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水下高速航行体艏部水动力自噪声预报方法及低噪声线型设计
引用本文:吕世金,苗金林,张晓伟. 水下高速航行体艏部水动力自噪声预报方法及低噪声线型设计[J]. 水动力学研究与进展(A辑), 2012, 27(3): 303-310
作者姓名:吕世金  苗金林  张晓伟
作者单位:中国船舶科学研究中心船舶振动噪声国家重点实验室,江苏无锡,214082
摘    要:针对水下高速航行体水动力自噪声特征,采用过渡区声辐射理论,建立了航行体艏部水动力自噪声预报方法。经模型试验考核偏差小于3dB,故该方法可以用于可用于航行体艏部水动力自噪声预报及低噪声线型设计。理论研究表明,航行体艏部水动力自噪声与边界层层流向湍流过渡转捩点位置有关,转捩点越往后,水动力自噪声越低。在此基础上,针对通用鱼雷外形,给出雷头低噪声设计拟合曲线。进一步分析发现,鱼雷艏部水动力自噪声随着平头端面直径的增大而增加,端面直径增加一倍,水动力自噪声增加约5dB,因此可以采用小的端面直径,来降低鱼雷艏部水动力自噪声。

关 键 词:水下高速航行体  水动力噪声  预报  低噪声设计

Prediction method of hydrodynamic self-noise and design of low noise bow profile for underwater high speed vehicle
LU Shi-jin , MIAO Jin-lin , ZHANG Xiao-wei. Prediction method of hydrodynamic self-noise and design of low noise bow profile for underwater high speed vehicle[J]. Chinese Journal of Hydrodynamics, 2012, 27(3): 303-310
Authors:LU Shi-jin    MIAO Jin-lin    ZHANG Xiao-wei
Affiliation:(National Key Laboratory on Ship Vibration and Noise,China Ship Science Research Center, Wuxi 214082,China)
Abstract:Using the sound radiation theory of boundary layer transition,a prediction method for hydrodynamic self-noise radiating from the bow of high speed underwater vehicle is established.The deviation between the results from this method and that from the model experiment can be less than 3dB.This method can be applied to predict the hydrodynamic self-noise of vehicle’s bow and to design low noise body form of the vehicle subsequently.The theory shows that the hydrodynamic self-noise of vehicle’s bow is related to the location of the transition point of boundary layer and the hydrodynamic self-noise is lower if the transition point located backward.By performing curve fittings for the bow lines of torpedoes in wide scope,further investigation shows that the hydrodynamic self-noise of torpedo’s bow increases as the diameter of flat head surface increasing,and the noise increases by 5dB if the diameter is doubled.So the flat head with smaller diameter will be helpful to decrease the hydrodynamic self-noise of torpedo’s bow.
Keywords:underwater vehicle  hydrodynamic self-noise  prediction  low noise profile design
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