Aerodynamics

Peer-to-peer file-sharing networks are currently receiving much attention as a means of sharing and distributing information. However, as recent experience shows, the anonymous, open nature of these networks offers an almost ideal environment for the spread of self-replicating inauthentic files.

Air Traffic Management (ATM) of the future allows for the possibility of free flight, in which aircraft choose their own optimal routes, altitudes, and velocities. The safe resolution of trajectory conflicts between aircraft is necessary to the success of such a distributed control system. In this paper, we present a method to synthesize provably safe conflict resolution maneuvers. The method models the aircraft and the maneuver as a hybrid control system and calculates the maximal set of safe initial conditions for each aircraft so that separation is assured in the presence of uncertainties in the actions of the other aircraft. Examples of maneuvers using both speed and heading changes are worked out in detail.

In this paper, by incorporating the dynamic surface control technique into a neural network-based adaptive control design framework, we have developed a backstepping-based control design for a class of nonlinear systems in pure-feedback form with arbitrary uncertainty. The circular design problem which may exist in pure-feedback systems is overcome. In addition, our development is able to eliminate the problem of 'explosion of complexity' inherent in the existing backstepping-based methods. A stability analysis is given, which shows that our control law can guarantee the semi-global uniformly ultimate boundedness of the solution of the closed-loop system, and makes the tracking error arbitrarily small. Moreover, the proposed control design scheme can also be directly applied to the strict-feedback nonlinear systems with arbitrary uncertainty. 528 D. WANG and multi-output nonlinear systems . Their paper presented a unified and a general approach to backstepping control of nonlinear systems in strict-feedback form using NN.

This paper presents an integral predictive and nonlinear robust control strategy to solve the path following problem for a quadrotor helicopter. The dynamic motion equations are obtained by the Lagrange–Euler formalism. The proposed control structure is a hierarchical scheme consisting of a model predictive controller (mpc) to track the reference trajectory together with a nonlinear H∞H∞ controller to stabilize the rotational movements. In both controllers the integral of the position error is considered, allowing the achievement of a null steady-state error when sustained disturbances are acting on the system. Simulation results in the presence of aerodynamic disturbances, parametric and structural uncertainties are presented to corroborate the effectiveness and the robustness of the proposed strategy.

Dr. Pines is a Professor at the University of Maryland in the Department of Aerospace Engineering. He is currently on leave at the DARPA in the Defense Sciences Office. Dr. Pines research interests include smart structures, structural health monitoring and micro and nano air vehicle flight physics. He is a fellow of IOP and an associate fellow of AIAA. He is also a member of ASME and AHS. Felipe Bohorquez is doctoral student at the University of Maryland working on micro air vehicle research. He is a student member of AIAA and the American Helicopter Society.

Experiments have been performed on the tip vortex trailing from a rectangular NACA 0012 half-wing. Preliminary studies showed the vortex to be insensitive to the introduction of a probe and subject only to small wandering motions. Meaningful velocity measurements could therefore be made using hot-wire probes.

An assessment on the capability of a doubly fed induction generator (DFIG) wind turbine for frequency regulation is presented. Detailed aerodynamic, structural and electrical dynamic models were used in this study. A control loop acting on the frequency deviation was added to the inertia contributing loop in order to enhance the inertia support from the DFIG wind turbine. The possibility of de-loading a wind turbine to provide primary and secondary frequency response was discussed. A frequency droop controller was examined where the droop is operating on the electronic torque set point below its maximum speed and is operating on the pitch demand at maximum speed. It is also shown that by reducing the generator torque set point the DFIG wind turbine can provide high frequency response.

This paper presents the results of a parametric experimental investigation aimed at optimizing the body force produced by single dielectric barrier discharge plasma actuators used for aerodynamic flow control. A primary goal of the study is the improvement of actuator authority for flow control applications at higher Reynolds number than previously possible. The study examines the effects of dielectric material and thickness, applied voltage amplitude and frequency, voltage waveform, exposed electrode geometry, covered electrode width, and multiple actuator arrays. The metric used to evaluate the performance of the actuator in each case is the measured actuator-induced thrust which is proportional to the total body force. It is demonstrated that actuators constructed with thick dielectric material of low dielectric constant produce a body force that is an order of magnitude larger than that obtained by the Kapton-based actuators used in many previous plasma flow control studies. These actuators allow operation at much higher applied voltages without the formation of discrete streamers which lead to body force saturation.

