Employing Computational-Mathematical Techniques for Optimizing Cold Spray Deposition Efficiency

Deposition efficiency is a critical metric in evaluating the quality of cold spray deposition. It reflects the effectiveness of the process and is influenced by several factors, such as the equipment configuration, type of gas used, nozzle design, selected process parameters, and the specific powder-substrate material system.

Our proposed model integrates several mathematical frameworks to account for particle impact characteristics based on size and material properties. By incorporating the actual feedstock size distribution, it provides a comprehensive estimation of deposition efficiency. Numerical simulations are also employed to improve accuracy while maintaining computational efficiency. This model offers a versatile tool for assessing cold spray deposition efficiency across various single- and multi-material feedstocks and substrates.

The numerical results align well with previously reported experimental data and accurately capture the impact of different parameter selections on overall deposition efficiency and the chemical composition of the final deposit. This approach enables a tailored and efficient evaluation of the deposition process, facilitating comprehensive optimization across a range of variables.