贯流风扇气动声场数值模拟及分析

针对贯流风扇气动噪声传播特性,采用基于非结构网格的CE/SE算法对其气动流场进行数值模拟,并模拟了气动噪声的传播.湍流模拟采用大涡模型,搭接式滑移网格模型处理动静干涉.噪声传播采用完全欧拉方程作为控制方程,远场采用无反射边界条件.将使用该方法得到的远场噪声频谱与实验数据进行对比分析,结果表明与实验测量得到宽带频谱不同,采用大涡模拟湍流模型进行声源模拟时,会加强部分离散频率上的声级,从而产生误差.     

基于SNGR方法的后缘噪声数值模拟

采用随机噪声产生和传播(SNGR)方法对后缘噪声进行数值模拟.SNGR方法结合随机方法和计算流体力学,耗费较少的计算资源就可以预测噪声水平.数值模拟时采用有限体积法求解雷诺平均Navier-Stokes(RANS)方程;采用有限差分法求解声学扰动方程,数值格式采用色散关系保持(DRP)格式,远场边界条件采用无反射边界条件.以二维平板和NACA0012翼型为例,编制程序,与参考结果对比表明,程序可以预测后缘噪声.     

快速随机粒子网格法的气动噪声预测方法

耦合随机湍流速度生成模型与线化欧拉方程技术,形成了一套具备模拟噪声在非均匀流场中传播能力的气动噪声混合预测方法。该混合方法的随机湍流速度生成模型采用了快速随机粒子网格法,为声传播模拟提供了可靠的源项。而噪声的传播计算选用线化欧拉方程,其空间离散采用9点5阶的色散保持关系格式,时间推进选用了高精度大时间步长的6级4阶龙格库塔格式,远场边界应用了无分裂形式的理想匹配层边界条件。首先,选用高斯脉冲传播算例对线化欧拉方程的时空离散格式、远场无反射边界条件进行了验证分析。然后,计算分析各向同性湍流的空间相关性验证湍流速度生成模型的可靠性。最后,基于已搭建的气动噪声混合预测方法进行了30P30N三段翼缝翼噪声的计算分析。计算分析可知:监测点处功率谱密度曲线、噪声指向性等计算结果与参考文献结果取得了较好的一致性。数值计算结果表明所建立的气动噪声混合预测方法能有效预测二维复杂构型的气动噪声问题。     

轴对称射流气动声场的数值模拟

构造了Kirchhoff积分和CFD计算相结合的算法,采用高精度差分格式对不同喷口马赫数的轴对称射流进行数值模拟,并以此作为近场声源,运用Kirchhoff积分方法研究远场气动噪声.数值结果表明,远场噪声具有方向性,噪声声压在离开对称轴20°处达到最大值.随着传播距离增大,噪声方向性逐渐减弱.     

汽车涡轮增压器同步谐波噪声仿真与优化

针对增压发动机急加速急减速时产生的增压器同步谐波噪声问题,该文通过噪声仿真技术进行分析与优化.首先,分析该噪声的特征与传播路径;其次,建立流场仿真模型.利用剪切应力输运湍流模型与分离涡流模拟湍流模型对增压器进行稳态与非稳态瞬态流场分析,提取非稳态流场的叶轮与压气机流道表面的偶极子声源;最后,建立噪声传播模型,计算该增压...     

环境风对高速列车气动噪声特性的影响分析

气动噪声随着列车运行速度的提高急剧增加,是高速列车噪声的重要组成部分。本文使用缩比为1:20的三车编组模型,通过三维瞬态延迟分离涡模型求解高速列车的外流场,分析了环境风对流场结构与声源特性的影响;之后使用FW-H方程进行噪声传播计算,分析了不同速度的环境风对高速列车气动声学行为特性的影响。结果表明：高速列车主要的噪声源分布在转向架附近,在环境风的影响下,列车背风侧声源强度高于迎风侧,列车底部声源强度增幅较大。10 m/s以内的环境风会改变高速列车在尾流区域的声学指向性,并使气动噪声增加2.1~8.7 dB。相关结论可以为高速列车气动声学设计等研究提供参考。     

