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Dominant Cutting Parameters Affecting the Specific Energy of Selected Sandstones when Using Conical Picks and the Development of Empirical Prediction Models

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Abstract

Specific energy is one of the most significant parameters in the process of rock cutting and it has been widely used for evaluating the performance of excavation machines. In this paper, based on rock cutting tests that were conducted on a linear cutting machine (LCM), the effects of relevant cutting parameters and characteristics, including the clearance angle, the cone (tip) angle of conical picks, the rake angle and the cutting depth on specific energy were investigated. Five different conical picks with the cone angles between 60° and 100° were used in the experiments. In addition, five different sandstones with uniaxial compressive strength varying from 17.91 to 85.98 MPa were subjected to cutting tests under different levels of cutting parameters. As a result of the tests, it was found that the clearance angle has a considerable effect on cutting force and specific energy. When it was greater than 10°, mean cutting force increased with the increasing cone angle, yet linearly decreased with the increasing rake angle and attack angle. However, specific energy has no statistical relationship with the attack angle, the rake angle, and the cone angle. It does not vary effectively with the relevant angles. Statistical analyses also indicate that strong relationships exist between the specific energy and the cutting depth in a power function. In this context, a general model of specific energy was proposed, and based on the test data and previous studies, empirical models of specific energy were developed using multiple non-linear regression and principal component regression methods. Besides, the statistical analyses showed a good agreement between the measured and predicted specific energy in unrelieved and relieved cutting modes. In conclusion, some prediction models of roadheader production rates were developed that were based on the models of specific energy. By comparing the results with the literature, it was found that the proposed models are valid in predicting the instantaneous cutting rate of roadheader especially at the cutting depth of 7–9 mm. They can be used for preliminary estimation of the production rate of roadheaders. Thus, it can be claimed that the models can offer effective solutions for the prediction of production rate of roadheaders equipped with conical picks.

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Abbreviations

d :

Depth of cut (mm)

FC:

Cutting force

FN:

Normal force

FCm :

Mean cutting force (N)

ICR:

Instantaneous cutting rate (m3/h)

k :

Energy transfer ratio

k opt :

Ratio of specific energy in relieved to unrelieved cutting mode

L :

Cutting distance (m)

M :

Mass of rock chips (kg)

P :

Cutting power of the cutting head (kW)

R σ :

Coefficient representing rock strength parameters

SE:

Specific energy (kWh/m3)

SEu :

Specific energy in unrelieved mode

SEopt :

Optimum specific energy in relieved mode

σ c :

Uniaxial compressive strength of rock (MPa)

σ t :

Tensile strength of rock (MPa)

ρ :

Density of the rock (kg/m3)

α :

Tilt angle

β :

Rake angle

γ :

Attack angle

θ :

Clearance angle

ϕ :

Cone angle of the pick

References

  • Avunduk E, Tumac D, Atalay AK (2014) Prediction of roadheader performance by artificial neural network. Tunn Undergr Space Technol 44:3–9

    Article  Google Scholar 

  • Balci C, Bilgin N (2007) Correlative study of linear small and full-scale rock cutting tests to select mechanized excavation machines. Int J Rock Mech Min Sci 44:468–476

    Article  Google Scholar 

  • Balci C, Demircin MA, Copur H, Tuncdemir H (2004) Estimation of optimum specific energy based on rock properties for assessment of roadheader performance. J S Afr Inst Min Metall 104(11):633–642

    Google Scholar 

  • Bilgin N, Seyrek T, Erdinc E, Shahriar K (1990) Roadheaders glean valuable tips for Istanbul Metro. Tunnels Tunnell October 29–32

  • Bilgin N, Dincer T, Copur H, Erdogan M (2004) Some geological and geotechnical factors affecting the performance of a roadheader in an inclined tunnel. Tunn Undergr Space Technol 19:629–636