In this paper, we present a controller design and its implementation on a mini-rotorcraft having 4 rotors. The dynamic model is obtained via a Lagrange approach. Experiment results show good performance of the proposed non-linear controller based on nested saturation.

The Kriging-based genetic algorithm is applied to aerodynamic design problems. The Kriging model, one of the response surface models, represents a relationship between the objective function (output) and design variables (input) using stochastic process. The kriging model drastically reduces the computational time required for objective function evaluation in the optimization (optimum searching) process. 'Expected improvement (EI)' is used as a criterion to select additional sample points. This makes it possible not only to improve the accuracy of the response surface but also to explore the global optimum efficiently. The functional analysis of variance (ANOVA) is conducted to evaluate the influence of each design variable and their interactions to the objective function. Based on the result of the functional ANOVA, designers can reduce the number of design variables by eliminating those that have small effect on the objective function. In this paper, the present method is applied to a two-dimensional airfoil design and the prediction of flap's position in a multi-element airfoil, where the lift-to-drag ratio (L/D) is maximized.

W ind is recognized worldwide as a cost-effective, environmentally friendly solution to energy shortages, and wind energy is currently t he fa stest-g row i ng energ y source in the world. Wind power investment worldwide is expected to expand threefold in the next decade, from about $18 billion in 2006 to $60 billion in 2016 . While the cost of wind energy is already very competitive with energy from coal and natural gas, there are still many unsolved challenges in expanding wind power. From bearings under constant friction to blades that must be able to handle gusts, lightning, and constantly changing wind conditions, today's wind turbines need increasingly sophisticated component designs, sensors, and control systems. Further, better wind forecasting methods are needed to improve site selection, optimize operations, and mitigate load fluctuations on the power grid. Although the United States receives only about 1% of its electrical energy from wind [2], the corresponding figure in Denmark is more than 15% . The integration of more than 20% penetration of wind energy into the grid will require modifications of the grid design and operation, with the possible addition of new transmission lines and energy storage systems.

In this paper, we consider the problem of autonomous navigation with a micro aerial vehicle (MAV) in indoor environments. In particular, we are interested in autonomous navigation in buildings with multiple floors. To ensure that the robot is fully autonomous, we require all computation to occur on the robot without need for external infrastructure, communication, or human interaction beyond high-level commands. Therefore, we pursue a system design and methodology that enables autonomous navigation with realtime performance on a mobile processor using only onboard sensors. Specifically, we address multi-floor mapping with loop closure, localization, planning, and autonomous control, including adaptation to aerodynamic effects during traversal through spaces with low vertical clearance or strong external disturbances. We present experimental results with ground truth comparisons and performance analysis.

This paper addresses mechanics, design, estimation and control for aerial grasping. We present the design of several lightweight , low-complexity grippers that allow quadrotors to grasp and perch on branches or beams and pick up and transport payloads. We then show how the robot can use rigid body dynamic models and sensing to verify a grasp, to estimate the the inertial parameters of the grasped object, and to adapt the controller and improve performance during flight. We present experimental results with different grippers and different payloads and show the robot's ability to estimate the mass, the location of the center of mass and the moments of inertia to improve tracking performance.

This paper proposes a wind speed estimation based sensorless maximum wind power tracking control for variable-speed wind turbine generators (WTGs). A specific design of the proposed control algorithm for a wind turbine equipped with a doubly fed induction generator (DFIG) is presented. The aerodynamic characteristics of the wind turbine are approximated by a Gaussian radial basis function network based nonlinear input-output mapping. Based on this nonlinear mapping, the wind speed is estimated from the measured generator electrical output power while taking into account the power losses in the WTG and the dynamics of the WTG shaft system. The estimated wind speed is then used to determine the optimal DFIG rotor speed command for maximum wind power extraction. The DFIG speed controller is suitably designed to effectively damp the low-frequency torsional oscillations. The resulting WTG system delivers maximum electrical power to the grid with high efficiency and high reliability without mechanical anemometers. The validity of the proposed control algorithm is verified by simulation studies on a 3.6 MW WTG system. In addition, the effectiveness of the proposed wind speed estimation algorithm is demonstrated by experimental studies on a small emulational WTG system.

