Applications of Low-Speed Dynamic-Stall Model to the NREL Airfoils

2009 ◽  
Vol 132 (1) ◽  
Author(s):  
Wanan Sheng ◽  
Roderick A. McD. Galbraith ◽  
Frank N. Coton
Keyword(s):  
Wind Turbine ◽  
Power Level ◽  
Leading Edge ◽  
Dynamic Stall ◽  
State University ◽  
Low Speed ◽  
Helicopter Blades ◽  
Mach Numbers ◽  
The Ohio State University ◽  
Low Sensitivity

National Renewable Energy Laboratory, USA (NREL) airfoils have been specially developed for wind turbine applications, and projected to yield more annual energy without increasing the maximum power level. These airfoils are designed to have a limited maximum lift and relatively low sensitivity to leading-edge roughness. As a result, these airfoils have quite different leading-edge profiles from airfoils applied to helicopter blades, and thus, quite different dynamic-stall characteristics. Unfortunately for wind turbine aerodynamics, the dynamic-stall models in use are still those specially developed and refined for helicopter applications. A good example is the Leishman–Beddoes dynamic-stall model, which is one of the most popular models in wind turbine applications. The consequence is that the application of such dynamic-stall model to low-speed cases can be problematic. Recently, some specific dynamic-stall models have been proposed or tuned for the cases of low Mach numbers, but their universality needs further validation. This paper considers the application of the modified dynamic low-speed stall model of Sheng et al. (“A Modified Dynamic Stall Model for Low Mach Numbers,” 2008, ASME J. Sol. Energy Eng., 130(3), pp. 031013) to the NREL airfoils. The predictions are compared with the data of the NREL airfoils tested at the Ohio State University. The current research has two objectives: to justify the suitability of the low-speed dynamic-stall model, and to provide the relevant parameters for the NREL airfoils.

Casing Treatment and Blade-Tip Configuration Effects on Controlled Gas Turbine Blade Tip/Shroud Rubs at Engine Conditions

2010 ◽  
Vol 133 (1) ◽  
Author(s):  
Corso Padova ◽  
Michael G. Dunn ◽  
Jeffery Barton ◽  
Kevin Turner ◽  
Alan Turner ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Computational Models ◽  
Leading Edge ◽  
State University ◽  
Casing Treatment ◽  
Bare Steel ◽  
Blade Tip ◽  
The Ohio State University ◽  
Force Components ◽  
Detailed Interpretation

Experimental results obtained for an Inconel® compressor blade rubbing bare-steel and treated casings at engine speed are described. Since 2002 a number of experiments were conducted to generate a broad database for tip rubs, the Rotor-Blade Rub database obtained using the unique experimental facility at the The Ohio State University Gas Turbine Laboratory. As of 2007, there are seven completed groups of measurements in the database. Among them a number of blade-tip geometries and casing surface treatments have been investigated. The purpose of this paper is to provide a detailed interpretation of this database. Load cell, strain, temperature, and accelerometer measurements are discussed and then applied to analyze the interactions resulting from progressive and sudden incursions of varying severity, defined by incursion depths ranging from 13 μm to 762 μm (from 0.0005 in. to 0.030 in.). The influence of blade-tip speed on these measurements is described. The results presented describe the dynamics of rotor and casing vibro-impact response at representative operational speeds similar to those experienced in flight. Force components at the blade tip in the axial and circumferential directions are presented for rub incursions ranging in depth from very light (13 μm) to severe (406 μm). Trends of variation are observed during metal-to-metal and metal-to-abradable contacts for two airfoil tip shapes and tip speeds 390 m/s (1280 ft/s) and 180 m/s (590 ft/s). The nonlinear nature of the rub phenomena reported in earlier work is confirmed. In progressing from light rubs to higher incursion, the maximum incurred circumferential load increases significantly while the maximum incurred axial load increases much less. The manner in which casing surface treatment affects the loads is presented. Concurrently, the stress magnification on the rubbing blade at root midchord, at tip leading edge, and at tip trailing edge is discussed. Computational models to analyze the nonlinear dynamic response of a rotating beam with periodic pulse loading at the free-end are currently under development and are noted.

