高鲁棒性的螺旋桨片条理论非线性修正方法

针对螺旋桨极端状态分析计算的问题，对片条理论（BEMT）方法进行了一定的改进。虽然片条理论在常规工况下能够比较准确地计算拉力和功率，但在考虑严重非线性的部分工况下，如很低或很高前进比状态，传统片条理论存在一定的局限性，无法可靠地计算拉力、功率、环量分布及诱导速度。鉴于此，分析了传统片条理论方程解的不唯一性和诱导速度的奇异性，然后结合涡流理论提出了一种环量迭代修正方法，解决了传统片条理论在极端工况下的计算困难。另一方面，为了兼顾多种叶素非线性效应，应用人工神经网络对叶素的大迎角特性、低雷诺数特性及跨声速特性进行特征提取，并为片条理论提供高效的叶素非线性气动特性预测。通过与计算及试验结果对比，验证了修正片条理论方法针对本文计算模型能够在很低/很高前进比下进行准确计算。在本文算例中，拉力和功率的相对误差在常规工作段可以保持在5%以内，在很低和很高前进比下仍可以保持在10%以内。

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

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.