Two independently developed mathematical models (GALES and HWIND) for predicting the critical wind speed and turning moment needed to uproot and break the stems of coniferous trees were compared and the results tested against field data on the forces experienced by forest trees and the wind speeds required to damage them. The GALES model calculates the aerodynamic roughness and zero-plane displacement of a forest stand. The aerodynamic roughness provides a measure of the stress (force/unit area) imposed on the canopy as a function of wind speed and the zero-plane displacement provides a measure of the average height on the tree at which the wind acts. Together they allow a calculation of the bending moment imposed on the tree for any wind speed. Data from almost 2000 trees uprooted during pulling experiments and destructive sampling of green wood then allow the model to make predictions of the wind speed at which the tree will be overturned and at which the tree will break for a number of coniferous species. The model assumes a linear relationship between tree stem weight and the maximum resistive moment that can be provided by the root system and it assumes that the stress in the outer fibres of the stem induced by the wind is constant with height. In the HWIND model the turning moment arising from the wind drag on the crown is calculated assuming a logarithmic upwind profile. Together with the contribution from the overhanging weight of the stem and branches caused by bending of the stem this provides the total bending moment. The angle of stem bend is explicitly calculated from the stiffness of the stem. The breaking strength of the stem and the support given by the root-soil plate are calculated from previous experiments on timber strength, and tree resistance to overturning by using root-soil plate mass to derive the resistive moment. This allows calculation of the wind speed required to break and overturn the tree. Model comparisons were performed for individual Scots pine (Pinus syl6estris L.) and Norway spruce (Picea abies L.) with varying tree height and stem taper (dbh/height). Tree location was at the forest stand edge on a podzolic soil. Model comparisons gave good agreement for the critical wind speeds at the forest edge required to break and overturn trees with a maximum difference in prediction of 26%. Slightly better agreement was obtained for Norway spruce (mean difference of 10.8%) than Scots pine (mean difference of 12.3%) and the best agreement was for trees with a taper of 100. At higher taper the GALES model generally predicted higher critical wind speeds than the HWIND model whereas at lower taper the reverse applied.

In this paper, we present a novel surrogate-assisted evolutionary optimization framework for solving computationally expensive problems. The proposed framework uses computationally cheap hierarchical surrogate models constructed through online learning to replace the exact computationally expensive objective functions during evolutionary search. At the first level, the framework employs a data parallel Gaussian Process based global surrogate model to filter the EA population of promising individuals. Subsequently, these potential individuals undergo a memetic search in the form of Lamarckian learning at the second level. The Lamarckian evolution involves a trust-region enabled gradient-based search strategy that employs radial basis function local surrogate models to accelerate convergence. Numerical results are presented on a series of benchmark test functions and an aerodynamic shape design problem. The results obtained suggest that the proposed optimization framework converges to good designs on a limited computational budget. Furthermore, it is shown that the new algorithm gives significant savings in computational cost when compared to the traditional evolutionary algorithm and other surrogate assisted optimization frameworks.

A time domain approach for predicting the coupled flutter and buffeting response of long span bridges is presented. The frequency dependent unsteady aerodynamic forces are represented by the convolution integrals involving the aerodynamic impulse function and structural motions or wind fluctuations. The aerodynamic impulse functions are derived from experimentally measured flutter derivatives, aerodynamic admittance functions, and spanwise coherence of aerodynamic forces using rational function approximations. A significant feature of the approach presented here is that the frequency dependent characteristics of unsteady aerodynamic forces and the nonlinearities of both aerodynamic and structural origins can be modeled in the response analysis. The flutter and buffeting response of a long span suspension bridge is analyzed using the proposed time domain approach. The results show good agreement with those from the frequency domain analysis. The example used to demonstrate the proposed scheme focuses on the treatment of frequency dependent self-excited and buffeting force effects. Application to nonlinear effects will be addressed in a future publication.