Modification of the NACA 632-415 Leading Edge for Better Aerodynamic Performance

2002 ◽  
Vol 124 (4) ◽  
pp. 327-334 ◽  
Author(s):  
Christian Bak ◽  
Peter Fuglsang
Keyword(s):  
Wind Tunnel ◽  
Wind Turbines ◽  
Power Level ◽  
Leading Edge ◽  
Aerodynamic Characteristics ◽  
Dynamic Stall ◽  
Wind Tunnel Tests ◽  
Damping Characteristics ◽  
Edge Roughness ◽  
Drag Ratio

Double stall causes more than one power level when stall-regulated wind turbines operate in stall. This involves significant uncertainty on power production and loads. To avoid double stall, a new leading edge was designed for the NACA 632-415 airfoil, an airfoil that is often used in the tip region of wind turbines. A numerical optimization tool incorporating XFOIL was used with a special formulation for the airfoil leading edge shape. The EllipSys2D CFD code was used to analyze the modified airfoil. In theory and in wind tunnel tests, the modified airfoil showed smooth and stable stall characteristics with no tendency to double stall. Also, both theory and wind tunnel tests showed that the overall aerodynamic characteristics were similar to NACA 632-415 except for an increase in the lift-drag ratio below maximum lift and an increase in maximum lift. The wind tunnel tests showed that dynamic stall and aerodynamic damping characteristics for the modified airfoil and the NACA 632-415 airfoil were the same. The modified airfoil with leading edge roughness in general had better characteristics compared with the NACA 632-415 airfoil.

Dynamic stall control on a vertical axis wind turbine aerofoil using leading-edge rod

Energy ◽  
2019 ◽  
Vol 174 ◽  
pp. 246-260 ◽  
Author(s):  
Junwei Zhong ◽  
Jingyin Li ◽  
Penghua Guo ◽  
Yu Wang
Keyword(s):  
Wind Turbine ◽  
Leading Edge ◽  
Vertical Axis ◽  
Dynamic Stall ◽  
Vertical Axis Wind Turbine ◽  
Stall Control

CALCULATION OF THE UNSTEADY AIRLOADS ON WIND TURBINE BLADES UNDER YAWED FLOW

2009 ◽  
Vol 23 (03) ◽  
pp. 493-496 ◽  
Author(s):  
HAI-QING SI ◽  
TONG-GUANG WANG
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Leading Edge ◽  
Aerodynamic Characteristics ◽  
Dynamic Stall ◽  
Dependent Manner ◽  
Wind Turbine Blades ◽  
Blade Element Momentum Theory ◽  
Momentum Theory ◽  
Blade Element

A dynamic stall model is coupled with the blade element momentum theory to calculate the cyclic variation of the aerodynamic characteristics of the wind turbine in yawed flow. In the dynamic stall model, unsteady effects under attached flow conditions are simulated by the superposition of indicial aerodynamic responses. The movement of the unsteady flow separation point is related to the static separation based on the Kirchhoff flow model via a deficiency function, in which the unsteady boundary layer response and the leading edge pressure response are taken into consideration. The induced vortex force and the associated pitching moment are represented empirically in a time-dependent manner during dynamic stall. The required input of the inflow velocity and incidence to the dynamic stall model is calculated using the improved blade element momentum theory. The calculated results are compared well with the NREL UAE Phase VI experimental data. For completeness, possible factors causing the difference between calculated and experimental results are analyzed and discussed in detail in this paper.