    Article  Google Scholar 

  • Bilgin N, Dumac D, Feridunoglu C, Karakas AR, Akgul M (2005) The performance of a roadheader in high strength rock formations in Kücüksu tunnel. In: Proceedings of the 31st ITA-AITES World Tunnel Congress. Istanbul, pp 815–820

  • Bilgin N, Demircin MA, Copur H, Balci C, Tuncdemir H, Akcin N (2006) Dominant rock properties affecting the performance of conical picks and the comparison of some experimental and theoretical results. Int J Rock Mech Min Sci 43:139–156

    Article  Google Scholar 

  • Bilgin N, Copur H, Balci C (2012) Effect of replacing disc cutters with chisel tools on performance of a TBM in difficult ground conditions. Tunn Undergr Space Technol 27:41–51

    Article  Google Scholar 

  • Bilgin N, Copur H, Balci C (2014) Mechanical excavation in mining and civil industries CRC Press, Boca Raton, p p366

    Google Scholar 

  • Brown TT (ed) (1981) ISRM suggested methods. Rock characterization testing and monitoring. Pergamon Press, Oxford, 211 p ISRM

    Google Scholar 

  • Cardu M, Iabichino G, Oreste P, Rispoli A (2017) Experimental and analytical studies of the parameters influencing the action of TBM disc tools in tunneling. Acta Geotech. https://doi.org/10.1007/s11440-016-0453-9

    Article  Google Scholar 

  • Comakli R, Kahraman S, Balci C (2014) Performance prediction of roadheaders in metallic ore excavation. Tunn Undergr Space Technol 40:38–45

    Article  Google Scholar 

  • Copur H, Bilgin N, Tuncdemir H, Balci C (2003) A set of indices based on indentation tests for assessment of rock cutting performance and rock properties. J S Afr Inst Min Metall 103(11):589–599

    Google Scholar 

  • Copur H, Bilgin N, Balci C, Tumac D, Avunduk E (2017) Effects of different cutting patterns and experimental conditions on the performance of a conical drag tool. Rock Mech Rock Eng. https://doi.org/10.1007/s00603-017-1172-8

    Article  Google Scholar 

  • Dursun AE, Gokay MK (2016) Cuttability assessment of selected rocks through different brittleness values. Rock Mech Rock Eng 49(4):1173–1190

    Article  Google Scholar 

  • Evans I (1984) A theory of the cutting force for point-attack picks. Int J Min Eng 2:63–71

    Article  Google Scholar 

  • Fowell RJ, Ochei NN (1984) A comparison of dust make and energy requirements for rock cutting tools. Int J Min Eng 2:73–83

    Article  Google Scholar 

  • Gehring KH (1989) Cutting comparison. Tunn Tunn Int 21(11): 27–30

    Google Scholar 

  • Gunes N, Yurdakul M, Goktan RM (2007) Prediction of radial bit cutting force in high-strength rocks using multiple linear regression analysis. Int J Rock Mech Min Sci 44:962–970

    Article  Google Scholar 

  • Gunes N, Tumac D, Goktan RM (2014) Rock cuttability assessment using the concept of hybrid dynamic hardness (HDH). Bull Eng Geol Environ 74(4):1–12

    Google Scholar 

  • He X, Xu C (2016) Specific energy as an index to identify the critical failure mode transition depth of rock cutting. Rock Mech Rock Eng 49(4):1461–1478

    Article  Google Scholar 

  • Hughes H (1972) Some aspects of rock machining. Int J Rock Mech Min Sci 9:205–211

    Article  Google Scholar 

  • Hurt KG, Evans I (1981) Point attack tools: an evaluation of function and use for rock cutting. Min Eng 140:673–675

    Google Scholar 

  • Hurt KG, McAndrew KM (1985) Cutting efficiency and life of rock cutting picks. Min Sci Technol 2:139–151

    Article  Google Scholar 

  • Levenberg K (1944) A method for the solution of certain non-linear problems in least squares. J Heart Lung Transpl 2(4):436–438

    Google Scholar 

  • Marquardt DW (1963) An algorithm for least square estimation of non-linear parameters. J Soc Ind Appl Math 11(2):431–441