In this paper, we present a model of a four rotor vertical take-off and landing (VTOL) unmanned air vehicle known as quadrotor aircraft. And we explained its control architecture including vision based control. Quadrotors have generated considerable interest in both the control community due to their complex dynamics and military because of their advantages over regular air vehicles. The proposed dynamical model which comprises gyroscopic effects and its control strategies can be source for future works.

This paper focuses on a class of robot manipulators termed "continuum" robots-robots that exhibit behavior similar to tentacles, trunks, and snakes. In previous work, we studied details of the mechanical design, kinematics, path-planning and small-deflection dynamics for continuum robots such as the Clemson "Tentacle Manipulator." In this paper, we discuss the dynamics of a planar continuum backbone section, incorporating a large-deflection dynamic model. Based on these dynamics, we formulate a vibration-damping setpoint controller, and include experimental results to illustrate the efficacy of the proposed controller.

I review the concept of optimal vortex formation and examine its relevance to propulsion in biological and bio-inspired systems, ranging from the human heart to underwater vehicles. By using examples from the existing literature and new analyses, I show that optimal vortex formation can potentially serve as a unifying principle to understand the diversity of solutions used to achieve propulsion in nature. Additionally, optimal vortex formation can provide a framework in which to design engineered propulsions systems that are constrained by pressures unrelated to biology. Finally, I analyze the relationship between optimal vortex formation and previously observed constraints on Strouhal frequency during animal locomotion in air and water. It is proposed that the Strouhal frequency constraint is but one consequence of the process of optimal vortex formation and that others remain to be discovered.

This paper is a short and nonexhaustive survey of some recent developments in optimal shape design (OSD) for fluids. OSD is an interesting field both mathematically and for industrial applications. Existence, sensitivity, and compatibility of discretizations are important theoretical issues. Efficient algorithmic implementations with low complexity are also critical. In this paper we discuss topological optimization, algorithmic differentiation, gradient smoothers, Computer Aided Design (CAD)-free platforms and shock differentiation; all these are applied to a multicriterion optimization for a supersonic business jet.

Scientists studying the dynamics of objects can use these visualization techniques to extract objects from 2D and 3D scalar and vector fields and thereby reduce "visual clutter." S cientific visualization aims to devise algorithms and methods that transform massive scientific data sets into pictures and other graphic representations that facilitate comprehension and interpretation. In many scientific domains, analysis of these pictures has motivated further scientific investigationlaboratory experiments. numerical simulations. or remote observations. If a particular region of activity is of interest, scientists attempt to identify and quantify it: What is it, what is its cause, how does it evolve, how long does it persist'? For example. scientists track a storm's progress for weather prediction, the change in the ozone "hole" for knowledge about the greenhouse effect, and the movement of air over an aircraft or automobile for better aerodynamic design.

A nonlinear dynamic model for a quadrotor nnmanned aerial vehicle b presented with a new vlsion of state parameter control which is based on Euler angles and open loop positions state observer. This method emphasizes 00 the control of roll, pitch and yaw augle rather than the translational motions of tbe UAV. For tbls reason the system has been presented into two cascade partial parts, the first one relates the rotational motion whose the control law will be applled in a closed loop form and the other one reflects the translational motion. A dynamic feedback controller is developped to transform the dosed loop part of the system into Linear, controllable and decoupled snhsystem. The wind parameters estimation of the quadrotor is used to avoid more sensors. Hence an estimator of resulting aerodynamic moments via Lyapunov function Is developed. Performance and robustness of the proposed controller are tested in slmolntion.

State-plane techniques in conjunction with piecewise-linear analysis is employed to study the steady-state and transient characteristics of a series resonant converter. With the direct viewing of the resonant tank energy and the device switching instant, the state portrayal provides unique insights into the complex behavior of the converter. Operation of the converter under both continuous and discontinuous current modes and at frequencies both below and above resonant frequency are discussed.

