Flow, Turbulence and Combustion最新文献

The application of wind energy leads to reduced greenhouse gas emissions and dependence on conventional sources of fuels. Nevertheless, traditional Savonius wind energy systems suffer from high negative torque and low efficiency. Therefore, the optimization of the blade shape of the Savonius wind turbine is an effective approach to enhance the use of clean and sustainable wind energy. In this work, selecting supplementary blades with quarter elliptical shapes is proposed to optimize the aerodynamic efficiency of the Savonius rotor by enhancing the amount of captured wind at minimal cost. The turbulence model SST/k–ω is used in ANSYS fluent to numerically simulate the performance of the rotor with supplementary blades. As a function of tip speed ratio (TSR), the torque coefficient (Ct) and power coefficient (Cp) are computed. Furthermore, the total pressure, velocity, and streamlines are estimated and analyzed. The results showed that the supplementary blades have the ability to enhance the output power of the turbine by lowering the negative drag behind the returning blade. Overall, the new configuration enhances the suction vortices and reverses flow, leading to better aerodynamic performance. The maximum Cp for the new configuration is observed at TSR = 0.5 with a value of 0.181 which is 13.1% better than the conventional Savonius turbine.

High fidelity computational fluid dynamics (CFD) is increasingly being used to enable deeper understanding of turbulence or to aid in the design of practical engineering systems. While such CFD approaches can predict complex turbulence phenomena, the computational grid often needs to be sufficiently refined to accurately capture the flow, especially at high Reynolds number. As a result, the computational cost of the CFD can become very high. It therefore becomes impractical to adopt such simulations for parametric investigations. To mitigate this, we propose a framework where coarse grid simulations can be used to predict the fine grid results through machine learning. Coarsening the computational grid increases the grid-induced error and affects the prediction of turbulence. This requires an approach that can generate a data-driven surrogate model capable of predicting the local error distribution and correcting for the turbulence quantities. The proposed framework is tested using a turbulent bluff-body flow in an enclosed duct. We first highlight the flow field differences between the fine grid and coarse grid simulations. We then consider a set of scenarios to investigate the capability of the surrogate model to interpolate and extrapolate outside the training data range. The impact of operating conditions and grid sizes are considered. A Random Forest regression algorithm is used to construct the surrogate model. Two different sets of input features are investigated. The first only takes into account the grid-induced error and local flow properties. The second supplements the first using additional variables that serve to capture and generalise turbulence. The global and localised errors for the predictions are quantified. We show that the second set of input features is better at correcting for the biases due to insufficient resolution and spurious flow behaviour, providing more accurate and consistent predictions. The proposed method has proven to be capable of correcting the coarse-grid results and obtaining reasonable predictions for new, unseen cases. Based on the investigated cases, we found this method maximises the benefit of the available data and shows potential for a good predictive capability.

We call classical a transport model in which each governing equation comprises a production term proportional to velocity gradients and terms such as diffusion and dissipation which are built from the internal quantities of the model and are local. They may depend on the wall-normal coordinate y. We consider the layer along a wall in which the total shear stress is uniform, and y is much smaller than the thickness of the full wall layer. We only use channels and boundary layers, but have seen no evidence that pipe flow is different. The conjectured General Law of the Wall (GLW), in contrast with the classical law for mean velocity (U) only, states that every quantity Q in the model (e.g., dissipation, stresses) is the product of four quantities: powers of the friction velocity ({u}_{tau }) and y which satisfy dimensional analysis; a constant C characteristic of the model; and a function f of the wall distance y in wall units, which closely approaches 1 outside the viscous and buffer layers. This is independent of any flow Reynolds number such as the friction Reynolds number in a channel, once it is large enough, and it rigidly constrains the y-dependence of Q outside the wall region: in particular, all the stresses are on plateaus. In the widely accepted velocity law of the wall, the shear rate dU/dy satisfies such a law with C the inverse of the Karman constant (kappa). We cannot prove the GLW property as a theorem, but we provide extensive arguments to the effect that any Classical equation set allows it, and many numerical results support it. A Structural Limitation any Classical Model would suffer from then arises because the results of experiments (not shown here) and Direct Numerical Simulations contradict the GLW, already for some of the Reynolds stresses in simple flows and all the way to the wall (the conflict between the GLW as predicted by Classical turbulence theory, on which the models are based, and measurements was discussed by Townsend as early as Townsend in J Fluid Mech 11:97–120, 1961). This implies that no modification of a model that remains within the classical type can make it agree closely with this key body of results. This has been tolerated for decades, but the GLW is stated here more precisely than it has been implicitly in the literature, it extends all the way to the wall, and it has theoretical interest. It creates a danger for the developing “data-driven” efforts based on Machine Learning in turbulence modelling, which generally involve all six Reynolds stresses and possibly other quantities such as budget terms.

