Study of Flow around a Trapezoidal Model of a Small-Sized UAV into Turbulent Wake

Investigations of the structure of the flow near the surface of a trapezoidal model of a small unmanned aerial vehicle were carried out when it enters a narrow turbulent wake. All experimental data were obtained in a wind tunnel at subsonic flow velocities. A feature of the work was that the study of the flow around the model was carried out at full-scale (flight) Reynolds numbers. Using the soot-oily visualization method, data on the features of the flow around the model were obtained, taking into account such factors as the angle of attack, the presence and absence of a source of external disturbances that generated a turbulent wake. The experiments were carried out in two flow regimes: at a zero angle of attack, when there are local separation bubbles on the wing, and at a large (supercritical) angle of attack of 18 degrees, when there is a global stall of the flow from the leading edge. It was shown that the turbulent wake has a significant effect on the nature of the flow near the model surface in both cases. Local separation bubbles gradually decrease in size with a decrease in the distance between the sources of disturbances and the wing. Large-scale vortices significantly decrease in geometrical dimensions and shift towards the side edges in the event of a global stall of the flow, thereby increasing the region of the attached flow on the model surface.

Electromagnetic Scattering of Near-Field Turbulent Wake Generated by Accelerated Propeller

The electromagnetic scattering study of the turbulent wake of a moving ship has important application value in target recognition and tracking. However, to date, there has been insufficient research into the electromagnetic characteristics of near-field propeller turbulence. This study presents a new procedure for evaluating the electromagnetic scattering coefficient and imaging characteristics of turbulent wakes in the near field. By controlling the different values of the net momenta, a turbulent wake was generated using the large-eddy simulation method. The results show that the net momentum transferred to the background flow field determines the development of the turbulent wake, which explains the formation mechanism of the turbulence. Combined with the turbulent energy attenuation spectrum, the electromagnetic scattering characteristics of the turbulent wake were calculated using the two-scale facet mode. Using this method, the impact of different parameters on the scattering coefficient and the electromagnetic image of the turbulence wake were investigated, to explain the modulation mechanism and electromagnetic imaging characteristics of the near-field turbulent wake. Moreover, an application for estimating a ship’s heading is proposed based on the electromagnetic imaging characteristics of the turbulent wake.

RANS-based design of experimental flow model for investigation of complex curved turbulent wakes subjected to adverse pressure gradient

Results are presented of a series of RANS computations aimed at creating a new experimental flow model of a curved turbulent wake evolving under adverse pressure gradient. In the course of the computations, key geometric parameters of the model (the angle of attack of a flat plate generating the wake and the shape and the angles of attack of liner foils creating the pressure gradient) were varied in a wide range. The purpose was to find the parameters ensuring desirable features of the flow, namely, a considerable wake curvature and its strong deceleration leading to formation of a large stagnation or even a reversal flow region, on the one hand, and no flow separation either from the flat plate or from the surfaces of the liner foils, on the other hand. As a result, the design satisfying all these demands has been found. This design will be implemented and studied in the framework of recently launched joint German-Russian project “Complex Wake Flows” which presents a continuation of an earlier similar project devoted to symmetric wakes.

Low-order modelling of the wake dynamics of an Ahmed body

We investigate the large-scale signature of the random switches between two mirrored turbulent wake states of flat-backed bodies. A direct numerical simulation (DNS) of the flow around an Ahmed body at a Reynolds number ( $Re$ ) of 10 000 is considered. Using proper orthogonal decomposition (POD), we identify the most energetic modes of the velocity field and build a low-dimensional model based on the first six fluctuating velocity modes capturing the characteristics of the flow dynamics during and between switches. In the absence of noise, the model produces random switches with characteristic time scales in agreement with the simulation and experiments. This chaotic model suggests that random switches are triggered by the increase of the vortex shedding activity. However, the addition of noise results in a better agreement in the temporal spectra of the coefficients between the model and the simulation.

