Rotor airfoil profile optimization for alleviating dynamic stall characteristics

Wang, Qing; Zhao, Qijun

doi:10.1016/j.ast.2017.11.033

Cited by 33 publications

(8 citation statements)

References 16 publications

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“…Gradient-based optimization (GBO), a local search approach, is commonly used for ASO. Recently, Wang et al (2015), Wang and Zhao (2018) alleviated the dynamic stall characteristics on rotor airfoil by using sequential quadratic programming (SQP). A more efficient GBO approach using the adjoint-based method (Jameson, 2003) is also implemented for ASO-based dynamic stall mitigation (Wong et al, 2006;Nadarajah and Jameson, 2007;Mani et al, 2012;Economon et al, 2015), mainly due to the efficient computation of gradients and its ability to handle high-dimensional optimization problems (Laurenceau and Meaux, 10th April 2008).…”

Section: Introductionmentioning

confidence: 99%

Multifidelity modeling similarity conditions for airfoil dynamic stall prediction with manifold mapping

Raul

Leifsson

2021

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PurposeThe purpose of this work is to investigate the similarity requirements for the application of multifidelity modeling (MFM) for the prediction of airfoil dynamic stall using computational fluid dynamics (CFD) simulations.Design/methodology/approachDynamic stall is modeled using the unsteady Reynolds-averaged Navier–Stokes equations and Menter's shear stress transport turbulence model. Multifidelity models are created by varying the spatial and temporal discretizations. The effectiveness of the MFM method depends on the similarity between the high- (HF) and low-fidelity (LF) models. Their similarity is tested by computing the prediction error with respect to the HF model evaluations. The proposed approach is demonstrated on three airfoil shapes under deep dynamic stall at a Mach number 0.1 and Reynolds number 135,000.FindingsThe results show that varying the trust-region (TR) radius (λ) significantly affects the prediction accuracy of the MFM. The HF and LF simulation models hold similarity within small (λ ≤ 0.12) to medium (0.12 ≤ λ ≤ 0.23) TR radii producing a prediction error less than 5%, whereas for large TR radii (0.23 ≤ λ ≤ 0.41), the similarity is strongly affected by the time discretization and minimally by the spatial discretization.Originality/valueThe findings of this work present new knowledge for the construction of accurate MFMs for dynamic stall performance prediction using LF model spatial- and temporal discretization setup and the TR radius size. The approach used in this work is general and can be used for other unsteady applications involving CFD-based MFM and optimization.

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Section: Introductionmentioning

confidence: 99%

Multifidelity modeling similarity conditions for airfoil dynamic stall prediction with manifold mapping

Raul

Leifsson

2021

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“…By comparing the original B-L model for an S809 type airfoil oscillating in pitch mode for different mean angles of attack, oscillation amplitudes, and reduced frequencies, they found that the modified B-L model showed better performance. Wang and Zhao (8) used a highly efficient optimization method to alleviate the dynamic stall characteristics of a rotor airfoil. They experimentally found that the optimized airfoil had a larger leading edge radius than an OA209 airfoil.…”

Section: Introductionmentioning

confidence: 99%

Influence of Oscillation Frequency and Nonlinear Structural Material of Airfoil in Wind Turbine System During Dynamic Stall

Wang¹,

Mishra²

2021

Sensors and Materials

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We study the nonlinear behavior of a wind turbine airfoil oscillating along the pitch mode of oscillation. In the analysis, the nonlinearity of the structural material, the airspeed, and the reduced frequency of oscillation are the important parameters considered. The equation of motion for the pitching oscillation case is modeled and derived using the Office National d'Etudes et de Recherches Aérospatiales (ONERA) dynamic stall model. In the ONERA dynamic stall model, the aerodynamic loads are given in terms of differential equations. We focus on the influence of the material structural nonlinearity and nondimensional airspeed on the wind turbine airfoil during the pitch mode of oscillation. The type of airfoil considered is the National Advisory Committee for Aeronautics (NACA) 0012 airfoil. To understand the effects of dynamic stall on the system under different situations of structural nonlinearity, we use bifurcation plots, phase plots, Poincaré maps, and the maximum Lyapunov exponent (MLE) to analyze the behavior of the airfoil and avoid the effect of non-periodic motion of the airfoil on the wind turbine system. The results show that chaos occurs for specific parameters of the airfoil of the wind turbine, which can be avoided by avoiding certain operating conditions corresponding to chaotic motion. This finding can be used as a guideline for wind turbine design and decrease the cost of maintenance.

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“…The addition of structures and control systems to the wind turbines increases their mass as well as their cost and complexity. Mitigating the adverse dynamic stall characteristics passively through aerodynamic shape optimization (ASO) has recently received interest from multiple researchers offering promising improvement in airfoil performance [12,16,23,24,26]. ASO studies for dynamic stall mitigation are typically done with adjoint-based computational fluid dynamics (CFD) simulations [4,12,16,26] and have shown promising results for multiple dynamic stall optimization cases.…”

Section: Introductionmentioning

confidence: 99%

“…The GBO approach, however, can get easily get stuck in local minima, especially if the CFD data is noisy. Wang et al [23,24] used sequential quadratic programming (SQP) to alleviate aerodynamic loads during dynamic stall cycle on rotor airfoils.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic Shape Optimization for Delaying Dynamic Stall of Airfoils by Regression Kriging

Raul¹,

Leifsson²,

Kozieł³

2020

Lecture Notes in Computer Science

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The phenomenon of dynamic stall produce adverse aerodynamic loading which can adversely affect the structural strength and life of aerodynamic systems. Aerodynamic shape optimization (ASO) provides an effective approach for delaying and mitigating dynamic stall characteristics without the addition of auxiliary system. ASO, however, requires multiple evaluations time-consuming computational fluid dynamics models. Metamodel-based optimization (MBO) provides an efficient approach to alleviate the computational burden. In this study, the MBO approach is utilized for the mitigation of dynamic stall characteristics while delaying dynamic stall angle of the flow past wind turbine airfoils. The regression Kriging metamodeling technique is used to approximate the objective and constrained functions. The airfoil shape design variables are described with six PARSEC parameters. A total of 60 initial samples are used to construct the metamodel, which is further refined with 20 infill points using expected improvement. The metamodel is validated with the normalized root mean square error based on 20 test data samples. The refined metamodel is used to search for the optimal design using a multi-start gradient-based method. The results show that an optimal design with a 3 • delay in dynamic stall angle as well a reduction in the severity of pitching moment coefficients can be obtained.

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Rotor airfoil profile optimization for alleviating dynamic stall characteristics

Cited by 33 publications

References 16 publications

Multifidelity modeling similarity conditions for airfoil dynamic stall prediction with manifold mapping

Multifidelity modeling similarity conditions for airfoil dynamic stall prediction with manifold mapping

Influence of Oscillation Frequency and Nonlinear Structural Material of Airfoil in Wind Turbine System During Dynamic Stall

Aerodynamic Shape Optimization for Delaying Dynamic Stall of Airfoils by Regression Kriging

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