Journal of Thermal Spray Technology

, Volume 17, Issue 4, pp 551–563 | Cite as

Optical Diagnostics Study of Gas Particle Transport Phenomena in Cold Gas Dynamic Spraying and Comparison with Model Predictions

  • Sudharshan Phani Pardhasaradhi
  • Vishnukanthan Venkatachalapathy
  • Shrikant V Joshi
  • Sundararajan Govindan
Peer Reviewed

Cold gas dynamic spraying (CGDS), a relatively new thermal spraying technique has drawn a lot of attention due to its inherent capability to deposit a wide range of materials at relatively low-operating temperatures. A De Laval nozzle, used to accelerate the powder particles, is the key component of the coating equipment. Knowledge concerning the nozzle design and effect of process parameters is essential to understand the coating process and to enable selection of appropriate parameters for enhanced coating properties. The present work employs a one-dimensional isentropic gas flow model in conjunction with a particle acceleration model to calculate particle velocities. A laser illumination-based optical diagnostic system is used for validation studies to determine the particle velocity at the nozzle exit for a wide range of process and feedstock parameters such as stagnation temperature, stagnation pressure, powder feed rate, particle size and density. The relative influence of process and feedstock parameters on particle velocity is presented in this work.


cold spray modeling of cold spray nozzle design powder particle diagnostics process parameters 


  1. 1.
    A.P. Alkhimov, A.N. Papyrin, V.F. Kosarev, N.J. Nesterovich, and M.M Shuspanov, “Gas Dynamic Spraying Method for Applying a Coating,” U.S. Patent 5,302,414, April 12, 1994Google Scholar
  2. 2.
    R.C. Dykhuizen, M.F Smith, D.L. Gilmore, R.A. Neiser, X. Jiang, S. Sampath, Impact of High Velocity Cold Spray Particles. J. Thermal Spray Technol., 8(4) (1999) 559-564CrossRefGoogle Scholar
  3. 3.
    R.C. Dykhuizen, M.F. Smith, Gas Dynamic Principles of Cold Spray. J. Thermal Spray Technol., 7(2) (1998) 205-212CrossRefGoogle Scholar
  4. 4.
    A.P. Alkhimov, V.F. Kosarev, S.V. Klinkov, The Features of Cold Spray Nozzle Design. J. Thermal Spray Technol., 10(2) (2001) 375-381CrossRefGoogle Scholar
  5. 5.
    B. Jodoin, Cold Spray Nozzle Mach Number Limitation. J. Thermal Spray Technol., 11(4) (2002) 496-507CrossRefGoogle Scholar
  6. 6.
    T. Stoltenhoff, H Kreye, H.J. Richter, An Analysis of the Cold Spray Process and Its Coatings. J. Thermal Spray Technol., 11(4) (2002) 542-550CrossRefGoogle Scholar
  7. 7.
    M. Grujicic, C.L. Zhao, C. Tong, W.S. DeRosset, D. Helfritch, Analysis of the Impact Velocity of Powder Particles in the Cold-Gas Dynamic-Spray Process. Mater Sci. Eng. A, 368 (2004) 222-230CrossRefGoogle Scholar
  8. 8.
    W.-Y. Li, H. Liao, G. Douchy, C. Coddet, Optimal Design of Cold Spray Nozzle by Numerical Analysis of Particle Velocity and Experimental Validation with 316L Stainless Steel Powder. Mater. Design, 28 (2007) 2129-2137CrossRefGoogle Scholar
  9. 9.
    W.-Y. Li, H. Liao, H.-T. Wang, C.-J. Li, G. Zhang, C. Coddet, Optimal Design of Convergent-Barrel Cold Spray Nozzle by Numerical Method. Appl. Surf. Sci., 253 (2006) 708-713CrossRefGoogle Scholar
  10. 10.
    T.-C. Jen, L. Li, W. Cui, Q. Chen, X. Zhang, Numerical Investigations on Cold Gas Dynamic Spray Process with Nano and Micro Size Particles. Int. J. Heat Mass Trans., 48 (2005) 4384-4396CrossRefGoogle Scholar
  11. 11.
    T. Marrocco, D.G. McCartney, P.H. Shipway, A.J. Sturgeon, Production of Titanium Deposits by Cold-Gas Dynamic Spray: Numerical Modeling and Experimental Characterization. J. Thermal Spray Technol., 15(2) (2006) 263-272CrossRefGoogle Scholar
  12. 12.
    K. Taylor, B. Jodoin, J. Karov, Particle Loading Effect in Cold Spray. J. Thermal Spray Technol., 15(2) (2006) 273-279CrossRefGoogle Scholar
  13. 13.
    B. Jodoin, F. Raletz, M. Vardelle, Cold Spray Modeling and Validation Using an Optical Diagnostic Method. Surf. Coat. Technol., 200 (2006) 4424-4432CrossRefGoogle Scholar
  14. 14.
    J. Wu, H. Fang, S. Yoon, H. Kim, C. Lee, Measurement of Particle Velocity and Characterization of Deposition in Aluminum Alloy Kinetic Spraying Process. Appl. Surf. Sci., 252 (2005) 1368-1377CrossRefGoogle Scholar
  15. 15.
    H. Fukanuma, N. Ohno, B. Sun, R. Huang, In-flight Particle Velocity Measurements with DPV-2000 in Cold Spray. Surf. Coat. Technol., 201 (2006) 1935-1941CrossRefGoogle Scholar
  16. 16.
    X.-J. Ning, J.-H. Jang, H.-J. Kim, The Effect of Powder Properties on In-flight Particle Velocity and Deposition Process During Low Pressure Cold Spray Process. Appl. Surf. Sci., 253 (2007) 7449-7455CrossRefGoogle Scholar
  17. 17.
    M. Karimi, A. Fartaj, G. Rankin, D. Vnaderzwet, W. Birtch, J. Villafuerte, Numerical Simulation of the Cold Gas Dynamic Spray Process. J. Thermal Spray Technol., 15(4) (2006) 518-523CrossRefGoogle Scholar
  18. 18.
    W.-Y. Li, C.-J. Li, H.-T. Wang, C.-X. Li, H.-S. Bang, Measurement and Numerical Simulation of Particle Velocity in Cold Spraying. J. Thermal Spray Technol., 15(4) (2006) 559-562CrossRefGoogle Scholar
  19. 19.
    J. Karthikeyan, C.M. Kay, J. Lindeman, R.S. Lima, and C.C. Berndt, Cold Spray Processing of Titanium Powder, Thermal Spray: Surface Engineering via Applied Research, C.C. Berndt, Ed., May 8-11, 2000 (Montreal, Quebec, Canada), ASM International, 2000, p 255-262Google Scholar
  20. 20.
    P. Sudharshan Phani, D. Srinivasa Rao, S.V. Joshi, G. Sundararajan, Effect of Process Parameters and Heat Treatments on Properties of Cold Sprayed Copper Coatings. J. Thermal Spray Technol., 16(2007) 425-434CrossRefGoogle Scholar
  21. 21.
    C.B. Henderson, Drag Coefficients of Spheres in Continuum and Rarefied Flows. AIAA J., 14(6) (1976) 707-708CrossRefGoogle Scholar

Copyright information

© ASM International 2008

Authors and Affiliations

  • Sudharshan Phani Pardhasaradhi
    • 1
  • Vishnukanthan Venkatachalapathy
    • 1
  • Shrikant V Joshi
    • 1
  • Sundararajan Govindan
    • 1
  1. 1.International Advanced Research Centre for Powder Metallurgy and New Materials (ARCI)HyderabadIndia

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