井孔中多极源在分层介质的声场模拟方法*

水平分层地层是常见的地质模型,为了获得地下水平分层介质中声波测井的响应并了解声波在其中的传播规律,需要对该模型进行声场数值模拟,通常采用基于时域有限差分的数值模拟方法。然而对于地下数百米井段的声场模拟,如何最大化地减小数值模拟的计算区域,提高计算速度和节省内存,是必须考虑的策略问题。本文中,我们提出了动态计算区域的仿真策略,给出了计算区域选取的优化方案,并通过算例验证策略的有效性。假设发射器分布在阵列接收器下方,模拟结果表明,当声源距离下方最近的分层边界超过2米时,位于仪器下方的所有分层介质可以在计算中忽略不计。对于位于阵列接收器上方的分层边界,在选取计算区域时,也同样采用类似的策略。利用这样的策略,我们连续快速模拟了多层介质中单极子和偶极子声波测井响应,其中纵波和横波速度提取结果与输入的连续分层介质参数吻合。应用这种策略,可开发出数百米甚至数千米的井孔声场连续快速仿真的数值模拟软件。     

炉内管阵列中声源辐射特性数值研究

炉内换热器结构类似于声子晶体,基于声子晶体理论,采用数值计算与软件模拟得到管阵列中声源不同方向的声传播特性,并将两种方法所得结果进行对比分析,研究声源在管阵列中不同位置处的辐射特性.结果表明：声指向性特性与声源通过管排数量,声源频率是否处在声波禁带有关.     

陆架斜坡海域上坡波导环境中声能量急剧下降现象及其定量分析

深度较浅的声源其辐射声波在陆架斜坡海域上坡传播时,在斜坡顶端会出现声能量急剧下降现象.利用射线声学模型分析了造成这一现象的原因,并根据抛物方程声场模型计算的深海和浅海平均传播损失定义了"声能量急剧下降距离",定量分析了声源位置对该现象的影响.结果表明:声源深度对"声能量急剧下降距离"影响较大,而声源与斜坡底端水平距离对其影响较小;当声源深度变大时,部分掠射角较小的声线最终能够达到斜坡顶端,致使"声能量急剧下降距离"增大,继续增加声源深度,将导致上坡声能量急剧下降现象消失.利用抛物方程声场模型对陆架斜坡海域上坡声传播进行数值仿真,结合"声能量急剧下降距离"的定义,计算并比较了声源位置不同时该距离的变化,数值计算结果验证了理论分析.     

运动声源简正波模型稳相点的射线多普勒近似算法

从航空声源水下声场建模出发,提出了运动声源稳相点的近似算法。由于Hawker给出的运动声源声场简正波模型计算方法不适用于高速运动声源,针对速度相对较大的低空运动声源辐射噪声激发的水下声场建模,采用虚源概念,基于射线声学理论得到近似多普勒频率,结合简正波理论求解稳相点,较好地解决了高速运动声源声场的解算问题。几种波导环境下两种方法数值计算比较结果表明该算法的有效性。     

Slat noise modeling and prediction

This paper presents a model for aircraft slat noise prediction, based on the theory of aerodynamic sound generation and the first principles of source flow physics. Starting from the theory of acoustic analogy, the noise from the high Reynolds number and low Mach number flows in the slat cove region is formulated as a general solution by the method of dimensional analysis, far-field asymptotic expansion and statistical modeling. The solution relates the far-field noise spectrum to the surface pressure statistics, the characteristic length and time scales in the surface pressure statistics and Green's function that accounts for the sound-flow coupling and propagation effects. The general solution is then used to extract scaling laws and correlation models for the individual functional dependences between the far-field noise and various parameters, including the slat noise spectral shape, its Mach number dependence and its far-field directivity. The simple scaling laws and correlation models are validated by test data and serve as building blocks to construct a slat noise prediction model.     

Prediction of Outdoor Noise Propagation Induced By Single-Phase Power Transformers

Outdoor power transformers are one of the most pervasive noise sources in power transmission and distribution systems. Accurate prediction of outdoor noise propagation plays a dominant role for the evaluation and control of noise relevant to the transformer stations. In this paper surface vibration tests are carried out on a scale model of a single-phase transformer tank wall at different excitation frequencies. The phase and amplitude of test data are found to be randomly distributed when the excitation frequency exceeds the seventh mode frequency, which allows the single-phase power transformer to be simplified as incoherent point sources. An outdoor-coherent model is subsequently developed and incorporated with the image source method to investigate noise propagation from single-phase power transformers, due to the occurrence of multiple reflections and diffractions in the propagation path of each point source. The proposed model is used to calculate the sound field of the power transformer group by exploiting the additional phase information. In comparison with the ISO9613 model and the boundary element method, it is found that the proposed coherent image source method leads to more accurate prediction results, and hence better performance for the prediction of the outdoor noise induced by single-phase power transformers.     

