Skip to main content
Log in

Optimum design of the internal flushing channel of a drill bit using RSM and CFD simulation

  • Published:
International Journal of Precision Engineering and Manufacturing Aims and scope Submit manuscript

Abstract

In this study, a series of computational fluid dynamics (CFD) simulations was conducted to evaluate and optimize the design of the internal flushing channel for a drill bit. The Star-CCM+ code was used to simulate the multi-phase flow of flushing air and escaping rock particles during drilling work. The values of the input parameters used for the simulation were obtained from in-situ drilling test results. Finally after choosing three major design factors and determining their appropriate sizes, the experimental design method known as response surface methodology (RSM) was used to obtain the optimum value of each factor.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Abbreviations

A P :

Projected area of the particle (m2)

C ε1, C ε2, C ε3, C ε4 :

Coefficients of turbulent dissipation rate

C d :

Drag coefficient

C vm :

Virtual mass coefficient

F b :

Particle body force (N)

F s :

Particle surface force (N)

f u :

User defined body force (N)

g :

Gravity acceleration (m s−2)

k :

Turbulent kinetic energy (m2 s−2)

m p :

Particles’ mass (kg)

\(\dot m_p\) :

Rate of mass transfer to the particle (kg s−1)

p :

Pressure (Pa)

p abs :

Absolute pressure (Pa)

p static :

Gradient of the static pressure in the continuous phase (Pa)

R :

Universal gas constant (J mol−1 K−1)

r p :

Position of the rock particle

T :

Fluid temperature (K)

t :

Time (s)

u i :

Fluctuant fluid velocity of i (i = x) (m s−1)

u j :

Fluctuant fluid velocity of j (j = y) (m s−1)

v i :

Fluid velocity in direction i (i = x) (m s−1)

v j :

Fluid velocity in direction j (j = y) (m s−1)

v k :

Fluid velocity in direction k (k = z) (m s−1)

v s :

Particle slip velocity (m s−1)

v p :

Absolute velocity of a particle (m s−1)

v g :

Grid velocity of a particle (m s−1)

V P :

Volume of the particle (m3)

δ :

Kroneker delta

ɛ :

Turbulence dissipation rate (m2 s−3)

µ:

Molecular viscosity of fluid (kg s m−2)

µ t :

Turbulence viscosity (kg s m−2)

µ m :

Mean value of rock particle diameter (mm)

ρ :

Particle density (kg m−3)

ρ c :

Density of continuous phase (kg m−3)

ρ f :

Fluid density (kg m−3)

σ st :

Standard deviation of rock particles’ diameters (mm)

σ k :

Prandlt number of turbulence kinetic energy

σ ε :

Prandlt number of turbulence dissipation rate

References

  1. The Freedonia Group Inc., “World Mining Equipment,” 2009.

    Google Scholar 

  2. Hustrulid, W. A. and Fairhurst, C., “A Theoretical and Experimental Study of the Percussive Drilling of Rock Part I-Theory of Percussive Drilling,” International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, Vol. 8, No. 4, pp. 311–333, 1971.

    Article  Google Scholar 

  3. Hustrulid, W. A. and Fairhurst, C., “A Theoretical and Experimental Study of the Percussive Drilling of Rock Part II-Force-Penetration and Specific Energy Determinations,” International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, Vol. 8, No. 4, pp. 335–356, 1971.

    Article  Google Scholar 

  4. Hustrulid, W. A. and Fairhurst, C., “A Theoretical and Experimental Study of the Percussive Drilling of Rock Part III-Experimental Verification of the Mathematical Theory,” International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, Vol. 9, No. 3, pp. 417–418, 1972.

    Article  Google Scholar 

  5. Hustrulid, W. A. and Fairhurst, C., “A Theoretical and Experimental Study of the Percussive Drilling of Rock Part IV-Application of the Model to Actual Percussion Drilling,” International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, Vol. 9, no. 3, pp. 431–442, 1972.

    Article  Google Scholar 

  6. Chiang, L. E. and Elias, D. A., “A 3D FEM Methodology for Simulating the Impact in Rock-Drilling Hammers,” International Journal of Rock Mechanics and Mining Sciences, Vol. 45, No. 5, pp. 701–711, 2008.

    Article  Google Scholar 

  7. Bu, C., Qu, Y., Cheng, Z., and Liu, B., “Numerical Simulation of Impact on Pneumatic DTH Hammer Percussive Drilling,” Journal of Earth Science, Vol. 20, No. 5, pp. 868–878, 2009.

    Article  Google Scholar 

  8. Oh, J. Y., Lee, G. H., Kang, H. S., and Song, C. S., “Modeling and Performance Analysis of Rock Drill Drifters for Rock Stiffness,” Int. J. Precis. Eng. Manuf., Vol. 13, No. 12, pp. 2187–2193, 2012.

    Article  Google Scholar 

  9. Shin, D. Y. and Song, C. H., “Performance Optimization of Downthe-Hole Hammer Using Taguchi Method,” Transactions of the Korean Society of Mechanical Engineers A, Vol. 36, No. 1, pp. 109–116, 2012.

    Article  MathSciNet  Google Scholar 

  10. Song, C. H., Kwon, K. B., Park, J. Y., Shin, D. Y., and Cho, J. W., “Flow Path Optimization and Compressor Sizing of Top-Hammer Drill Bit using CFD Simulation,” Proc. of the KSFC 2012 Autumn Conference, pp. 19–25, 2012.

