One of the main challenges in simulating high Reynolds number (Re) turbulent boundary layers (TBLs) is the long streamwise distance required for large scale outer-layer structures to develop, making such simulations prohibitively expensive. We propose an inflow generation method for high Re wall turbulence that leverages the known structure and scaling laws of TBLs. Enabling shorter development lengths by providing rich input information. As observed from the inner-scaled pre-multiplied spectra of streamwise velocity, with an increase in Re the outer region grows or occupies more of the spanwise wavenumber space inproportion to the increase in Re; while the inner region remains approximately the same. Exploiting this behavior, we generate high-Re inflow conditions for a target Re by starting from cross-stream velocity slices at a lower base Re. In spectral space, we identify the inner and outer region wavenumbers, and shift the outer-region components proportionally to the desired Re increase. We closely examine the capability of this method by scaling a set of velocity slices at Reθ = 2240 and 4430 to Reθ = 8000, and using them as inflow conditionsfor direct numerical simulations (DNS) of spatially developing TBLs growingfrom Reθ = 8000 − 9000. Skin friction coefficient and shape factor predicted bythe new method, regardless of the base Re tested, is within ±3.5% and ±0.5% respectively of that of a precursor simulation right from the inlet. Reynolds stresses match very well after ≈ 8 δ990 . This gives an order of magnitude reduction in development length compared to other methods in literature.

This study introduces vector autoregression (VAR) as a linear procedure that can be used for synthesizing turbulence time series over an entire plane, allowing them to be imposed as an efficient turbulent inflow condition in simulations requiring stationary and cross-correlated turbulence time series. VAR is a statistical tool for modelling and prediction of multivariate time series through capturing linear correlations between multiple time series. A Fourier-based proper orthogonal decomposition (POD) is performed on the two-dimensional (2-D) velocity slices from a precursor simulation of a turbulent boundary layer at a momentum thickness-based Reynolds number, Re-theta=790. A subset of the most energetic structures in space are then extracted, followed by applying a VAR model to their complex time coefficients. It is observed that VAR models constructed using time coefficients of 5 and 30 most energetic POD modes per wavenumber (corresponding to 66% and 97% of turbulent kinetic energy, respectively) are able to make accurate predictions of the evolution of the velocity field at Re-theta=790 for infinite time. Moreover, the 2-D velocity fields from the POD-VAR when used as a turbulent inflow condition, gave a short development distance when compared with other common inflow methods. Since the VAR model can produce an infinite number of velocity planes in time, this enables reaching statistical stationarity without having to run an extremely long precursor simulation or applying ad hoc methods such as periodic time series.

A scale-resolving simulation of a turbulent boundary layer (TBL) requires an inflow condition that introduces turbulence into the domain. The boundary values must accurately approximate real turbulent structures in order to allow for sustained growth of the TBL. In practice, all inflow conditions incur an error on the flow field directly downstream. This error is typically quantified as the distance from the inlet at which the velocity statistics recover correct values.However, this measure is insufficient for simulations where evaluating acoustic pressure is an important outcome, necessitating a quantification of the error in the pressure field. This aspect of inflow generation is currently not addressed in the literature and constitutes the main topic of this article. In particular, we look at three known inflow boundary conditions (namely precursor, the synthetic eddy method, and recycling using an upstream open channel) and evaluate how silent they are. For this, the sensitive case of a TBL developing over a flat plate is used as the test case. The main outcome is that using the recycling method introduces the least amount of numerical noise to the sound field while giving reasonably good agreement in terms of the overall developmentof the TBL.

Modern computing clusters offer specialized hardware for reduced-precision arithmetic that can speed up the time to solution significantly. This is possible due to a decrease in data movement, as well as the ability to perform arithmetic operations at a faster rate. However, for high-fidelity simulations of turbulence,such as direct and large-eddy simulation, the impact of reduced precision on the computed solution and the resulting uncertainty across flow solvers and different flow cases have not been explored in detail and limits the optimal utilization of new high-performance computing systems. In this work, the effect of reduced precision is studied using four diverse computational fluid dynamics (CFD) solvers (two incompressible, Neko and Simson, and two compressible, PadeLibs and SSDC) using four test cases: turbulent channel flow at Reτ = 550 and higher, forced transition in a channel, flow over a cylinder at ReD = 3900, and compressible flow over a wing section at Rec = 50000. We observe that the flow physics are remarkably robust with respect to reduction in lower floating-point precision, and that often other forms of uncertainty, due to for example time averaging, often have a much larger impact on the computed result. Our results indicate that different terms in the Navier–Stokes equations can be computed to a lower floating-point accuracy without affecting the results. In particular,standard IEEE single precision can be used effectively for the entirety of the simulation, showing no significant discrepancies from double-precision results across the solvers and cases considered. Potential pitfalls are also discussed.

The development of a three-dimensional (3D) turbulent boundary layer over the Boeing speed bump is studied by infinitely sweeping the leading edge—thereby introducing a cross-flow component. While several numerical studies have looked at two-dimensional turbulent boundary layers over the bump, the current work corresponds closer to wings in practice, while retaining the simplicity of centerslice of the geometry. For validation, the unswept bump is also simulated, and time series data at different streamwise stations of cross-stream planes are usedto compute pre-multiplied spanwise spectra and linear coherence spectra. The linear coherence spectra revealed the potential influence of the wind tunnel topwall and/or a combination with minute inconsistencies in the inflow condition that can enhance the wall-normal coherence between the near-wall and outerregion of the boundary layer. The examination of pre-multiplied spectra shows the boundary layer development in a new light while hinting at the narrow width of the domain usually preferred for the Boeing bump simulations. Comparisons are then made between the swept and unswept configurations in terms of the development of the boundary layer and introduction of sweep causing the streamlines to curve. As seen in other experiments over swept surfaces, sweeping reduces the skin friction over the bump. The skin friction of the swept bump also did not show the second peak in skin friction observed for the unswept bump. In addition, the swept bump does not suffer incipient separation in the streamwise direction unlike the unswept bump.

Rotors play a major role in various applications including ventilation and propulsion systems such as in helicopters, drones, gas turbines, wind turbines and many more. This visualization of instantaneous vortical structures (identified by the λ2 criterion) shows complex flow structures emanating from a twisted drone rotor that is impulsively starting to rotate at 1600 rpm. Initially, a starting vortex is formed as a result of lift generation and shed as a connected vortex tube from the entire surface of the blade, which has a strong connection to the blade tip via the so-called tip vortex. Leading-edge separation occurs at span positions of high twist, followed by wave-induced breakdown to turbulence along the whole wing span. This turbulence then sheds as small-scale vortices into the wake and dissipates. Understanding the behaviour of these vortices from such complex blades and how they interact with the other blade is critical to design more efficient and potentially more silent propellers.