Matthew Melius

Identification of Markov process within a wind turbine array boundary layer

The Markovian properties within a wind turbine array boundary layer are explored for data taken in a wind tunnel containing a model wind turbine array. A stochastic analysis of the data is carried out using the mathematics of Markov processes. The data were obtained using hot-wire anemometry thus providing point velocity statistics. The theory of Markov process is applied to obtain a statistical description of longitudinal velocity increments inside the turbine wake. Comparison of two- and three-scale conditional probability density functions indicates the existence of Markovian properties in longitudinal velocity increments for scale differences larger than the Taylor microscale. This result is quantified by use of the Wilcoxon rank-sum test which verifies that this relationship holds independent of initial scale selection outside of the near-wake region behind a wind turbine. Furthermore, at the locations which demonstrate Markovian properties, there appears to be a well defined inertial subrange which ...

Evaluation of Higher Order Moments and Isotropy in the Wake of a Wind Turbine Array

Hot-wire measured signals are analyzed using the third and fourth order statistical moments as well as the energy spectra and structure functions in the wake of a model wind turbine array. The skewness experiences sharp excursions, away from a Gaussian behavior, due to the presence of the turbine rotor. Kurtosis is maximized at the top tip, hub, and bottom tip of the turbine. A below Gaussian kurtosis level in the probability density function (pdf) results for the streamwise direction moving away from the wall, while the hub and top tip of the pdf converge to a Gaussian behavior. At one diameter downstream of the turbine, the wall-normal kurtosis at the top tip, hub region, and slightly above the wall positions shows an increase in comparison to the other wall-normal locations. Similar peaks in wall-normal kurtosis are found five diameters and one diameter downstream of the turbine in near-wall region. These peaks converge to Gaussian behavior moving away from the wall. Energy spectra and structure functions indicate that the inertial subrange extends near the top tip in the near-wake and away from the wall in the far-wake. Utilizing the cross-spectra and mixed structure function, anisotropic behavior is held for all near- and far-wake region with exception at some small scales. Based on the structure function ratios of wall-normal and streamwise velocities, the wake is highly anisotropic for all locations except at top tip and the majority of scales in the near-wake. Contrary to this result, the ratio between the wall-normal and streamwise spectrum displays a defined range of scales behaving isotropically at most locations, the only exception being at hub height. In far-wake, the structure function ratio and spectral ratio show a significant reduction in anisotropic behavior at larger scales.

Dynamic stall of an experimental wind turbine blade

To understand the complex flow phenomena over wind turbine blades during stall development, a scaled three-dimensional non-rotating blade model is designed to be dynamically similar to a rotating full-scale NREL 5 MW wind turbine blade. A time-resolved particle image velocimetry (PIV) investigation of flow behavior during the stall cycle examines the processes of stall development and flow reattachment. Proper orthogonal decomposition (POD) and vortex detection techniques are applied to the PIV fields to quantify relevant flow characteristics such as vortex size, separation angle, and separation point throughout a dynamic pitching cycle. The behavior of the POD coefficients provides time scales for the transitional stages which are quantified and compared, revealing that transition from attached flow to full stall is delayed to higher angles of attack and occurs at a higher rate than the transition from full stall to attached flow. The instantaneous flow fields are then reconstructed using the first four POD modes to demonstrate their prominent roles throughout the stall cycle and their ability to capture the general separation behavior over the blade surface

The role of surface vorticity during unsteady separation

Unsteady flow separation in rotationally augmented flow fields plays a significant role in a variety of fundamental flows. Through the use of time-resolved particle image velocimetry, vorticity accumulation and vortex shedding during unsteady separation over a three-dimensional airfoil are examined. The results of the study describe the critical role of surface vorticity accumulation during unsteady separation and reattachment. Through evaluation of the unsteady characteristics of the shear layer, it is demonstrated that the buildup and shedding of surface vorticity directly influence the dynamic changes of the separation point location. The quantitative characterization of surface vorticity and shear layer stability enables improved aerodynamic designs and has a broad impact within the field of unsteady fluid dynamics.Unsteady flow separation in rotationally augmented flow fields plays a significant role in a variety of fundamental flows. Through the use of time-resolved particle image velocimetry, vorticity accumulation and vortex shedding during unsteady separation over a three-dimensional airfoil are examined. The results of the study describe the critical role of surface vorticity accumulation during unsteady separation and reattachment. Through evaluation of the unsteady characteristics of the shear layer, it is demonstrated that the buildup and shedding of surface vorticity directly influence the dynamic changes of the separation point location. The quantitative characterization of surface vorticity and shear layer stability enables improved aerodynamic designs and has a broad impact within the field of unsteady fluid dynamics.

Experimental Study of Turbine Hub Height Variation on Wind Farms

Characteristics of a wind turbine array boundary layer under controlled variations of the hub height of the turbines are studied through wind tunnel experiments. The atmosphere has been reproduced using a passive grid, strakes and roughness elements. Particle image velocimetry technique is employed to obtain converged statistics at four locations at the centerline. The array consists of a four by three arrangement. The velocity eld is then studied, mean velocity and uctuations, to observe dierences attributed to the change in hub height of the turbine.