A direct numerical simulation (DNS) of a plane wall jet is performed at a Reynolds number of $Re_{j}=7500$. The streamwise length of the domain is long enough to achieve self-similarity for the mean flow and the Reynolds shear stress. This is the highest Reynolds number wall jet DNS for a large domain achieved to date. The high resolution simulation reveals the unsteady flow field in great detail and shows the transition process in the outer shear layer and inner boundary layer. Mean flow parameters of maximum velocity decay, wall shear stress, friction coefficient and jet spreading rate are consistent with several other studies reported in the literature. Mean flow, Reynolds normal and shear stress profiles are presented with various scalings, revealing the self-similar behaviour of the wall jet. The Reynolds normal stresses do not show complete similarity for the given Reynolds number and domain length. Previously published inner layer budgets based on LES are inaccurate and those that have been measured are only available in the outer layer. The current DNS provides fully balanced, explicitly calculated budgets for the turbulence kinetic energy, Reynolds normal stresses and Reynolds shear stress in both the inner and outer layers. The budgets are scaled with inner and outer variables. The inner-scaled budgets in the near wall region show great similarity with turbulent boundary layers. The only remarkable difference is for the turbulent diffusion in the wall-normal Reynolds stress and Reynolds shear stress budgets. The outer layer interacts with the inner layer through turbulent diffusion and the excess energy from the wall-normal direction is transferred to the spanwise direction.
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Flows throughout different zones of turbines have been investigated using large eddy simulation (LES) and hybrid Reynolds-averaged Navier–Stokes-LES (RANS-LES) methods and contrasted with RANS modeling, which is more typically used in the design environment. The studied cases include low and high-pressure turbine cascades, real surface roughness effects, internal cooling ducts, trailing edge cut-backs, and labyrinth and rim seals. Evidence is presented that shows that LES and hybrid RANS-LES produces higher quality data than RANS/URANS for a wide range of flows. The higher level of physics that is resolved allows for greater flow physics insight, which is valuable for improving designs and refining lower order models. Turbine zones are categorized by flow type to assist in choosing the appropriate eddy resolving method and to estimate the computational cost.
The major techniques for measuring jet noise have significant drawbacks, especially when including engine installation effects such as jet–flap interaction noise. Numerical methods including low order correlations and Reynolds-averaged Navier–Stokes (RANS) are known to be deficient for complex configurations and even simple jet flows. Using high fidelity numerical methods such as large eddy simulation (LES) allows conditions to be carefully controlled and quantified. LES methods are more practical and affordable than experimental campaigns. The potential to use LES methods to predict noise, identify noise risks, and thus modify designs before an engine or aircraft is built is a possibility in the near future. This is particularly true for applications at lower Reynolds numbers such as jet noise of business jets and jet-flap interaction noise for under-wing engine installations. Hence, we introduce our current approaches to predicting jet noise reliably and contrast the cost of RANS–numerical-LES (RANS–NLES) with traditional methods. Our own predictions and existing literature are used to provide a current guide, encompassing numerical aspects, meshing, and acoustics processing. Other approaches are also briefly considered. We also tackle the crucial issues of how codes can be validated and verified for acoustics and how LES-based methods can be introduced into industry. We consider that hybrid RANS–(N)LES is now of use to industry and contrast costs, indicating the clear advantages of eddy resolving methods.
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