High-robustness nonlinear-modification method for propeller blade element momentum theory

被引：0
|
作者：
Fan Z. [1 ,2 ]
Zhou Z. [1 ,2 ]
Zhu X. [2 ]
Wang R. [1 ,2 ]
Wang K. [1 ,2 ]
机构：
[1] School of Aeronautics, Northwestern Polytechnical University, Xi'an
[2] Laboratory of Science and Technology on UAV, Northwestern Polytechnical University, Xi'an
来源：
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2018年 / 39卷 / 08期
关键词：
Blade element momentum theory; Neural networks; Propeller; Vertical take-off and landing; Vortex flow;
D O I：
10.7527/S1000-6893.2018.21869
中图分类号：
学科分类号：
摘要：
The Blade Element Momentum Theory (BEMT) method is modified to analyze the propeller under extreme conditions. The BEMT method can give accurate calculation of thrust and power at normal conditions, but when it comes to the nonlinear condition, such as the conditions of extreme low and high advance ratio, BEMT cannot calculate the thrust, power, circulation and induced velocity accurately and robustly. In view of this problem, this paper discusses non-physical solution and the singular solution of induced velocity for the BEMT equations. Based on the vortex theory, a circulation-iteration method is developed to improve the robustness of propeller analysis at extreme conditions. To take multi-nonlinear effects into consideration, an artificial neural network is used to acquire the aerodynamic characteristics of large-angle effect, low Reynolds number and transonic effects of the blade element and to provide efficient prediction of nonlinear aerodynamic characteristics of blade elements for the BEMT. The modified BEMT is validated using the Computational Fluid Dynamics (CFD) method and the experiment, and a comparison of the results show high robustness and accuracy of the modified BEMT for extreme condition analysis. Calculation results demonstrate that the relative error of the thrust and power are less than 5% at normal conditions, and less than 10% at extreme conditions. © 2018, Press of Chinese Journal of Aeronautics. All right reserved.
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