Experimental investigation of aerofoil tonal noise at low Mach number

This paper presents an experimental investigation of aerofoil tones emitted by a controlled-diffusion aerofoil at low Mach number ( $0.05$ ), moderate Reynolds number based on the chord length ( $1.4 \times 10^{5}$ ) and moderate incidence ( $5^{\circ }$ angle of attack). Wall-pressure measurements have been performed along the suction side of the aerofoil to reveal the acoustic source mechanisms. In particular, a feedback loop is found to extend from the aerofoil trailing edge to the regions near the leading edge where the flow encounters a mean favourable pressure gradient, and consists of acoustic disturbances travelling upstream. Simultaneous wall-pressure, velocity and far-field acoustic measurements have been performed to identify the boundary-layer instability responsible for tonal noise generation. Causality correlation between far-field acoustic pressure and wall-normal velocity fluctuations has been performed, which reveals the presence of a Kelvin–Helmholtz-type modal shape within the velocity disturbance field. Tomographic particle image velocimetry measurements have been performed to understand the three-dimensional aspects of this flow instability. These measurements confirm the presence of large two-dimensional rollers that undergo three-dimensional breakdown just upstream of the trailing edge. Finally, modal decomposition of the flow has been carried out using proper orthogonal decomposition, which demonstrates that the normal modes are responsible for aerofoil tonal noise. The higher normal modes are found to undergo regular modulations in the spanwise direction. Based on the observed modal shape, an explanation of aerofoil tonal noise amplitude reduction is given, which has been previously reported in modular or serrated trailing-edge aerofoils.

Modelling Wall-Pressure Spectra in Turbulent Boundary Layers Using Neural Networks

In this work, we model the spectra of wall-pressure fluctuations beneath subsonic, supersonic and hypersonic turbulent boundary layers (TBLs) at zero pressure gradient using neural networks (NNs). We collect and compile data pertaining to wall-pressure fluctuation spectra from several experimental and computational studies on TBLs. In contrast to conventional methods of hand-tuning the parameters of a model to fit the available data, the use of modern powerful statistical learning techniques such as neural networks provide an automatic and quick way to fit a model. We explore four different scenarios of making use of the compiled data. In comparison with COMPRA-G, an empirical model recently proposed to account for compressibility effects in TBLs, we achieve a better fit to observed data using the NN model, particularly at low frequencies of the spectra.

Effect of Emissary Vein on Hemodynamics of the Transverse- Sigmoid Sinus Junction

Objective: To investigate the effect of the blood flow direction and afflux location of emissary veins (EVs) on the hemodynamics of the transverse-sigmoid sinus (TS-SS) junction.Methods: A patient-specific geometric model was constructed using computed tomography venography (CTV) and 4D flow MR data from a venous pulsatile tinnitus (PT) patient. New EV models were assembled with the afflux at the superior, middle and inferior portions of the SS from the original model, and inlet and outlet directions were applied. Computational fluid dynamics (CFD) simulation was performed to analyze the wall pressure and flow pattern of the TS-SS junction in each condition.Results: Compared to the model without EVs, the wall pressure was greatly increased in models with inlet flow and greatly decreased in models with outlet flow. The more closely the EV approached the TS-SS, the larger the pressure in models with inlet flow, and the smaller the pressure in models with outlet flow. The flow streamline in the lateral part of the TS-SS junction was smooth in all models. The streamlines in the medial part were regular spirals in outlet models and chaotic in inlet models. The streamlines showed no obvious changes regardless of afflux location. The velocity at the TS-SS junction of inlet models were uniform, medium-low flow rate, while in control and outlet models were the lateral high flow rate and the central low flow rate.Conclusion: The flow direction and afflux location of EVs affect the hemodynamics of the TS-SS junction, which may influence the severity of PT.