The calculation of the derivatives of output quantities of aerodynamic flow codes, commonly known as numerical sensitivity analysis, has recently become of increased importance for a variety of applications in flow analysis, but the original motivation came from the field of aerodynamic shape optimization. There the large numbers of design variables needed to parameterize surfaces in 3d necessitates the use of gradient based optimization algorithms, and hence efficient and accurate evaluation of gradients. In this context over the last 20 years a variety of approaches have been developed to supply these gradients, raising particular challenges that have required novel algorithms. In this paper we examine the historical development of these approaches, describe in some detail the theoretical background of each major method and the associated numerical techniques required to make them practical in an engineering setting. We give examples from our own experience and describe what we consider to be the state-of-the-art in these methods, including their application to optimization of complex 3d aircraft configurations.

Steady-state RANS Computational Fluid Dynamics simulations of pollutant dispersion in the neutrally stable atmospheric boundary layer are made with the commercial code Fluent 6.1 for three case studies: plume dispersion from an isolated stack, low-momentum exhaust from a rooftop vent on an isolated cubic building model and high-momentum exhaust from a rooftop stack on a low-rise rectangular building with several rooftop structures. The results are compared with the Gaussian model, the semi-empirical ASHRAE model and wind tunnel and full-scale measurements. It is shown that in all three cases and with all turbulence models tested, the lateral plume spread is significantly underestimated. It is suggested that transient simulations might be required to achieve more accurate results. The numerical results are quite sensitive to the value of the turbulent Schmidt number. The comparisons however can not clearly indicate which Schmidt number is most suitable for which type of flow due to the large number of other error sources in the simulations, including steady-state RANS modelling, turbulence modelling, near-wall treatment limitations and unintended streamwise gradients in the turbulent kinetic energy profiles.

Many species travel in highly organized groups 1-3 . The most quoted function of these configurations is to reduce energy expenditure and enhance locomotor performance of individuals in the assemblage 4-11 . The distinctive V formation of bird flocks has long intrigued researchers and continues to attract both scientific and popular attention . The well-held belief is that such aggregations give an energetic benefit for those birds that are flying behind and to one side of another bird through using the regions of upwash generated by the wings of the preceding bird 4,7,9-11 , although a definitive account of the aerodynamic implications of these formations has remained elusive.

High performance and reliability are required for wind turbines to be competitive within the energy market. To capture their nonlinear behavior, wind turbines are often modeled using parameter-varying models. In this paper we design and compare multiple linear parameter-varying (LPV) controllers, designed using a proposed method that allows the inclusion of both faults and uncertainties in the LPV controller design. We specifically consider a 4.8 MW, variable-speed, variable-pitch wind turbine model with a fault in the pitch system. We propose the design of a nominal controller (NC), handling the parameter variations along the nominal operating trajectory caused by nonlinear aerodynamics. To accommodate the fault in the pitch system, an active fault-tolerant controller (AFTC) and a passive fault-tolerant controller (PFTC) are designed. In addition to the nominal LPV controller, we also propose a robust controller (RC). This controller is able to take into account model uncertainties in the aerodynamic model. The controllers are based on output feedback and are scheduled on an estimated wind speed to manage the parameter-varying nature of the model. Furthermore, the AFTC relies on information from a fault diagnosis system. The optimization problems involved in designing the PFTC and RC are based on solving bilinear matrix inequalities (BMIs) instead of linear matrix inequalities (LMIs) due to unmeasured parameter variations. Consequently, they are more difficult to solve. The paper presents a procedure, where the BMIs are rewritten into two necessary LMI conditions, which are solved using a two-step procedure. Simulation results show the performance of the LPV controllers to be superior to that of a reference controller designed based on classical principles.

In this paper we extend our previous results on coordinated control of rotating rigid bodies to the case of teams with heterogenous agents. We assume that only a certain subgroup of the agents (the leaders) are vested with the main control objective, that is, maintain constant relative orientation amongst themselves. The other members of the team must meet relaxed control specifications, namely, maintain their respective orientations within certain bounds, dictated by the orientation of the leaders. The proposed control laws respect the limited information each rigid body has with respect to the rest of its peers (leaders or followers), as well as with the rest of the team. Each rigid body is equipped with a feedback control law that utilizes the Laplacian matrix of the associated communication graph, and which encodes the limited communication capabilities between the team members. Similarly to the single integrator case, the convergence of the system relies on the connectivity of the communication graph.

