Optimization design of axial flow fan blades for V-type condenser based on dynamic MSST-PANS model correction and surrogate model

Abstract

V-type condensers are commonly used in multi-split air conditioners, heat pump units, and large refrigeration equipment. With their unique bidirectional air inlet structure, they guide airflow through narrow fins with a spacing of 2 mm for heat exchange. However, the unique geometric structure leads to curved channels where adverse pressure gradients couple with strong velocity gradients in air fluids, easily causing strong swirling and flow separation phenomena. Traditional simulation methods often fail due to difficulty in capturing high-curvature turbulence. Therefore, this study proposes an improved method based on curvature factors to regulate turbulence production terms. By coupling high curvature and strong swirl scales to reconstruct turbulence viscosity correction variables, a curvature-corrected dynamic MSST-PANS model is introduced to ensure prediction accuracy. The curvature correction term enhances the accuracy of turbulence simulation under complex geometries, compensating for the shortcomings of traditional models. At the same time, Bezier curves are used to parameterize the blade profile, combined with the NSGA-II multi-objective genetic optimization algorithm to optimize the cascade design, improving flow field uniformity and heat exchange efficiency. Through the optimization design of the axial flow fan blades for the V-type condenser, the flow characteristics and heat exchange efficiency are significantly improved. After optimization, the overall average flow velocity of the modified condenser increased by 14.27%, the standard deviation of average flow velocity decreased by 21.18% compared to the prototype, the maximum impeller efficiency increased by 8.7%, and the heat exchange rate increased by 10.27%, further enhancing performance.