Wind energy is one of the significant sources of renewable energy, yet a number of challenges preclude optimal operation of wind plants. Research is warranted in order to minimize the power losses and improve the productivity of wind plants. Here, a framework combining turbulence theory and data mining techniques is built to elucidate physics and mechanisms driving the energy extraction of the wind plants under a number of atmospheric/operating conditions. The performance of wind turbines is subjected to adverse effects caused by wake interactions. Therefore, it is crucial to understand wake-to-wake interactions as well as wake-to-atmospheric boundary layer interactions. Experimental and numerical data sets are examined in order to provide descriptions of the wakes and extract relevant features. As wakes merge, it is of interest to observe characteristics within the turbulent velocity signal obtained via wind tunnel experiments. Higher order moments, structure functions, intermittency and multifractality analysis are investigated to distinguish the flow dynamics. In this manner, considered approaches highlight the flow deceleration induced by the wind turbines, which subsequently changes the energy transfer rate imposed by the coherent eddies, and adapt the equilibrium range in the energy cascade. Also, wind turbines induce scale interactions and cause the intermittency that lingers at large and small scales. When wind plants interact dynamically with small scales, the flow becomes highly intermittent and multifractality is increased, especially near the rotor. Multifractality parameters, including the Hurst exponent and the combination factor, show the ability to describe the flow state in terms of its development. Based on Markov theory, the time evolution of the probability density function of the velocity is described via the Fokker-Planck equation and its Kramers-Moyal coefficients. Stochastic analysis proves the non-universality of the turbulent cascade immediate to the rotor, and the impact of the generation mechanism on flow cascade. Classifying the wake flow based the velocity and intermittency signs emphasizes that a negative correlation is dominant downstream from the rotor. These results reflect large-scale organization of the velocity-intermittency events corresponding to a recirculation region near the hub height and bottom tip. A linear regression approach based on the Gram-Charlier series expansion of the joint probability density function successfully models the contribution of the second and fourth quadrants. Thus, the model is able to predict the imbalance in the velocity and intermittency contribution to momentum transfer. Via large eddy simulations, the structure of the turbulent flow within the array under stratified conditions is quantified through the use of the Reynolds stress anisotropy tensor, proper orthogonal decomposition and cluster-based modeling. Perturbations induced by the turbine wakes are absorbed by the background turbulence in the unstable and neutrally stratified cases. Contrary, the flow in the stable stratified case is fully dominated by the presence of turbines and extremely influenced by the Coriolis force. Also, during the unstable period the turbulent kinetic energy is maximum. Thus, leading to fast convergence of the cumulative energy with only few modes. Reynolds stress anisotropy tensor reveals that under unstable thermal stratification the turbulence state tends to be more isotropic. The turbulent mixing due to buoyancy determines the degree of anisotropy and the energy distribution between the flow layers. The wakes of the turbines display large degree of anisotropy due to the correlation with the turbulent kinetic energy production. A combinatorial technique merging image segmentation via K-Means clustering and colormap of the barycentric map is posed. Clustering aids in extracting identical features from the spatial distribution of anisotropy colormap images by minimizing the sum of squared error over all clusters. Clustering also enables to highlight the wake expansion and interaction as produced by the wind turbines as a function of thermal stratification. A cluster-based reduced-order dynamical model is proposed for flow field and passive scalars; the model relies on full-state measurements. The dynamical behavior is predicted through the cluster transition matrix and modeled as a Markov process. The geometric nature of the attractor shows the ability to assess the quality of the clustering and identify transition regions. Periodical trends in the cluster transition matrix characterize the intrinsic periodical behavior of the wake. The modeling strategy points out a feasible path for future design and control that can be used to maximize power output. In addition, characterization of intermittency with power integration model can allow for power fluctuation arrangement/prediction in wind plants.

