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Modeling supersonic heated jet noise at fixed jet Mach number using an asymptotic approach for the acoustic analogy Green's function and an optimized turbulence model

机译:使用渐近方法为声学类比格林函数和优化的湍流模型模拟固定速度马赫数下的超声加热射流噪声

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In this study we show how accurate jet noise predictions can be achieved within Goldstein's generalized acoustic analogy formulation for heated and un-heated supersonic jets using a previously developed asymptotic theory for the adjoint vector Green's function and a turbulence model whose independent parameters are determined using an optimization algorithm . In this approach, mean flow non-parallelism enters the lowest order dominant balance producing enhanced amplification at low frequencies, which we believe corresponds to the peak sound at small polar observation angles. The novel aspect of this paper is that we exploit both mean flow and turbulence structure from existent Large Eddy Simulations database of two axi-symmetric round jets at fixed jet Mach number and different nozzle temperature ratios to show (broadly speaking) the efficacy of the asymptotic approach. The empirical parameters that enter via local turbulence length scales within the algebraic-exponential turbulence model are determined by optimizing against near field turbulence data post-processed from the LES calculation. Our results indicate that accurate jet noise predictions are obtained with this approach up to a Strouhal number of 0.5 for both jets without introducing significant empiricism.
机译:在这项研究中,我们展示了如何使用先前开发的伴随向量格林函数渐近理论和湍流模型(其独立参数是通过使用优化算法。在这种方法中,平均流量非平行度进入最低阶的显性平衡,从而在低频下产生增强的放大,我们认为这对应于在较小的极地观察角处的峰值声音。本文的新颖之处在于,我们利用固定轴流马赫数和不同喷嘴温度比的两个轴对称圆形射流的现有大型涡模拟数据库,利用均流和湍流结构来显示(广义上)渐近线的功效方法。通过针对从LES计算后处理的近场湍流数据进行优化,可以确定通过代数指数湍流模型内的局部湍流长度尺度输入的经验参数。我们的结果表明,使用这种方法可以获得准确的射流噪声预测,两种射流的斯特劳哈尔数最高为0.5,而不会引入明显的经验。

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