Manipulating the organized flow in the near-wall region of a turbulent boundary layer is a direct path to achieving skin-friction drag reduction. However, near-wall flow measurements in high Reynolds number ((Re_{tau })) wall flows can be challenging, due to this region’s small physical size and measurement resolution issues. The present study demonstrates the capability of hot-wire (HW) and stereoscopic particle image velocimetry (PIV) techniques of accurately estimating the trends of near-wall flow statistics in high-(Re_{tau }) drag-reduced turbulent boundary layers. The drag reduction strategy considered involves imposition of streamwise travelling waves of spanwise wall oscillations, well known for attenuating the drag-producing near-wall streaks via unsteady cross-flow straining. A flow phase identification methodology is proposed, based on real-time tracking of the wall-oscillation cycle, to estimate the near-wall phase-based statistics from PIV experiments. This methodology is leveraged to investigate phase-specific orientations of the near-wall flow features, which have been shown in the literature to mimic the characteristics of the shear strain vector, dictating the efficacy of this drag reduction scheme. Reconciliation of the HW and PIV measurements demonstrates that the trends exhibited by higher-order moments of the near-wall streamwise velocity fluctuations, with increasing drag reduction, are representative of the inherent flow physics of the drag-reduced flow. Apart from assisting with the design of high-(Re_{tau }) experiments over drag-reducing devices (riblets, plasma actuators, etc.), the present outcomes also inform high-(Re_{tau }) studies in more general three-dimensional wall flows.

Turbulent length and time scales represent a fundamental quantity for analysing and modelling turbulent flows. Although higher order statistical moments have been conveniently used for decades to describe the mean behaviour of turbulent fluid flow, the definition of the integral turbulent scales seems to be limited to the velocity or its fluctuation itself (i.e. the first moment). Higher order moments are characterized by smaller integral scales and a framework is proposed for estimating autocorrelation functions and integral turbulent length or time scales of higher order moments under the assumption that the probability distribution of the velocity field is Gaussian. The new relations are tested for synthetic turbulence as well as for DNS data of a turbulent plane jet at Reynolds number 10000. The present results in particular suggest that the length or time scales of higher order moments can be markedly smaller than those of the turbulent variable itself, which has implications for statistical uncertainty estimates of higher order moments.

In this study, the viscous filtering technique is extended to one-sided and biased finite-difference schemes for non-uniform meshes. The most attractive feature of this technique lies in its numerical stability despite the use of a purely explicit time advancement. This feature is well recovered for non-uniform meshes, making the approach as a simple and efficient alternative to the implicit time integration of the viscous term in the context of direct and large-eddy simulation. The rationale to develop generalized filter schemes is presented. After a validation based on the Burgers solution while using a refined mesh in the shock region, it is shown that a high-order formulation can be used to ensure both molecular and artificial dissipation for performing implicit LES of transitional boundary layer while relaxing drastically the time step constraint.

Installation noise is a dominant source associated with aircraft jet engines. Recent studies show that linear wavepacket models can be employed for prediction of installation noise, which suggests that linear control strategies can also be adopted for mitigation of it. We present here a simple model to test different control approaches and highlight the potential restrictions on a successful noise control in an actual jet. The model contains all the essential elements for a realistic representation of the actual control problem: a stochastic wavepacket is obtained via a linear Ginzburg-Landau model; the effect of the wing trailing edge is accounted for by introducing a semi-infinite half plane near the wavepacket; and the actuation is achieved by placing a dipolar point source at the trailing edge, which models a piezoelectric actuator. An optimal causal resolvent-based control method is compared against the classical wave-cancellation method. The effect of the causality constraint on the control performance is tested by placing the sensor at different positions. We demonstrate that when the sensor is not positioned sufficiently upstream of the trailing edge, which can be the case for the actual control problem due to geometric restrictions, causality reduces the control performance. We also show that this limitation can be moderated using the optimal causal control together with modelling of the forcing.

