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Simulation and Modeling of Hypersonic Turbulent Boundary Layers Subject to Favorable Pressure Gradients due to Streamline Curvature

机译:超声波湍流边界层对良好压力梯度引起的仿真和建模

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Direct numerical simulations (DNS) of favorable-pressure-gradient turbulent boundary layers are presented for a nominal freestream Mach number of 5, with the objective of assessing the limitations of the currently available Reynolds-averaged Navier-Stokes (RANS) models. The favorable pressure gradient is induced by the streamwise curvature of the two-dimensional, planar, convex measurement surface used during experiments at the Texas A&M University. The DNS data shows good comparison with the measured velocity profiles, strain rates, and some, but not all, of the Reynolds-stress components. The discrepancies between the predicted and the measured wall-normal as well as shear stress components are primarily attributed to the lower than actual values inferred from typical PIV measurements of turbulent boundary layers. The DNS data shows a zero or slightly negative Reynolds shear stress in the outer part of the boundary-layer, which is indicative of the decaying turbulent motion under a strong favorable pressure gradient. The DNS data is also compared with the results of RANS computations based on commonly used zero, one, and two equation eddy-viscosity models. The RANS models yield reasonable comparisons with the DNS-based skin friction under zero and weak pressure gradients, but significant discrepancies under a strong pressure gradient. The k-ω SST model provided the best overall predictions of skin friction, except in the region where the flow transitions from a favorable to an adverse pressure gradient. While the RANS models examined herein also give good predictions of the Reynolds shear stress under a sufficiently weak pressure gradient, none of those models are able to appropriately capture the reduction in the Reynolds stresses when the flow was subjected to a strong pressure gradient. An a priori assessment of the turbulent heat-flux prediction based on the assumption of a constant turbulent Prandtl number with the DNS data shows that while the constant turbulent Prandtl number model is effective in predicting the wall-normal component of turbulent heat flux, it does not capture the turbulent heat transfer in the streamwise direction for all the pressure gradient cases. The failure of the constant turbulent Prandtl number model highlights a requirement for more advanced models of the turbulent heat flux.
机译:有利 - 压力梯度湍流边界层的直接数值模拟(DNS)呈现出名义的FreeStream Mach数量5,其目的是评估当前可用的雷诺平均天Navier-Stokes(RAN)模型的限制。通过在德克萨斯A&M大学的实验期间使用的二维平面,凸的测量表面的流动曲率诱导了有利的压力梯度。 DNS数据与测量的速度分布,应变率和一些但不是全部,雷诺应力组件的良好比较。预测和测量的壁正常以及剪切应力分量之间的差异主要归因于从湍流边界层的典型PIV测量推断的低于实际值。 DNS数据在边界层的外部示出了零或略微负雷诺剪切应力,其指示在强良好的压力梯度下的衰减湍流运动。还将DNS数据与基于常用的零,一个和两个等式辅助粘度模型的RAN计算结果进行了比较。 RAN模型在零和弱压力梯度下与基于DNS的皮肤摩擦产生合理的比较,但在强大的压力梯度下具有显着的差异。 K-ωSST模型提供了皮肤摩擦的最佳总体预测,除了在流动从良好的不利压力梯度转变的区域中。虽然这里检查的RAN模型还给出了在足够弱的压力梯度下对雷诺剪切应力的良好预测,但是当流动经受强烈的压力梯度时,这些模型都没有适当地捕获雷诺应力的减小。基于DNS数据的恒定湍流PRANDTL号的假设是基于恒定湍流普朗特数的先验评估,虽然恒定的湍流PRANDTL号码模型可有效地预测湍流热通量的壁正常成分,但它确实如此对于所有压力梯度案例,不捕获流动方向上的湍流传热。恒定湍流普朗特数模型的失败突出了对湍流热通量更先进模型的要求。

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