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Stochastic modelling of leading-edge noise in time-domain using vortex particles
Journal of Sound and Vibration ( IF 4.3 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.jsv.2020.115656
Sparsh Sharma , Ennes Sarradj , Heiko Schmidt

Abstract The interaction of a wing/blade profile with turbulent inflow is one of the main sources of sound generation in turbomachines. There are already several noise prediction methodologies available which either appear not to account for the influence of geometrical and flow parameters on noise generation or have been able to account for a remarkably limited extent due to the requirement of high-performance computing for flow calculations. This leads to the motivation of the current paper, which presents a low-cost and easy-to-use noise prediction methodology based on the statistical modelling of the inflow turbulence and Lookup Table (LUT) approach for aeroacoustic design and optimisation. The development of the statistical method is divided into three parts; namely – i) calculating the background flow, ii) modelling of statistically optimised inflow disturbance, iii) computing the far-field sound pressure for individual vortex passages and superpose them linearly – this step involves repeated computation of identical vortex passages and can be therefore easily sped up using a database approach. In the framework of this work, a new approach to model the inflow turbulence using vortex particles characterised by shape functions, based on waveforms, is presented. The idea is to not conduct a time-dependent unsteady calculation of the flow field in real-time, instead to consider the mean flow around the profile in the computational domain, in which the vortex particles are convected to realise a statistical turbulent signal. The convection of these vortex particles, also, does not take place in the real-time calculation, instead, vortices of every possible size and strength are convected in a similar domain with a specific airfoil, and the acoustic radiation due to their interaction with the airfoil are computed and stored in a database. The far-field noise is predicted using Curle’s formulation. The generated database is accessed using the LUT approach to rapidly extract the acoustic signals. Through this approach, the influence of geometrical as well as flow parameters on the noise generated by airfoils can be quantified without requiring to conduct a numerical simulation every time for a new set of geometrical and flow variables. In the article, the application of the method for different blade profiles is shown, and the results obtained are compared with the standard literature.

中文翻译:

使用涡流粒子对时域前沿噪声进行随机建模

摘要 机翼/叶片轮廓与湍流流入的相互作用是涡轮机中产生声音的主要来源之一。已经有几种可用的噪声预测方法,它们要么似乎没有考虑几何参数和流动参数对噪声产生的影响,要么由于对流量计算的高性能计算的要求而能够考虑到非常有限的程度。这导致了当前论文的动机,该论文基于流入湍流和查找表 (LUT) 方法的统计建模,提出了一种低成本且易于使用的噪声预测方法,用于气动声学设计和优化。统计方法的发展分为三个部分;即 – i) 计算背景流量,ii) 统计优化流入扰动的建模,iii) 计算单个涡流通道的远场声压并将它们线性叠加 - 此步骤涉及重复计算相同的涡流通道,因此可以使用数据库方法轻松加速。在这项工作的框架内,提出了一种基于波形使用以形状函数为特征的涡流粒子来模拟流入湍流的新方法。其思想是不实时对流场进行时间相关的非定常计算,而是在计算域中考虑轮廓周围的平均流动,其中涡流粒子对流以实现统计湍流信号。这些涡流粒子的对流,也不会在实时计算中发生,相反,各种可能大小和强度的涡流在具有特定翼型的类似域中对流,并且由于它们与翼型相互作用而产生的声辐射被计算并存储在数据库中。使用 Curle 公式预测远场噪声。使用 LUT 方法访问生成的数据库以快速提取声学信号。通过这种方法,可以量化几何参数和流动参数对翼型产生的噪声的影响,而无需每次都对一组新的几何和流动变量进行数值模拟。文中展示了该方法在不同叶片型面下的应用,并将所得结果与标准文献进行了比较。并且由于它们与翼型的相互作用而产生的声辐射被计算并存储在数据库中。使用 Curle 公式预测远场噪声。使用 LUT 方法访问生成的数据库以快速提取声学信号。通过这种方法,可以量化几何参数和流动参数对翼型产生的噪声的影响,而无需每次都对一组新的几何和流动变量进行数值模拟。文中展示了该方法在不同叶片型面下的应用,并将所得结果与标准文献进行了比较。并且由于它们与翼型的相互作用而产生的声辐射被计算并存储在数据库中。使用 Curle 公式预测远场噪声。使用 LUT 方法访问生成的数据库以快速提取声学信号。通过这种方法,可以量化几何参数和流动参数对翼型产生的噪声的影响,而无需每次都对一组新的几何和流动变量进行数值模拟。文中展示了该方法在不同叶片型面下的应用,并将所得结果与标准文献进行了比较。使用 LUT 方法访问生成的数据库以快速提取声学信号。通过这种方法,可以量化几何参数和流动参数对翼型产生的噪声的影响,而无需每次都对一组新的几何和流动变量进行数值模拟。文中展示了该方法在不同叶片型面下的应用,并将所得结果与标准文献进行了比较。使用 LUT 方法访问生成的数据库以快速提取声学信号。通过这种方法,可以量化几何参数和流动参数对翼型产生的噪声的影响,而无需每次都对一组新的几何和流动变量进行数值模拟。文中展示了该方法在不同叶片型面下的应用,并将所得结果与标准文献进行了比较。
更新日期:2020-12-01
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