Pitching moment

About: Pitching moment is a research topic. Over the lifetime, 3213 publications have been published within this topic receiving 38721 citations.

High-Lift Optimization Design Using Neural Networks on a Multi-Element Airfoil

Abstract: Roxana M. GreenmanAerospace EngineerNASA Ames Research CenterMoffett Field, California 94035-1000, U. S. A.Tel: 650-604-3997, Fax: 650-604-2238E-mail: rgreenman@mail.arc.nasa.govKarlin R. RothAerospace EngineerNASA Ames Research CenterMoffett Field, California 94035-1000, U. S. A.Tel: 650-604-6678, Fax: 650-604-2238E-mail: kroth@mail.arc.nasa.govABSTRACTThe high-lift performance of a multi-element airfoil wasoptimized by using neural-net predictions that were trainedusing a computational data set. The numerical data was gener-ated using a two-dimensional, incompressible, Navier-Stokesalgorithm with the Spaiart-Allmaras turbulence model. Becauseit is difficult to predict maximum lift for high-lift systems, anempirically-based maximum lift criteria was used in this studyto detemaine both the maximum lift and the angle at which itoccurs. Multiple input, single output networks were trainedusing the NASA Ames variation of the Levenherg-Marquardtalgorithm for each of the aerodynamic coefficients (lift, drag,and moment). The artificial neural networks were integratedwith a gradient-based optimizer. Using independent numericalsimulations and experimental data for this high-lift configura-tion, it was shown that this design process successfully opti-mized flap deflection, gap, overlap, and angle of attack tomaximize lift. Once the neural networks were trained and inte-grated with the optimizer, minimal additional computerresources were required to perform optimization runs with dif-ferent initial conditions and parameters. Applying the neuralnetworks within the high-lift rigging optimization processreduced Me amount of computational time and resources by83% compared with traditional gradient-based optimization pro-cedures for multiple optimization runs.NOMENCLATURECa drag coefficient, C a - D/(q_c)Ct lift coefficient, C l - L/(q=c)C m moment coefficient, C,. --M/(q=c 2)C e.,is

Aerodynamics Analysis of Small Horizontal Axis Wind Turbine Blades by Using 2D and 3D CFD Modelling

Abstract: Please write a brief description of your work, or copy an abstract you have included in the Thesis Wind power is one of the most important sources of renewable energy. Wind-turbines extract kinetic energy from the wind. Currently much research has concentrated on improving the aerodynamic performance of wind turbine blade through wind tunnel testing and theoretical studies. These efforts are much time consuming and need expensive laboratory resources. However, wind turbine simulation through Computational Fluid Dynamics (CFD) software offers inexpensive solutions to aerodynamic blade analysis problem. In this study, two-dimensional aerofoil (i.e. DU-93 and NREL-S809) CFD models are presented using ANSYS-FLUENT software. Using the Spalart-Allmaras turbulent viscosity, the dimensionless lift, drag and pitching moment coefficients were calculated for wind-turbine blade at different angles of attack. These CFD model values we then validated using published calibrated lift and drag coefficients evident in the literature. Optimum values of these coefficients as well as a critical angle were found from polar curves of lift, drag and moment modelling data. These data were exploited in order to select the aerofoil with best aerodynamic performance for basis of a three-decisional model analogue. Thereafter a three-dimensional CFD model of small horizontal axis wind-turbine was produced. The numerical solution was carried out by simultaneously solving the three-dimensional continuity, momentum and the Naveir-Stokes equations in a rotating reference frame using a standard non-linear k-ω solver so that the rotational effect can be studied. These three-dimensional models were used for predicting the performance of a small horizontal axis wind turbine. Moreover, the analysis of wake effect and aerodynamic noise can be carried out when the rotational effect was simulated.

Post stall studies of untwisted varying aspect ratio blades with an NACA 4415 airfoil section. Part I

Abstract: Wind Turbine blades operate over a wide angle of attack range. Unlike aircraft, a wind turbine's angle of attack range extends deep into stall where the three dimensional performance characteristics of air foils are not generally known. Peak power predictions upon which wind turbine components are sized, depend on a good understanding of a blade's post stall characteristics. The results of the wind tunnel investigation of untwisted, constant chord blades having four aspect ratios, with an NACA 4415 series airfoil section, at angles of attack ranging from -10 to 100 degrees are discussed. Tests were conducted for aspect ratios of 6, 9, 12 and infinity at four Reynolds numbers ranging from one-quarter million to one million. The results on the same family of airfoil section but with varying thickness ratio are given. Results of force and pitching moment measurements over the angle of attack range for all combinations of Reynolds numbers and aspect ratios, and the effects of boundary layer tripping, are presented. Both initial and secondary stall are presented. The maximum drag coefficient is found to occur an an angle of attack of 90 degrees. The pitching moment is unstable beyond stall. The lift and post-stall drag-coefficients decrease with decreasing aspect ratio. The boundary layer tripping is observed to decrease the lift curve slope and stalling angle of attack. The drag coefficient (with tripping) is significantly affected only at low aspect ratio. Beyond secondary stall, the lift to drag ratio is independent of aspect ratio. The maximum lift to drag ratio for the infinite aspect ratio blade is roughly twice that of the blade with an aspect ratio of six. This effect is independent of Reynolds number in the range studied.

A non-linear aeroelastic model for the study of flapping-wing flight

Abstract: A = element cross-sectional area AR = aspect ratio a = mass-proportional damping constant b = stiffness-proportional damping constant Cd = drag coefficient Cdf = skin-friction drag coefficient Cmac = airfoil moment coefficient about its aerodynamic center Cn = normal force coefficient c = wing segment chord length Dc = drag due to camber Df = friction drag E = modulus of elasticity Fy = total chordwise force F'(k), G'(k) = terms for modified Theodorsen function G = shear modulus of elasticity gr = acceleration due to gravity h = total plunging displacement h = elastic component of plunging displacement hQ imposed displacement / = moment of inertia J = polar moment of inertia k = reduced frequency based on | c L = total lift M = total twisting moment acting on a wing segment