Abstract

The single-expansion ramp nozzle (SERN) is intensely over-expanded and leads to a large separation zone. The flow separation is the central phenomenon causing a reduction in thrust, and shock waves lead to a drop in the flow stagnation pressure and increase the energy loss. In this study, the unsteady compressible flow in a SERN was studied by employing the k-kl-ω transition turbulence model with high ability in separation flow prediction. In this regard, the finite volume code with the pressure-implicit with the splitting of operators algorithm and the adaptive mesh refinement technique were applied. Firstly, the results were compared with published data and it is revealed that the numerical methodology was capable of detecting the exact structure of lambda shock and wall pressure. Then, the influences of harmonic inlet and outlet conditions were evaluated on the flow behavior. The results showed that for harmonic inlet pressure conditions the value of friction coefficient in the case with wavelength of 0.3 is greater than the cases with the wavelength of 0.15 and 0.6. Also, it is found that the shock train did not form for the case with wavelength of 0.6. Furthermore, for the harmonic condition in outlet pressure, the minimum wall shear stress was obtained for the case with the wavelength of 015, and the shock strength, in this case, is more than the cases with wavelength of 0.6 and 0.3.

摘要

单膨胀斜坡喷嘴 (SERN) 过度膨胀并导致大的分离区。流动分离是导致推力减小的中心现象，激波导致流动驻点压力下降并增加能量损失。在这项研究中，通过使用k - kl - ω研究了 SERN 中的不稳定可压缩流具有高分离流动预测能力的转捩湍流模型。在这方面，应用了具有压力隐式的有限体积代码和算子分裂算法以及自适应网格细化技术。首先，将结果与已发表的数据进行比较，结果表明该数值方法能够检测 lambda 激波和壁面压力的确切结构。然后，评估了谐波入口和出口条件对流动行为的影响。结果表明，对于谐波入口压力条件，摩擦系数值在波长为 0.3 的情况下大于波长为 0.15 和 0.6 的情况。此外，发现对于波长为 0.6 的情况，激波列没有形成。此外，