Optimization of Cold Spray Nozzles Based on the Response Surface Methodology

Author(s): Kun T.1*, Wenjie H.1, Yurong W.2

1 National Aerospace University “Kharkiv Aviation Institute”, 17, Chkaloova St, 61000 Kharkiv, Ukraine;
2 Commercial Aircraft Corporation of China Ltd., 1027, Changning Rd., 200050 Shanghai, China

*Corresponding Author’s Address: [email protected]

Issue: Volume 11, Issue 1 (2024)

Submitted: August 30, 2023
Received in revised form: December 1, 2023
Accepted for publication: December 12, 2023
Available online: January 8, 2024

Kun T., Wenjie H., Yurong W. (2024). Optimization of cold spray nozzles based on the response surface methodology. Journal of Engineering Sciences (Ukraine), Vol. 11(1), pp. F1–F11. https://doi.org/10.21272/jes.2024.11(1).f1

DOI: 10.21272/jes.2024.11(1).f1

Research Area:  Processes in Machines and Devices

Abstract. Spraying technical parameters are important factors that affect spraying efficiency. Most studies on spraying technical parameters use single-factor methods to study the speed of spray particles, and few scholars have studied the joint influence of multiple factors. This article uses gas temperature, particle size, and gas pressure as independent variables, and the independent variables interact. The design-expert method was used to establish a linear regression equation model of the velocity of sprayed Al and Cu particles at the Laval exit and the velocity before deposition with the substrate, and the response surface analysis method was used to predict the optimal spraying parameters of Al and Cu particles. The study found the contribution rate of three factors to particle velocity: the prediction of particle velocity at the exit of the Laval nozzle and before deposition with the substrate was realized; the error between the predicted value of particle velocity and the actual value obtained by simulation is less than 1.6 %, indicating that the speed linear regression equation established is effective and reliable in predicting the simulation results; the optimal spraying parameters and particle speeds of Al and Cu particles were obtained through response surface analysis.

Keywords: cold spray, multi-factorial experiment, regression analysis, design optimization.


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