For aircraft that have propellers mounted in front of the wings or tail, the prop wash produced by the propellers can have a strong influence on the aerodynamics of the aircraft. As the accelerated air from the propeller flows over the wings and tail, it can cause an alteration in the aerodynamic forces produced by those surfaces. Thus, an understanding of propeller-wing interactions is essential for the design and analysis of many aircraft. There are multiple existing methods for analyzing the propeller-wing interactions. High order methods, such as wind tunnel testing or computational fluid dynamics, provide very accurate results but come at a high cost in computation or labor. Low-order methods provide results with good accuracy at a significantly lower cost. Thus, it is desirable to use low-order methods for initial design and utilize higher order methods closer to the end of the design phase. Current low-order models for propeller-wing interactions give reasonable results, but have shortcomings in either computational cost or accuracy. In an effort to improve on these existing models, an improved low-order model for propeller-wing interactions is proposed. This improved model utilizes several aerodynamic models such as blade element theory and lifting line theory as well as a novel turbulent prop wash model. The final model is shown to provide more accurate results using efficient numerical methods.

No description available.

No description available.

Thesis (Ph. D.)--Washington State University, December 2006. / Includes bibliographical references (p. 148-156).

Thesis (M.S.M.E.)--University of Delaware, 2006. / Principal faculty advisor: Sunil K. Agrawal, Dept. of Mechanical Engineering. Includes bibliographical references.

Ground vehicles, both on roads or on rail, are sensitive to crosswinds and the handling, travelling speeds or in some cases, safety can be affected. Full modelling of the crosswind stability of a vehicle is a demanding task as the nature of the disturbance, the wind gust, is complex and the aerodynamics, vehicle dynamics and driver reactions interact with each other.  One of the objectives of this thesis, is to assess the aerodynamic response of simplified ground vehicles under sudden strong crosswind disturbances by using an advanced turbulence model. In the aerodynamic simulations, time-dependant boundary data have been used to introduce a deterministic wind gust model into the computational domain.  This thesis covers the implementation of such gust models into Detached-Eddy Simulations (DES) and assesses the overall accuracy. Different type of grids, numerical setups and refinements are considered. Although the overall use of DES is seen suitable, further investigations can be foreseen on more challenging geometries.  Two families of vehicle models have been studied. The first one, a box-like geometry, has been used to characterize the influence of the radius of curvature and benefited from unsteady experimental data for comparison. The second one, the Windsor model, has been used to understand the impact of the different rear designs. Noticeably, the different geometries tested have exhibited strong transients in the loads that can not be represented in pure steady crosswind conditions. The static coupling between aerodynamics and vehicle dynamics simulations enhances the comparisons of the aerodynamic designs. Also, it shows that the motion of the centre of pressure with respect the locations of the centre of gravity and the neutral steer point, is of prime interest to design vehicles that are less crosswind sensitive. Recommendations on the future work on crosswind sensitivity for ground vehicles are proposed at the end of this thesis. / <p>QC 20111206</p> / crosswind stability and unsteady aerodynamics

Computational investigations were carried out on an advanced serpentine jet engine inlet duct to understand the development and propagation of secondary flow structures. Computational analysis which went in tandem with experimental investigation was required to aid secondary flow control required for enhanced pressure recovery and decreased distortion at the engine face. In the wake of earlier attempts with modular fluidic actuators used for this study, efforts were directed towards optimizing the actuator configurations. Backed by both computational and experimental resources, many variations in the interaction of fluidic actuators with the mainstream flow were attempted in the hope of best controlling secondary flow formation. Over the length of the studies, better understanding of the flow physics governing flow control for 3D curved ducts was developed. Blowing tangentially, to the wall at the bends of the S-duct, proved extremely effective in enforcing active flow control. At practical jet momentum coefficients, significant improvements characterized by an improved pressure recove ry of 37% and a decrease in distortion close to 90% were seen.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: Low Reynolds Number; Micro Air Vehicle; Low Aspect Ratio; Spanwise pressure measurements; Spanwise Lift Distributions. Includes bibliographical references (p. 84-85).

Thesis (M.S. in Mechanical Engineering)--Naval Postgraduate School, June 2004. / Thesis advisor(s): Knox Millsaps. Includes bibliographical references (p. 69-72). Also available online.