The objective of this study is to propose a cross-flow fan for VTOL applications, evaluate its aerodynamic performance, and enhance its performance through a multi-objective optimization design method. Following an investigation into a three-dimensional CFD analysis approach for assessing the fan’s aerodynamic performance, a multi-objective optimization framework that simultaneously optimizes the rotor and casing by integrating CFD analysis and a deep neural network was developed and implemented. Based on CFD-derived performance metrics, the optimized fan demonstrated a thrust-shaft power ratio approximately 12.4 % lower than that of the original fan, while achieving a thrust increase of approximately 78.1 %. This substantial improvement in thrust was attributed to elevated flow velocity and flow rate at the fan outlet. Additionally, the thrust coefficient of the cross-flow fan was shown to be more than one order of magnitude greater than that of a conventional propeller fan. Performance validation using a scaled-down model further confirmed the effectiveness of the optimization method: although the thrust-shaft power ratio of the optimized fan was approximately 3.0 % lower than the original fan, its thrust increased by approximately 64.2 %. These findings underscore the potential of the proposed optimization approach not only for high-performance fan design but also for advancing the development of next-generation VTOL aircraft.
扫码关注我们
求助内容:
应助结果提醒方式:
