CFD ANALYSIS OF COLD GAS DYNAMIC SPRAY COATING UNDER DIFFERENT CONDITIONS

Abstract

The emerging and future cold spray (CS) coating technology has limitless opportunities and possibilities. Still, parameters like particle velocity, temperature, and flow dynamics lack precise control, which may improve the coating quality, performance, and long-lasting applications. Such limitations catalyzed the evolution of simulation work. The experimental measurement is often limited by cost, time, reproducibility, failure risks, and control over variables. Complementing them with computational methods like simulations can help overcome many drawbacks. CFD Simulation is superior to the experimental methods due to its cost effectiveness, greater control over variables, continuous monitoring, reproducibility, optimization, detailed data collection, faster results, etc. Therefore, the CFD Simulation used for CS process technology necessitates the optimization of multiple parameters to achieve optimal coating performance. According to the literature, the critical particle velocity for effective deposition in CS lies within the range of 400 - 585 m/s for particle sizes around 20 µm. This study calculates the particle velocity at the nozzle exit, proximate to the substrate, for varying particle sizes and propellant gas compositions under conditions yielding extreme and least velocities. A two-dimensional axisymmetric convergent-divergent nozzle model was employed and initialized with specific parameters and boundary conditions. Commercially Pure (C.P.) Titanium was selected as the coating material, with an inlet temperature of 401 K, across particle sizes of 20 µm, 40 µm, 60 µm, 80 µm, and 100 µm. The material properties include a 4850 kg/m³ density and a specific heat capacity of 544.25 J/kg-K. To further understand the CS process, a numerical simulation was vi conducted to examine the impact of varying pressure and gas mixtures on the pre-heat temperature and impact velocity of feedstock powder particles in the Cold Spraying coating process. The analysis discovered that the pressure of 7 MPa is most effective to achieve high-impact velocities. Pure helium gas was recognized as the most suitable for maximizing the impact velocity among the gas mixtures examined. In contrast, a mixture of 80% nitrogen (N₂) and 20% helium (He) generated the maximum pre-heat temperatures. Higher impact velocities enhance the coating properties by improving particle bonding strength and the quality of the first layer deposition, which are the main factors in the Cold Spraying process. This analysis was carried out using computational fluid dynamics (CFD), an advanced method that gives similar results via simulation to experimental results. This work analyzed the impact of the powder particle shape and size on the impact velocity using CFD for the CS coating process. The geometry for simulation was modeled using SolidWorks, while the numerical analysis was carried out using ANSYS Fluent workbench. The numerical simulation uses optimal input parameters for cold spraying. The model used for analysis was a pressure-based, axisymmetric model that explains the flow dynamics in the CS nozzle. The model was the realizable k-ɛ turbulence model, known for its accuracy in representing the physics of high velocity flows. Various powder particle sizes and varying stand-off distances were used to analyze using copper as the coating material to be coated on the steel substrate. The results show the spherical powder particles were the most reliable when sprayed with a 35 mm stand-off distance. Moreover, this study observes the effect of injector length on impact velocity, particle temperature, and substrate surface temperature in the cold spraying process. A two-dimensional axisymmetric model was created in SolidWorks, and the computational analysis performed using ANSYS Fluent was used for the simulations. Titanium powder was coated on the steel substrate as the feedstock powder. This study examined the effect of different propelling gas mixtures on particle velocity and temperature. The results indicated that particle velocity was maximized with helium, an inert gas, and minimized with pure nitrogen. On the other hand, the particle and vii substrate temperatures were highest when pure nitrogen was used under identical operating conditions. Based on the findings, the 15 mm injector length is optimal for attaining a balanced performance for velocity and temperature. Finally, the study focused on how disparities in process parameters—such as pressure, temperature, material particle size, and velocity of the coating material powder, which was taken as titanium—affect the substrate surface temperature in the CS coating process. These findings contribute a unique viewpoint to CS technology. The geometry was simulated using a two-dimensional axisymmetric model, incorporating a k-ɛ turbulence model with a second-order implicit pressure-based solver. Our results show the substrate surface temperature was maximum when the injector length was 15 mm. It was also observed that the optimal nozzle barrel length corresponded to the particle injector length, suggesting a critical relationship between these components in achieving optimal coating performance. As discussed above, the results highlight several critical parameters that significantly improve experimental outcomes, including the optimal injector length, stand-off distance, and the pre-heating of powder particles. Upon analyzing the particle size and shape with various pressure ranges, the research reveals critical insights for boosting performance. Moreover, selecting the most effective carrier gases or gas mixtures is crucial for achieving maximum temperatures and impact velocities. These simulations control parameters like particle velocity, temperature, and flow dynamics, improving the performance of CS coating.