A lifting-line code, CAMRAD II, and a Reynolds-Averaged Navier-Stokes code, OVERFLOW-D, were used to predict the aerodynamic performance of a two-bladed horizontal axis wind turbine. All computations were compared with experimental data that was collected at the NASA Ames Research Center 80-by-120-foot Wind Tunnel. Lifting-line computations were performed for both axial and yawed operating conditions while the Navier-Stokes computations were performed for only the axial conditions. Various stall delay models and dynamic stall models were used by the CAMRAD II code. For axial operating conditions, the predicted rotor performance varied significantly, particularly for stalled wind speeds. The lifting-line required the use of stall delay models to obtain the proper stall behavior, yet it still has difficulty in predicting the proper power magnitude in stall. The Navier-Stokes method captures the stall behavior and gives a detailed insight into the fluid mechanics of the stall behavior.

We consider a combined experimental (based on flow visualization, direct force measurement and phaseaveraged 2D particle image velocimetry in a water tunnel), computational (2D Reynolds-averaged Navier-Stokes) and theoretical (Theodorsen's formula) approach to study the fluid physics of rigid-airfoil pitch-plunge in nominally two-dimensional conditions. Shallow-stall (combined pitch-plunge) and deep-stall (pure-plunge) are compared at a reduced frequency commensurate with flapping-flight in cruise in nature. Objectives include assessment of how well attached-flow theory can predict lift coefficient even in the presence of significant separation, and how well 2D velocimetry and 2D computation can mutually validate one another. The shallow-stall case shows promising agreement between computation and experiment, while in the deepstall case, the computation's prediction of flow separation lags that of the experiment, but eventually evinces qualitatively similar leading edge vortex size. Dye injection was found to give good qualitative match with particle image velocimetry in describing leading edge vortex formation and return to flow reattachment, and also gave evidence of strong spanwise growth of flow separation after leadingedge vortex formation. Reynolds number effects, in the range of 10,000-60,000, were found to influence the size of laminar separation in those phases of motion where instantaneous angle of attack was well below stall, but have limited effect on post-stall flowfield behavior. Discrepancy in lift coefficient time history between experiment, theory and computation was mutually comparable, with no clear failure of Theodorsen's formula. This is surprising and encouraging, especially for the deep-stall case, because the theory's assumptions are clearly violated, while its prediction of lift coefficient remains useful for capturing general trends.

Large-eddy simulation (LES) of a liquid-fueled lean-direct injection (LDI) combustor is carried out by resolving the entire inlet flow path through the swirl vanes and the combustor. A localized dynamic subgrid closure is combined with a subgrid mixing and combustion model so that no adjustable parameters are required. The inflow spray is specified by a Kelvin-Helmholtz (or aerodynamic) breakup model and compared with LES without breakup, where the incoming spray is approximated using measured data just downstream of the injector. Overall, both time-averaged gas and droplet velocity predictions compare well with the measured data. The major impact of breakup is on fuel evaporation in the vicinity of the injector. Further downstream, a broad spectrum of drop sizes are recovered by the breakup simulation and produces spray quality, as in the no-breakup case. It is shown that the vortex breakdown bubble (VBB) is smaller with more intense reverse flow when there is heat release. The swirling shear layer plays a major role in spray dispersion and the VBB provides an efficient flame-holding mechanism to stabilize the flame. Unsteady features such as the efficient dispersion of the spray by the precessing vortex core (PVC) are well captured. Flame structure analysis using the Takeno flame index shows the presence of a diffusion flame in the central portion, whereas premixed burning mode is observed farther away. Instantaneous thermochemical states of fuel-air mixing and oxidation indicate significant departure from the gaseous diffusion limits, consistent with earlier observations. Additionally, particle-particle and particle-gas correlations are analyzed and discussed. (S. Menon).

