Novel Method of Predicting Deposition Efficiency in Cold Spray by Incorporating Sphericity into 1D Numerical Models

Abstract In cold spray (CS) additive manufacturing process, micrometer scale particles accelerated through a supersonic nozzle are targeted on a surface with velocities in the rage of 300-1500 m/s in solid state. The impact energy of the particles leads them to deform plastically with high shear energy near the impact interface and adhere to the surface metallurgically, mechanically, and chemically. Using CS, deposition of metals, metal matrix composites, and polymers are achieved with high adhesive/cohesive strength and low porosity. Sensitivity of the CS additive manufacturing process to the variabilities in the process parameters are still being understood. Among the process parameters, particle morphology can have significant implications on drag forces, and therefore, on the particle impact velocity. This in turn affects the deposition efficiency (DE) and the quality of products. In this work, a new approach is introduced for computing DE by incorporating particle sphericity and its variation into one-dimensional numerical models. Size, sphericity, and the variability of size and sphericity of aluminum, copper, titanium, and tantalum particles are measured from static optical microscope images. The data is used for predicting impact velocity, temperature, and DE. The model results are then compared with particle velocity measurements.