Song Zhu, Qing (2006) Numerical modeling of the cold spray process. Masters thesis, Concordia University.
- Accepted Version
This thesis involves numerical modeling of several cold spray processes in order to predict the gas flow as well as the particle conditions upon impacting on a substrate. Particle normal velocity was found to be the most important factor to improve the deposition efficiency and coating quality. Particle velocity was calculated with both Lagrangian and Eulerian approaches. The Lagrangian approach was used to investigate the effect of particle size and substrate geometry in a dilute particle flow. The shape and strength of the bow shock formed near the substrate for different geometries (such as concave, convex, and flat) were studied. Consequently, the particle normal velocities impacting on the substrates located at various stand-off distances were calculated. Furthermore, the numerical simulations were repeated with particles of various sizes as well as different types of feeding gas. The results were compared to obtain the optimum substrate location and the appropriate particle size for each feeding gas. The numerical results were validated against the experimental results for the majority of the process parameters including the gas Mach number and mean particle velocity. The Eulerian approach was also implemented to model dense particulate flows. It was found that a dense particulate flow could significantly decelerate the gas flow and consequently result in small particle velocity.
|Divisions:||Concordia University > Faculty of Engineering and Computer Science > Mechanical and Industrial Engineering|
|Item Type:||Thesis (Masters)|
|Authors:||Song Zhu, Qing|
|Pagination:||xv, 85 leaves : ill. ; 29 cm.|
|Degree Name:||M.A. Sc.|
|Program:||Mechanical and Industrial Engineering|
|Thesis Supervisor(s):||Dolatabadi, Ali|
|Deposited By:||Concordia University Libraries|
|Deposited On:||18 Aug 2011 18:47|
|Last Modified:||30 Nov 2011 21:59|
Repository Staff Only: item control page
Downloads per month over past year