    Google Scholar 

  11. Song, C. H., Kwon, K. B., Park, J. Y., Shin, D. Y., and Cho, J. W., “Optimization of Flow Path of Drill Bit Using CFD Simulation,” Journal of Korean Society for Rock Mechanics, Tunnel & Underground space, Vol. 22, No. 4, pp. 257–265, 2012.

    Article  Google Scholar 

  12. Yoon, H. S., Wu, R., Lee, T. M., and Ahn, S. H., “Geometric Optimization of Micro Drills using Taguchi Methods and Response Surface Methodology,” Int. J. Precis. Eng. Manuf., Vol. 12, No. 5, pp. 871–875, 2011.

    Article  Google Scholar 

  13. Li, Z. Z., Cheng, T. H., Xuan, D. J., Ren, M., Shen, G. Y., and Shen, Y. D., “Optimal Design for Cooling System of Batteries using DOE and RSM,” Int. J. Precis. Eng. Manuf., Vol. 13, No. 9, pp. 1641–1645, 2012.

    Article  Google Scholar 

  14. Kim, K. Y., Kim, C. Y., and Kim, K. S., “Assessment of Hydraulic Drilling Data on Homogeneous Rock Mass,” Journal of Korean Society for Rock Mechanics, Vol. 18, No. 6, pp. 480–490, 2008.

    Google Scholar 

  15. Rhie, C. M. and Chow, W. L., “Numerical Study of the Turbulent Flow Past an Airfoil with Trailing Edge Separation,” AIAA Journal, Vol. 21, No. 11, pp. 1525–1532, 1983.

    Article  MATH  Google Scholar 

  16. Lee, B. H., Yi, J. S., Kim, B. H., and Chung, H. S., “A Numerical Analysis on EGR Cooler of CI Engine,” Proc. of Korean Society of Automotive Engineers Annual Conference, pp. 197–202, 2009.

    Google Scholar 

  17. El Tahry, S. H., “K-ɛ Equation for Compressible Reciprocating Engine Flows,” Journal of Energy, Vol. 7, No. 4, pp. 345–353, 1983.

    Article  Google Scholar 

  18. CD-Adapco, “STAT-CD Version 3.24 Methodology,” 2004.

    Google Scholar 

  19. Launder, B. E. and Spalding, D., “The Numerical Computation of Turbulent Flows,” Computer Methods in Applied Mechanics and Engineering, Vol. 3, No. 2, pp. 269–289, 1974.

    Article  MATH  Google Scholar 

  20. CD-Adapco, “STAR-CCM+ Version 7.02 0.11 User guide,” 2011.

    Google Scholar 

  21. Cundall, P. A. and Strack, O. D., “A Discrete Numerical Model for Granular Assemblies,” Geotechnique, Vol. 29, No. 1, pp. 47–65, 1979.

    Article  Google Scholar 

  22. Sah, J. Y. and Choi, J. W., “Analysis of Granular Flow using DEM,” Transactions of the Korea Society of Mechanical Engineers B, Vol. 28, No. 3, pp. 256–264, 2004.

    Article  Google Scholar 

  23. Markku, T., “Surface Drilling in Open Pit Mining,” 1st Ed., pp. 7–9, 2006.

    Google Scholar 

  24. Kwak, J. S., “Application of Taguchi and Response Surface Methodologies for Geometric Error in Surface Grinding Process,” International Journal of Machine Tools and Manufacture, Vol. 45, No. 3, pp. 327–334, 2005.

    Article  Google Scholar 

  25. Aslan, N. and Cebeci, Y., “Application of Box-Behnken Design and Response Surface Methodology for Modeling of Some Turkish Coals,” Fuel, Vol. 86, No. 1, pp. 90–97, 2007.

    Article  Google Scholar 

  26. Kuehl, R. O., “Design of Experiments: Statistical Principles of Research Design and Analysis,” Cengage Learning, 2nd Ed., pp. 435–440, 2000.

    Google Scholar 

  27. Minitab Inc., “Minitab Guide,” http://www.webpages.uidaho.edu/~brian/minitab_guide_msbtc_georgetown_university.pdf (Accessed 21 MAY 2014)

  28. Wu, L., Yick, K. l., Ng, S. P., and Yip, J., “Application of the Box-Behnken Design to the Optimization of Process Parameters in Foam Cup Molding,” Expert Systems with Applications, Vol. 39, No. 9, pp. 8059–8065, 2012.

    Article  Google Scholar 

  29. Karnachi, A. A. and Khan, M. A., “Box-Behnken Design for the Optimization of Formulation Variables of Indomethacin Coprecipitates with Polymer mixtures,” International Journal of Pharmaceutics, Vol. 131, No. 1, pp. 9–17, 1996.

    Article  Google Scholar 

  30. Smits, A. J., “A Physical Introduction to Fluid Mechanics (in Korean),” John Wiley, pp. 363–366, 2000.

    Google Scholar 

  31. Kim, M. S., Kang, D. O., and Heo, S. J., “Innovative Design Optimization Strategy for the Automotive Industry,” International Journal of Automotive Technology, Vol. 15, No. 2, pp. 291–301, 2014.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jung-Woo Cho.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, CH., Kwon, KB., Park, JY. et al. Optimum design of the internal flushing channel of a drill bit using RSM and CFD simulation. Int. J. Precis. Eng. Manuf. 15, 1041–1050 (2014). https://doi.org/10.1007/s12541-014-0434-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12541-014-0434-6

Keywords

Navigation