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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:用渐近方法对固定喷射Mach数进行建模超音速加热射流,用于声学比较绿色功能和优化的湍流模型

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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,我们展示了使用先前显影的渐近理论的加热和未加热的超声波喷射在Goldstein的广义声学模拟中可以实现精确的射流预测,用于使用预先开发的伴随矢量绿色的功能和使用独立参数确定的湍流模型的湍流模型优化算法。在这种方法中,平均流量无平行度进入在低频下产生增强放大的最低阶的主导平衡,我们认为我们认为对应于小极性观察角度的峰值声音。本文的新颖方面是,在固定喷射马赫数和不同喷嘴温度比的两个AXI对称圆形喷射器的存在的大型涡流模拟数据库中,我们利用平均流量和湍流结构。(广泛地说)渐近的效果方法。通过代数 - 指数湍流模型内通过局部湍流长度缩放的经验参数通过从LES计算后处理的近场湍流数据进行优化来确定。我们的结果表明,在不引入显着经验主义的情况下,使用这种方法可以获得精确的射流预测,其达到速度为0.5。

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