Aerodynamic parameter estimation is an integral part of aerospace system design and life cycle process. Recent advances in computational power have allowed the use of online parameter estimation techniques in varied applications such as reconfigurable or adaptive control, system health monitoring, and fault tolerant control. The combined problem of state and parameter identification leads to a nonlinear filtering problem; furthermore, many aerospace systems are characterized by nonlinear models as well as noisy and biased sensor measurements. Extended Kalman filter (EKF) is a commonly used algorithm for recursive parameter identification due to its excellent filtering properties and is based on a first order approximation of the system dynamics. Recently, the unscented Kalman filter (UKF) has been proposed as a theoretically better alternative to the EKF in the field of nonlinear filtering and has received great attention in navigation, parameter estimation, and dual estimation problems. However, the use of UKF as a recursive parameter estimation tool for aerodynamic modeling is relatively unexplored. In this paper we compare the performance of three recursive parameter estimation algorithms for aerodynamic parameter estimation of two aircraft from real flight data. We consider the EKF, the simplified version of the UKF and the augmented version of the UKF. The aircraft under consideration are a fixed wing aircraft (HFB-320) and a rotary wing UAV (ARTIS). The results indicate that although the UKF shows a slight improvement in some cases, the performance of the three algorithms remains comparable.

Due to growing interest in wind energy harvesting offshore as well as in the urban environment, vertical axis wind turbines (VAWTs) have recently received renewed interest. Their omni-directional capability makes them a very interesting option for use with the frequently varying wind directions typically encountered in the built environment while their scalability and low installation costs make them highly suitable for offshore wind farms. However, they require further performance optimization to become competitive with horizontal axis wind turbines (HAWTs) as they currently have a lower power coefficient (CP). This can be attributed both to the complexity of the flow around VAWTs and the significantly smaller amount of research they have received. The pitch angle is a potential parameter to enhance the performance of VAWTs. The current study investigates the variations in loads and moments on the turbine as well as the experienced angle of attack, shed vorticity and boundary layer events (leading edge and trailing edge separation, laminar-to-turbulent transition) as a function of pitch angle using Computational Fluid Dynamics (CFD) calculations. Pitch angles of −7° to +3° are investigated using Unsteady Reynolds-Averaged Navier-Stokes (URANS) calculations while turbulence is modeled with the 4-equation transition SST model. The results show that a 6.6% increase in CP can be achieved using a pitch angle of −2° at a tip speed ratio of 4. Additionally, it is found that a change in pitch angle shifts instantaneous loads and moments between upwind and downwind halves of the turbine. The shift in instantaneous moment during the revolution for various pitch angles suggests that dynamic pitching might be a very promising approach for further performance optimization.

The genetic changes in marginal zone B cell lymphomas (MZBCL) vary according to the anatomical region. This study aimed to investigate genomic aberrations in ocular MZBCL and to compare them with those of tumors from other anatomical sites. The study population comprised 24 cases of primary ocular MZBCL, 11 pulmonary MZBCL, and seven nodal MZBCL. For array CGH, fresh tumor tissues were analyzed with a genome-wide scanning array containing 2,304 BAC/PAC clones which cover the whole human genome at a resolution of 1.3 Mb. FISH analysis for MALT1 gene alteration was performed for ocular and nodal MZBCL and RT-PCR for the detection of API2-MALT1 transcripts was performed for pulmonary MZBCL. The recurrent genomic alterations in ocular MZBCL were losses of chromosome bands 6q23.3 (9/24, 38%), 7q36.3 (2/24, 8%), and 13q34 (2/24, 8%), and gains of chromosomes 3 (9/24, 38%), and 15 (4/24, 16%), and chromosome arms 18q (4/24, 16%), and 6p (2/24, 8%). The t(11;18)(q21;q21) was not detected. The genomic alterations of pulmonary MZBCL included recurrent loss of 18q21 (2/11, 19%). A t(11;18)(q21;q21) fusion transcript was detected in five out of eight cases (63%). Nodal MZBCL showed neither recurrent genome alterations nor any change in MALT1 gene copy number. In conclusion, the array CGH profile of ocular MZBCL is distinct from those of pulmonary and nodal MZBCL. Deletion of chromosome band 6q23.3 in ocular MZBCL is a novel finding and may constitute a crucial genetic alteration in the pathogenesis of ocular MZBCL. © 2007 Wiley-Liss, Inc.

