M. Seddighi

Near Wall Behavior of Turbulence in an Unsteady Channel Flow

Direct Numerical Simulations (DNS) of unsteady turbulent flows in a channel accelerating uniformly from steady state are performed to study turbulence behaviour near the wall. Several steady flow simulations at various Reynolds numbers are carried out to facilitate direct comparisons between steady and unsteady behavior. It is shown that the behavior of turbulence for the streamwise velocity component in the near wall region is distinctly different from that in the core region. Moreover, the three components of the turbulent fluctuations exhibit very different characteristics reflecting the anisotropic behaviour of turbulence.

The Influence of Free Stream Turbulence Intensity on the Unsteady Behavior of a Wind Turbine Blade Section

Extensive wind tunnel tests have been conducted to investigate effects of turbulence intensity variations on the behavior of a section of a wind turbine blade in an oscillatory motion. Special emphasize was applied on the aerodynamic characteristics when oscillating the model in the vicinity of its static stall angle of attack and in the post stall condition. The model had 0.25m chord and was pitched about its quarter-chord. Data were acquired at various Reynolds number, and reduced frequency. Results show that turbulent intensity has strong effect on the unsteady load coefficients, hence aerodynamic performance of this model. Furthermore, free stream turbulence has different effect on the aerodynamic loads when the maximum angle of attack is near the static stall angle or beyond it (Post stall condition).

Transition of Transient Channel Flow with High Reynolds Number Ratios

Large-eddy simulations of turbulent channel flow subjected to a step-like acceleration have been performed to investigate the effect of high Reynolds number ratios on the transient behaviour of turbulence. It is shown that the response of the flow exhibits the same fundamental characteristics described in He & Seddighi (J. Fluid Mech., vol. 715, 2013, pp. 60–102 and vol. 764, 2015, pp. 395–427)—a three-stage response resembling that of the bypass transition of boundary layer flows. The features of transition are seen to become more striking as the Re-ratio increases—the elongated streaks become stronger and longer, and the initial turbulent spot sites at the onset of transition become increasingly sparse. The critical Reynolds number of transition and the transition period Reynolds number for those cases are shown to deviate from the trends of He & Seddighi (2015). The high Re-ratio cases show double peaks in the transient response of streamwise fluctuation profiles shortly after the onset of transition. Conditionally-averaged turbulent statistics based on a λ_2-criterion are used to show that the two peaks in the fluctuation profiles are due to separate contributions of the active and inactive regions of turbulence generation. The peak closer to the wall is attributed to the generation of “new” turbulence in the active region, whereas the peak farther away from the wall is attributed to the elongated streaks in the inactive region. In the low Re-ratio cases, the peaks of these two regions are close to each other during the entire transient, resulting in a single peak in the domain-averaged profile.

Influence of a k-type Roughness on the Behaviour of Turbulence in an Unsteady Channel Flow

Direct Numerical Simulations (DNS) have been carried out for a spatially fully developed turbulent channel flow with one smooth wall and one k-type rough-wall surface to study the influence of a square bar roughness on the behaviour of unsteady turbulent flow. The flow state under investigation is a uniform acceleration from an initially steady turbulent flow. Results are compared with simulations of flows in a smooth wall channel undergoing a similar acceleration, and with quasi-steady behaviour obtained using steady flow simulations. The turbulence in the wall region and the buffer layer of an accelerating flow with a rough wall shows strikingly different behaviour from that of corresponding flows with smooth walls. The characteristic long delays in the response of the streamwise turbulent velocity and the different behaviours of the three turbulent velocity components that are exhibited in smooth wall flows are not seen in the rough wall flow. This is attributed to different turbulent production mechanisms in the two types of flows. Important differences are also seen in the wall shear stress responses one wall is rough and when both walls are smooth.

Prediction of Transition Point on an Oscillating Airfoil Using Neural Network

Dynamic Neural network was used to minimize the amount of data required to predict the location of transition point on a 2-D oscillatory wing. For this purpose, various experimental tests were carried out on a section of a 660kw wind turbine blade. A multi layer non linear perceptrons network was trained using the output signals of four hot films attached on the upper surface of the model. Results show that using only 50% of the test data, the trained network was able to the transition point with an acceptable accuracy. Moreover, the method can predict the transition points at any position of the wing surface for different Reynolds numbers, amplitudes and initial angles of oscillation, and of course at various reduced frequencies.Copyright

Effect of Surface Roughness on an Airfoil in Pitching Motion

Extensive experimental tests have been conducted to examine the roughness effects on the aerodynamic performance of a model in an oscillatory motion. All tests were carried out in a 0.8× 0.8 m 2 low-speed wind tunnel. The model had 0.25m chord and was pitched about its quarter-chord. Data were acquired at various Reynolds number and reduced frequencies. Surface roughness was applied at two different locations of the model upper surface, leading edge and the point of maximum thickness. Furthermore, tunnel turbulent was varied and all tests were repeated. The results indicate that the width of the hysteresis loop, position of the figure eight shape, slope of the normal force coefficient curve, as well as the maximum normal force of the model were all influenced by both the surface roughness and turbulent intensity significantly. Nomenclature k = Reduced frequency, ∞ = U fc k π f = Pitching frequency, (Hz) ∞ U = Free stream velocity (m/s) c = Airfoil chord (m) 0 α = Mean incidence angle (deg) α = Amplitude of the pitching motion, (deg) l C = Lift coefficient n C = Normal force coefficient a