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A method to predict circulation control noise.

机译:一种预测循环控制噪声的方法。

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摘要

Underwater vehicles suffer from reduced maneuverability with conventional lifting append- ages due to the low velocity of operation. Circulation control offers a method to increase maneuverability independent of vehicle speed. However, with circulation control comes additional noise sources, which are not well understood. To better understand these noise sources, a modal-based prediction method is developed, potentially offering a quantitative connection between flow structures and far-field noise. This method involves estimation of the velocity field, surface pressure field, and far-field noise, using only non-time-resolved velocity fields and time-resolved probe measurements. Proper orthogonal decomposition, linear stochastic estimation and Kalman smoothing are employed to estimate time-resolved velocity fields. Poisson's equation is used to calculate time-resolved pressure fields from velocity. Curle's analogy is then used to propagate the surface pressure forces to the far field.;This method is developed on a direct numerical simulation of a two-dimensional cylinder at a low Reynolds number (150). Since each of the fields to be estimated are also known from the simulation, a means of obtaining the error from using the methodology is provided. The velocity estimation and the simulated velocity match well when the simulated additive measurement noise is low. The pressure field suffers due to a small domain size; however, the surface pressures estimates fare much better. The far-field estimation contains similar frequency content with reduced magnitudes, attributed to the exclusion of the viscous forces in Curle's analogy. In the absence of added noise, the estimation procedure performs quite nicely for this model problem. The method is tested experimentally on a 650,000 chord-Reynolds-number flow over a 2-D, 20% thick, elliptic circulation control airfoil. Slot jet momentum coefficients of 0 and 0.10 are investigated. Particle image velocimetry, unsteady pressure and phased-acoustic-array data are acquired simultaneously in an aeroacoustic wind-tunnel facility. The velocity field estimation suffers due to poor correlation with the unsteady pressure data, especially in the 0.10 momentum coefficient case. The prediction without slot jet blowing matches single microphone measurements within 0-10 dB over the frequency range of interest while the prediction with the jet active is quite poor and differ from measurements by as much as 35 dB. Suggestions for improvement of the proposed method are offered.;Data from the acoustic array are then investigated. Single microphone spectra are obtained, and it is shown that background noise is significant. In order to circumvent this problem, beamforming is employed. The primary sources of background noise are from the tunnel collector and jet/sidewall interaction. DAMAS is employed to remove the effects of the array point spread function. Spectra are acquired by integrating the DAMAS result over the source region. The resulting DAMAS spectral levels are significantly below single microphone levels. A scaling analysis is performed on the processed array data. With a constant free-stream velocity and a varying jet velocity the data scale as ;6;7
机译:水下航行器由于操作速度低而使用传统的起重附件降低了机动性。循环控制提供了一种独立于车速来提高机动性的方法。然而,伴随循环控制而来的还有其他噪声源,人们对此不太了解。为了更好地理解这些噪声源,开发了一种基于模态的预测方法,可能在流动结构和远场噪声之间提供定量连接。该方法仅使用非时间分辨的速度场和时间分辨的探头测量值来估算速度场,表面压力场​​和远场噪声。适当的正交分解,线性随机估计和卡尔曼平滑可用于估计时间分辨速度场。泊松方程用于根据速度计算时间分辨的压力场。然后使用Curle的类比将表面压力传播到远场。该方法是基于对低雷诺数(150)的二维圆柱体的直接数值模拟而开发的。由于通过仿真还可以知道每个要估计的字段,因此提供了一种通过使用该方法获得误差的方法。当模拟附加测量噪声较低时,速度估计和模拟速度匹配良好。压力场由于域尺寸小而受到影响;但是,表面压力估计要好得多。远场估计包含相似的频率内容,但幅度减小,这是由于在Curle的类比中排除了粘性力。在没有增加噪声的情况下,此模型问题的估计过程非常好。该方法在250,000厚的2D椭圆循环控制机翼上的650,000弦-雷诺数流上进行了实验测试。研究了狭缝射流动量系数0和0.10。粒子图像测速,不稳定压力和相声阵列数据是在空气声风洞设施中同时获取的。速度场估计由于与不稳定压力数据的相关性较差而受到影响,尤其是在动量系数为0.10的情况下。没有缝隙喷射吹气的预测会在感兴趣的频率范围内匹配0-10 dB内的单个麦克风测量值,而具有喷射有源的预测效果很差,与测量值相差多达35 dB。提出了改进方法的建议。然后研究了声阵列数据。获得了单个麦克风频谱,并且表明背景噪声是显着的。为了避免这个问题,采用了波束成形。背景噪声的主要来源来自隧道收集器和射流/侧壁相互作用。 DAMAS用于消除阵列点扩展功能的影响。通过对源区域上的DAMAS结果进行积分来获取光谱。最终的DAMAS频谱水平大大低于单个麦克风水平。对处理后的阵列数据执行缩放分析。在恒定的自由流速度和变化的射流速度下,数据比例为; 6; 7

著录项

  • 作者

    Reger, Robert W.;

  • 作者单位

    The Florida State University.;

  • 授予单位 The Florida State University.;
  • 学科 Aerospace engineering.;Engineering.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 179 p.
  • 总页数 179
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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