Nozzle optimization for cold gas dynamic spraying

Oleksandr Shorinov, Nina Savchenko, Olha Shypul, Dmytro Bilan

Abstract


This study investigates the influence of nozzle geometry on the characteristics of the cold gas dynamic spraying (CGDS) process under low-pressure conditions (up to 1.0 MPa). This study aims to develop a methodology for the multicriteria optimization of nozzle geometric parameters to achieve the required particle velocity for the formation of high-quality coatings using CGDS at low pressure. The research objectives are as follows: to identify the key geometric parameters of the nozzle (critical and exit diameters, and the length of the divergent section) that have the most significant impact on particle velocity; to develop an analytical model based on isentropic gas-dynamic modeling; and to perform statistical analysis using the experimental design method. Methods. An interdisciplinary approach was used, combining isentropic flow modeling, response surface methodology (RSM), second-order regression analysis, and analysis of variance (ANOVA) to achieve high-accuracy modeling of complex interactions. A total of 47 computational-analytical experiments were conducted to build a mathematical model describing particle velocity as a function of five factors related to nozzle geometry, gas temperature, and inlet pressure. Results. A precise regression model (R² > 0.95) was developed to predict the velocity of aluminum particles with a diameter of 25 µm at the nozzle exit with high reliability. The optimal parameter combination achieving a velocity exceeding 499 m/s was determined, ensuring high-quality coating. It was proven that the proper selection of nozzle geometry and gas parameters allows effective energy transfer to powder particles even under limited pressure (1 MPa). Conclusions. The proposed nozzle design optimization method improves the efficiency of the CGDS process by increasing particle velocity without increasing gas pressure, which is especially important for energy-efficient technologies for applying protective and restorative coatings under modern engineering challenges. The practical application of the obtained results can enhance industrial spraying technologies, reduce energy consumption, and extend the service life of refurbished components.

Keywords


cold gas dynamic spraying; nozzle geometry; isentropic modeling; particle velocity; statistical analysis; ANOVA; multi-objective optimization; low pressure

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DOI: https://doi.org/10.32620/aktt.2025.4sup2.16