Flow and acoustic fields of a rectangular over-expanded supersonic jet interacting with an adjacent parallel plate are investigated using compressible Large Eddy Simulations (LES). The jet exits from a converging diverging rectangular nozzle of aspect ratio 2 with a design Mach number 1.5. Four distances (0 to 3 equivalent diameters) between the plate and the adjacent lip of the rectangular jet in the minor axis plane are studied. The geometry of the nozzle, the positions of the plate, and the exit conditions are identical to the ones of an experimental study. Snapshots and mean velocity fields are presented. Good agreement with the PIV experimental measurements is obtained. Previously, the corresponding free jet has been found to undergo a strong flapping motion in the minor axis plane due to screech. Here, it is shown that the intensity of the screech increases for certain distances from the plate and decreases for others, as compared to the corresponding free jet. Two points space-time cross correlations of the pressure along the jet’s shear-layers show, in two cases, an amplification of the aeroacoustic feedback mechanism leading to screech noise in the jet shear-layer closer to the plate. This amplification is due to acoustic waves impinging on the plate, and generating propagating waves back towards the jet, thus exciting the shear-layer at the screech frequency, around the tenth shock cell. Moreover, when the jet develops as a wall jet on the plate, the screech frequency and its associated flapping motion is canceled but a symmetrical oscillation of the jet at a lower frequency becomes dominant and radiates in the near acoustic field. This oscillation mode, as the ones associated with the screech tones for the other cases studied, can be explained by the use of a vortex sheet model of the ideally expanded equivalent planar jet.

The freestream turbulence-induced transition of a dense-gas boundary layer past a thick leading edge representative of turbine blades is investigated with large-eddy simulations. Due to the high Reynolds number conditions, typical of Organic Rankine Cycle applications, transition occurs early on the blade. In such conditions, the freestream turbulence is characterized by relatively large scales compared to the boundary layer size, but at the same time small compared to the blade thickness. These turbulent structures wrap around the large leading-edge and strongly influence the downstream evolution of the transitional boundary layer, by modulating the appearance and evolution of turbulent spots. Combined with the favorable pressure gradient, this effect delays and smooths the transitional region over a wider chordwise extent compared to flat plate bypass transitions with comparable levels of freestream turbulence. Laminar streaks are generated inside the transitional boundary layer in the form of clusters, modulated by the intense large-scale structures that develops at the leading-edge. Despite their low population, the low-speed streaks are found to be the turbulent spots precursors through two mechanisms: streak instabilities and streak interactions. The main effect of the use of an organic vapour is the high-Reynolds-number effects in the leading-edge receptivity process. Another intriguing peculiarity of the dense-gas is the appearence of near-wall spanwise-oriented vortices below the turbulent spots. Such structures have been observed in supersonic air flows on cold walls. Despite the subsonic Mach number in the transition region for the present configuration, their presence is associated to the large heat capacity of the organic working fluid that almost suppresses friction heating.

The mechanism that provokes friction drag reduction in a turbulent boundary layer flow which is actively controlled by spanwise travelling transversal surface waves is investigated. The focus is on discussing the drag reducing mechanism for a low and a moderately high Reynolds number. At the low friction velocity based Reynolds number (Re_tau approx 393), the periodic secondary flow field induced by the surface actuation interacts with the quasi-streamwise vortices. An elliptic deformation of these vortices initiates their breakup and the reduced amount lowers the overall wall-shear stress level due to the consequently attenuated high-speed streaks. At the moderately high Reynolds number (Re_tau approx 1525), the effectiveness of this mechanism is reduced but a second contributor occurs, which manipulates the inner–outer interaction. The large-scale motions of the log layer can less effectively impose their footprint onto the near-wall flow field since large-scale ejections, which are introduced by the surface actuation in the near-wall region, balance the outer-layer sweeps. Since the outer-layer impact on the inner region is intensified by increasing Reynolds number, its disruption is beneficial as to a successful application of this drag reduction method to engineering relevant Reynolds numbers.