In situ observations of turbulent ship wakes and their spatiotemporal extent

In areas of intensive ship traffic, ships pass every 10 min. Considering the amount of ship traffic and the predicted increase in global maritime trade, there is a need to consider all types of impacts shipping has on the marine environment. While the awareness about, and efforts to reduce, chemical pollution from ships is increasing, less is known about physical disturbances, and ship-induced turbulence has so far been completely neglected. To address the potential importance of ship-induced turbulence on, e.g., gas exchange, dispersion of pollutants, and biogeochemical processes, a characterisation of the temporal and spatial scales of the turbulent wake is needed. Currently, field measurements of turbulent wakes of real-size ships are lacking. This study addresses that gap by using two different methodological approaches: in situ and ex situ observations. For the in situ observations, a bottom-mounted acoustic Doppler current profiler (ADCP) was placed at 32 m depth below the shipping lane outside Gothenburg harbour. Both the acoustic backscatter from the air bubbles in the wake and the dissipation rate of turbulent kinetic energy were used to quantify the turbulent wake depth, intensity, and temporal longevity for 38 ship passages of differently sized ships. The results from the ADCP measurements show median wake depths of 13 m and several occasions of wakes reaching depths > 18 m, which is in the same depth range as the seasonal thermocline in the Baltic Sea. The temporal longevity of the observable part of the wakes had a median of around 10 min and several passages of > 20 min. In the ex situ approach, sea surface temperature was used as a proxy for the water mass affected by the turbulent wake (thermal wake), as lowered temperature in the ship wake indicates vertical mixing in a thermally stratified water column. Satellite images of the thermal infrared sensor (TIRS) onboard Landsat-8 were used to measure thermal wake width and length, in the highly frequented and thus major shipping lane north of Bornholm, Baltic Sea. Automatic information system (AIS) records from both the investigated areas were used to identify the ships inducing the wakes. The satellite analysis showed a median thermal wake length of 13.7 km (n=144), and the longest wake extended over 60 km, which would correspond to a temporal longevity of 1 h 42 min (for a ship speed of 20 kn). The median thermal wake width was 157.5 m. The measurements of the spatial and temporal scales are in line with previous studies, but the maximum turbulent wake depth (30.5 m) is deeper than previously reported. The results from this study, combined with the knowledge of regional high traffic densities, show that ship-induced turbulence occurs at temporal and spatial scales large enough to imply that this process should be considered when estimating environmental impacts from shipping in areas with intense ship traffic.

PIV Visualization of Flow Around Airfoil Controlled by Synthetic Jet Actuators at Shear-Layer and Wake Instability Frequencies

The response of a separated boundary layer to synthetic jet flow control at the global wake instability (F+ ≈ 𝒪(1)) and the shear-layer instability (F+ ≈ 𝒪(10)) measured by particle image velocimetry are presented. The visualization shows that in each of the control cases, coherent vorticity develops and breaks down into a turbulent wake. When the jets are actuated by burst-modulation at the wake instability frequency, they induce regular formation and detachment of large-scale vorticity to form a wide turbulent wake. Excitation at the shear-layer instability frequency, on the other hand, produces a train of alternating velocity fluctuations in the boundary layer which dissipate to a narrower wake. Proper orthogonal decomposition of the velocity fields show that the physical extent of the jet-induced coherent structures is decreased with increasing addition of momentum for both excitation frequencies.

Cascade With Sinusoidal Leading Edges: Identification And Quantification of Deflection With Unsupervised Machine Learning

One of the key issues in turbomachinery design is the identification of loss mechanisms and their quantification, both during preliminary design and in all subsequent optimization loops. Over the years, many correlations have been proposed, accounting for different dissipative mechanisms that occur in blade-to-blade passages, such as the development of boundary layers, turbulent wake mixing, shockwaves, and secondary flows or off-design incidence. In recent years, the fan industry started the production of more complex rotor geometries, characterized by sinusoidal leading and trailing edges, mostly to extend stall margin and to reduce noise emissions. Literature still lacks a quantification of the losses introduced by the secondary motions released by serrated leading-edges. In this paper we investigate a design of experiments that entails 76 cases of a 3D flow cascade with NACA 4digit profiles with sinusoidal leading edges to measure losses according to the Lieblein’s approach. The flow field simulated with RANS strategy was investigated using an unsupervised machine learning strategy to classify and isolate the turbulent wake downstream of the cascade with a combination of Principal Component Analysis and Gaussian Mixture clustering. Then a gradient boosting regressor was used to derive the correlation between input parameters and cascade deflection.