| 积冰几何特性对翼型性能影响的神经网络预测 |
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| 引用本文： | 袁坤刚,曹义华. 积冰几何特性对翼型性能影响的神经网络预测[J]. 北京航空航天大学学报, 2008, 34(8): 900-903 |
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| 作者姓名： | 袁坤刚 曹义华 |
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| 作者单位： | 北京航空航天大学 航空科学与工程学院, 北京 100191 |
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| 摘 要： | 积冰几何形状对翼型气动系数的影响是复杂的.采用BP(Back Propagation)神经网络的LM(Levenberg-Marguardt)学习算法,建立明冰的典型几何特性(冰角前缘半径、冰角高度和冰角位置)对翼型气动系数影响的神经网络,得到该3种几何参数对气动系数影响的规律;建立了典型冰形参数对最大升力系数影响的神经网络,该网络能很好的预测冰形参数对应的最大升力系数值;此外,建立了冰型位置对舵面铰链力矩系数影响的神经网络.仿真结果表明,BP神经网络仿真结果与实验值具有高度一致性,并能预测非实验值条件下的气动系数;翼型表面积冰位置变化对气动系数影响最大;铰链力矩系数在失速迎角达到之前就发生突变,可以更安全地用来预测失速的发生.
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| 关 键 词： | 积冰 气动性能 气动系数 神经网络 失速 |
| 收稿时间： | 2007-07-13 |
Effect of ice geometry to airfoil performance using neural networks prediction |
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| Yuan Kungang,Cao Yihua. Effect of ice geometry to airfoil performance using neural networks prediction[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(8): 900-903 |
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| Authors: | Yuan Kungang Cao Yihua |
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| Affiliation: | School of Aeronautic Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China |
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| Abstract: | The ice accretion geometric characteristics have complex effects on airfoil aerodynamic coefficients.By using levenberg-marguardt(LM) learn algorithm of back-propagation(BP) network,several neural networks were established to get correlations between typical glaze ice geometry(ice horn leading-edge radius,ice height and ice horn position on airfoil surface) and airfoil aerodynamic coefficients.The neural network was also generated for predicting the maximum lift coefficient in typical ice accretion geometri... |
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| Keywords: | ice accretion aerodynamic performance aerodynamic coefficient neural network stall |
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