    Article  Google Scholar 

  • Mellor M (1972) Normalization of specific energy values. Int J Rock Mech Min Sci 9:661–663

    Article  Google Scholar 

  • Nishimatsu Y (1972) The mechanics of the rock cutting. Int J Rock Mech Min Sci 9:261–270

    Article  Google Scholar 

  • Origliasso C, Cardu M, Kecojevic V (2014) Surface miners: evaluation of the production rate and cutting performance based on rock properties and specific energy. Rock Mech Rock Eng 47(2):757–770

    Article  Google Scholar 

  • Rostami J, Ozdemir L, Neil DM (1994) Performance prediction: a key issue in mechanical hard rock mining. Min Eng 46(11):1264–1267

    Google Scholar 

  • Shao W, Li XS, Sun Y, Huang H (2017) Parametric study of rock cutting with SMART*CUT picks. Tunn Undergr Space Technol 62:134–144

    Article  Google Scholar 

  • Thuro K, Plinninger RJ (1999) Predicting roadheader advance rates. Tunn Tunnel 6:36–39

    Google Scholar 

  • Tiryaki B (2009) Estimating rock cuttability using regression trees and artificial neural networks. Rock Mech Rock Eng 42(6):939–946

    Article  Google Scholar 

  • Tiryaki B, Dikmen AC (2006) Effects of rock properties on specific cutting energy in linear cutting of sandstones by picks. Rock Mech Rock Eng 39(2):89–120

    Article  Google Scholar 

  • Tumac D, Bilgin N, Feridunoglu C, Ergin H (2007) Estimation of rock cuttability from shore hardness and compressive strength properties. Rock Mech Rock Eng 40(5):477–490

    Article  Google Scholar 

  • Wang X, Liang YP, Wang QF, Zhang ZY (2017) Empirical models for tool forces prediction of drag-typed picks based on principal component regression and ridge regression methods. Tunn Undergr Space Technol 62:75–95

    Article  Google Scholar 

  • Yagiz S (2009) Assessment of brittleness using rock strength and density with punch penetration test. Tunnel Undergr Space Technol 24:66–74

    Article  Google Scholar 

  • Yurdakul M, Gopalakrishnan K, Akdas H (2014) Prediction of specific cutting energy in natural stone cutting processes using the neuro-fuzzy methodology. Int J Rock Mech Min Sci 67:127–135

    Article  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge the Open Fund of Chongqing Key Laboratory of Manufacturing Equipment Mechanism Design and Control (Grant No. KFJJ2016032), the Chongqing Science and Technology Innovation leading talent support plan (Grant No. CSTCCXLJRC201709), National Science and Technology Major Project of China (Grant No. 2016ZX05043005). The authors also would like to acknowledge to Prof. N. Bilgin, Prof. H. Copur and Prof. C. Balci (Istanbul Technical University, Turkey) for kindly providing data for evaluating the cutting test results.

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Authors and Affiliations

  1. Chongqing Key Laboratory of Manufacturing Equipment Mechanism Design and Control, Chongqing Technology and Business University, Chongqing, 400067, China

    Xiang Wang & Qing-Feng Wang

  2. China Coal Technology Engineering Group Chongqing Research Institute, Chongqing, 400039, China

    Xiang Wang, Qing-Feng Wang & Lin Yang

  3. State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing, 400044, China

    Yun-Pei Liang

  4. Department of Mining and Mineral Extraction, Zonguldak Vocational School, Bulent Ecevit University, 67500, Zonguldak, Turkey

    Okan Su

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  1. Xiang Wang
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Correspondence to Xiang Wang.

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Wang, X., Wang, QF., Liang, YP. et al. Dominant Cutting Parameters Affecting the Specific Energy of Selected Sandstones when Using Conical Picks and the Development of Empirical Prediction Models. Rock Mech Rock Eng 51, 3111–3128 (2018). https://doi.org/10.1007/s00603-018-1522-1

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