/SINTEF rock drillability test procedures and apparatus.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Aligholi, S., Lashkaripour, G.R., Ghafoori, M. et al. Evaluating the Relationships Between NTNU/SINTEF Drillability Indices with Index Properties and Petrographic Data of Hard Igneous Rocks. Rock Mech Rock Eng 50, 2929–2953 (2017). https://doi.org/10.1007/s00603-017-1289-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00603-017-1289-9