A Modified Dynamic Stall Model for Low Mach Numbers

2008 ◽  
Vol 130 (3) ◽  
Author(s):  
W. Sheng ◽  
R. A. McD. Galbraith ◽  
F. N. Coton
Keyword(s):  
Mach Number ◽  
Wind Turbine ◽  
Experimental Results ◽  
Dynamic Stall ◽  
Modified Model ◽  
Wind Turbine Aerodynamics ◽  
Mach Numbers ◽  
The University

The Leishman–Beddoes dynamic stall model is a popular model that has been widely applied in both helicopter and wind turbine aerodynamics. This model has been specially refined and tuned for helicopter applications, where the Mach number is usually above 0.3. However, experimental results and analyses at the University of Glasgow have suggested that the original Leishman–Beddoes model reconstructs the unsteady airloads at low Mach numbers less well than at higher Mach numbers. This is particularly so for stall onset and the return from the fully stalled state. In this paper, a modified dynamic stall model that adapts the Leishman–Beddoes dynamic stall model for lower Mach numbers is proposed. The main modifications include a new stall-onset indication, a new return modeling from stalled state, a revised chordwise force, and dynamic vortex modeling. The comparisons to the Glasgow University dynamic stall database showed that the modified model is capable of giving improved reconstructions of unsteady aerofoil data in low Mach numbers.

Five Decades of Research Experience in Speech Anatomy and Physiology

2016 ◽  
Vol 1 (5) ◽  
pp. 4-12
Author(s):  
David P. Kuehn
Keyword(s):  
Ohio State University ◽  
State University ◽  
Research Experience ◽  
University Of Iowa ◽  
University Of Illinois ◽  
Anatomy And Physiology ◽  
The Ohio State University ◽  
Speech Science ◽  
The University ◽  
East Carolina University

This report highlights some of the major developments in the area of speech anatomy and physiology drawing from the author's own research experience during his years at the University of Iowa and the University of Illinois. He has benefited greatly from mentors including Professors James Curtis, Kenneth Moll, and Hughlett Morris at the University of Iowa and Professor Paul Lauterbur at the University of Illinois. Many colleagues have contributed to the author's work, especially Professors Jerald Moon at the University of Iowa, Bradley Sutton at the University of Illinois, Jamie Perry at East Carolina University, and Youkyung Bae at the Ohio State University. The strength of these researchers and their students bodes well for future advances in knowledge in this important area of speech science.

Selection of a leading edge noise prediction method for PNoise

2018 ◽  
pp. 214-223
Author(s):  
AM Faria ◽  
MM Pimenta ◽  
JY Saab Jr. ◽  
S Rodriguez
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Prediction Method ◽  
Leading Edge ◽  
Wind Farms ◽  
Broadband Noise ◽  
Turbulence Energy ◽  
Noise Prediction ◽  
Migration Routes ◽  
Turbulent Inflow

Wind energy expansion is worldwide followed by various limitations, i.e. land availability, the NIMBY (not in my backyard) attitude, interference on birds migration routes and so on. This undeniable expansion is pushing wind farms near populated areas throughout the years, where noise regulation is more stringent. That demands solutions for the wind turbine (WT) industry, in order to produce quieter WT units. Focusing in the subject of airfoil noise prediction, it can help the assessment and design of quieter wind turbine blades. Considering the airfoil noise as a composition of many sound sources, and in light of the fact that the main noise production mechanisms are the airfoil self-noise and the turbulent inflow (TI) noise, this work is concentrated on the latter. TI noise is classified as an interaction noise, produced by the turbulent inflow, incident on the airfoil leading edge (LE). Theoretical and semi-empirical methods for the TI noise prediction are already available, based on Amiet’s broadband noise theory. Analysis of many TI noise prediction methods is provided by this work in the literature review, as well as the turbulence energy spectrum modeling. This is then followed by comparison of the most reliable TI noise methodologies, qualitatively and quantitatively, with the error estimation, compared to the Ffowcs Williams-Hawkings solution for computational aeroacoustics. Basis for integration of airfoil inflow noise prediction into a wind turbine noise prediction code is the final goal of this work.

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