Multiple pure tone noise prediction

This paper presents a fully numerical method for predicting multiple pure tones, also known as “Buzzsaw” noise. It consists of three steps that account for noise source generation, nonlinear acoustic propagation with hard as well as lined walls inside the nacelle, and linear acoustic propagation outside the engine. Noise generation is modeled by steady, part-annulus computational fluid dynamics (CFD) simulations. A linear superposition algorithm is used to construct full-annulus shock/pressure pattern just upstream of the fan from part-annulus CFD results. Nonlinear wave propagation is carried out inside the duct using a pseudo-two-dimensional solution of Burgers? equation. Scattering from nacelle lip as well as radiation to farfield is performed using the commercial solver ACTRAN/TM. The proposed prediction process is verified by comparing against full-annulus CFD simulations as well as against static engine test data for a typical high bypass ratio aircraft engine with hardwall as well as lined inlets. Comparisons are drawn against nacelle unsteady pressure transducer measurements at two axial locations as well as against near- and far-field microphone array measurements outside the duct.     

机体表面湍流边界层噪声特性及预测方法研究

湍流边界层噪声是飞机巡航过程中的主要外部噪声源,对舱内噪声水平的影响尤为重要。因此,对飞机机体表面湍流边界层噪声的研究具有重要意义。本文通过试验获得了某型民机巡航过程中的湍流边界层噪声,试飞工况为3500ft/0.78、3500ft/0.7、2500ft/0.67、1500ft/0.66。对实测数据进行分析,发现湍流边界层噪声与动压、边界层厚度等参数有关。同时,利用计算流体力学的方法得到了飞机机体表面的压力分布,并分析了压力梯度对湍流边界层噪声的影响。最后,基于工程预测方法对湍流边界层噪声进行了预测,对于不存在逆压梯度的区域,预测结果与试验结果吻合较好,仅部分频段存在一定偏差。通过对模型的参数进行优化,改善了预测结果。     

Comparative Study of the Propagation of Jet Noise in Static and Flow Environments

In order to analyze the effect of the background flow on the sound prediction of fine-scale turbulence noise, the sound spectra from static and flow environments are compared. It turns out that, the two methods can obtain similar predictions not only at 90 deg to the jet axis but also at mid- and high frequencies in other directions. The discrepancies of predictions from the two environments show that the effect of the jet flow on the sound propagation is related to low frequencies in the downstream and upstream directions. It is noted that there is an obvious advantage of computational efficiency for calculating in static environment, compared with that in flow environment. A good agreement is also observed to some extent between the predictions in static environment and measurements of subsonic to supersonic. It is believed that the predictions in static environment could be an effective method to study the propagation of the sound in jet flow and to predict the fine scale turbulence noise accurately in a way as well.     

A robust super-resolution approach with sparsity constraint in acoustic imaging

Acoustic imaging is a standard technique for mapping acoustic source powers and positions from limited observations on microphone sensors, which often causes an ill-conditioned inverse problem. In this article, we firstly improve the forward model of acoustic power propagation by considering background noises at the sensor array, and the propagation uncertainty caused by wind tunnel effects. We then propose a robust super-resolution approach via sparsity constraint for acoustic imaging in strong background noises. The sparsity parameter is adaptively derived from the sparse distribution of source powers. The proposed approach can jointly reconstruct source powers and positions, as well as the background noise power. Our approach is compared with the conventional beamforming, deconvolution and sparse regularization methods by simulated, wind tunnel data and hybrid data respectively. It is feasible to apply the proposed approach for effectively mapping monopole sources in wind tunnel tests.     

Time-domain simulations of sound propagation through screen-induced turbulence

A flow model in combination with a statistical-dynamical turbulence generator and a linearised Euler time-domain model for sound waves were used to simulate the effect of screen-induced turbulence on the noise level in the acoustical shadow of a screen in wind. Instead of simulating a great number of different frozen turbulence realisations, the concept of transient turbulence was successfully tested and applied. This concept is adequate to the time-domain model and reduces the computational demands. Several two-dimensional simulations allowed to isolate the individual effects of wind and screen on the propagation of 500 Hz sound waves over a 4-m high noise barrier. At a distance of 250 m from the source (240 m behind the screen) the sheltering effect of the screen and the refraction effect of the wind are in the order of 6 and 4 dB, respectively. The screen-induced turbulence leads to fluctuations in the noise level with a standard deviation of 1.2 dB and a maximum amplitude of 3 dB. However, the time averaged effect turned out to be in the order of merely 0.2 dB. The effect of the screen-induced turbulence on the average noise level behind the screen is therefore negligible.