Over the last 30 years, Boeing has developed, manufactured, sold, and supported hundreds of billions of dollars worth of commercial airplanes. During this period, it has been absolutely essential that Boeing aerodynamicists have access to tools that accurately predict and confirm vehicle flight characteristics. Thirty years ago, these tools consisted almost entirely of analytic approximation methods, wind tunnel tests, and flight tests. With the development of increasingly powerful computers, numerical simulations of various approximations to the Navier-Stokes equations began supplementing these tools. Collectively, these numerical simulation methods became known as Computational Fluid Dynamics (CFD). This paper describes the chronology and issues related to the acquisition, development, and use of CFD at Boeing Commercial Airplanes in Seattle. In particular, it describes the evolution of CFD from a curiosity to a full partner with established tools in the design of cost-effective and high-performing commercial transports.

A biomechanically parsimonious hypothesis for the evolution of flapping flight in terrestrial vertebrates suggests progression within an arboreal context from jumping to directed aerial descent, gliding with control via appendicular motions, and ultimately to powered flight. The more than 30 phylogenetically independent lineages of arboreal vertebrate gliders lend strong indirect support to the ecological feasibility of such a trajectory. Insect flight evolution likely followed a similar sequence, but is unresolved paleontologically. Recently described falling behaviors in arboreal ants provide the first evidence demonstrating the biomechanical capacity for directed aerial descent in the complete absence of wings. Intentional control of body trajectories as animals fall from heights (and usually from vegetation) likely characterizes many more taxa than is currently recognized. Understanding the sensory and biomechanical mechanisms used by extant gliding animals to control and orient their descent is central to deciphering pathways involved in flight evolution.

The Ahmed reference body represents a simplified car geometry that can be used to investigate the main flow features in the wake of vehicles. The present work presents unsteady flow simulations at the rear slant angles 25°and 35°using the PowerFLOW 4.0 D3Q19 lattice Boltzmann model. The flow of the wake is discussed and distributions of averaged pressure and velocities are compared with available experimental findings. The resolution requirement is investigated in terms of computational requirement and accuracy achieved. The predictive capability and the feasibility of the very large eddy simulation (VLES) approach within the lattice Boltzmann framework is demonstrated.

Wind turbines operate in the surface layer of the atmospheric boundary layer, where they are subjected to strong wind shear and relatively high turbulence levels. These incoming boundary layer flow characteristics are expected to affect the structure of wind turbine wakes. The near-wake region is characterized by a complex coupled vortex system (including helicoidal tip vortices), unsteadiness and strong turbulence heterogeneity. Limited information about the spatial distribution of turbulence in the near wake, the vortex behavior and their influence on the downwind development of the far wake hinders our capability to predict wind turbine power production and fatigue loads in wind farms. This calls for a better understanding of the spatial distribution of the 3D flow and coherent turbulence structures in the near wake. Systematic wind-tunnel experiments were designed and carried out to characterize the structure of the near-wake flow downwind of a model wind turbine placed in a neutral boundary layer flow. A horizontal-axis, three-blade wind turbine model, with a rotor diameter of 13 cm and the hub height at 10.5 cm, occupied the lowest one-third of the boundary layer. High-resolution particle image velocimetry (PIV) was used to measure velocities in multiple vertical stream-wise planes (x–z) and vertical span-wise planes (y–z). In particular, we identified localized regions of strong vorticity and swirling strength, which are the signature of helicoidal tip vortices. These vortices are most pronounced at the top-tip level and persist up to a distance of two to three rotor diameters downwind. The measurements also reveal strong flow rotation and a highly non-axisymmetric distribution of the mean flow and turbulence structure in the near wake. The results provide new insight into the physical mechanisms that govern the development of the near wake of a wind turbine immersed in a neutral boundary layer. They also serve as important data for the development and validation of numerical models.