Simulation of aeroelastic behavior in a composite wind turbine blade

Rafiee, Roham; Tahani, Mojtaba; Moradi, Mohsen

doi:10.1016/j.jweia.2016.01.010

Cited by 65 publications

(28 citation statements)

References 32 publications

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“…Table 2 shows properties of the composites [12]. 5 ] X , where X is the number of sets needed to attain a desired thickness. The layups are selected to produce different level of coupling.…”

Section: Blade Internal Structurementioning

confidence: 99%

“…Mirror layups of the blade shells produced an induced twist toward stall and improved in the energy capture by 15.5%. Another Fluid-Structure Interaction approach used BEM to calculate the aerodynamic loads and used 3D FEA to predict the deformation of the blade [5]. This iterative analysis showed that the deflection of the blade reduces the power output.…”

Section: Introductionmentioning

confidence: 99%

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Effects of Bend-Twist Coupling Deformation on the Aerodynamic Performance of a Wind Turbine Blade

Sompong¹

2017

GEOMATE

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ABSTRACT:Comprehensive research exists on passive pitch control of wind turbines using bend-twist coupling property of composite materials. Blades with bend-twist coupling deformation can increase energy capture, improve dynamic stability, or reduce aerodynamic loads. The objectives of this work are to apply bend-twist coupling into an existing blade design and to investigate the resulting aerodynamic performance. The 41.25-meter blade was based on GE 1.5 GLX wind turbine. Aerodynamic loads were calculated using Blade Element Momentum (BEM) theory and Computational Fluid Dynamics (CFD) simulation. The resultant thrust and torque from both methods agree well. However, only the CFD can provide details of pressure distribution over the complex blade surface. Three levels of bend-twist coupling were designed for the Glass/Epoxy blade skins i.e. no coupling, low coupling, and high coupling. From Finite Element Analysis (FEA), the deflections of the three blades were slightly different while the twist angles were considerably different. The deformed geometries of the blades were then used to produce new three dimensional (3D) models for the prediction of the power coefficient (C P ) by CFD. The results show that the proper bend-twist coupling laminate can improve the performance of the blade. At low wind speed, the C P is higher than the baseline blade. At wind speed greater than rated speed, however, the blades twist two much and the C P decreases below the baseline blade. Simulation of 3D blade models can help in the design of a bend-twist coupling level suitable to the blade shape and wind speed.

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Section: Blade Internal Structurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effects of Bend-Twist Coupling Deformation on the Aerodynamic Performance of a Wind Turbine Blade

Sompong¹

2017

GEOMATE

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“…Aeroelastic stability analysis of a full-scale composite blade has been investigated, with the aerodynamic loading determined using modified Blade Element momentum (BEM) theory and CFD method. Then, a 3D FEM was built using the iterative approach of fluid-structure interaction (FSI) to investigate the aeroelastic behavior [7]. After linearizing the nonlinear equations of the wind turbine blades, the active control of the optimal proportional-integral-derivative (PID) control method and the optimized linear quadratic regulator (LQR) are proposed to suppress the flap-wise and lead-lag flutter.…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Control of Active Trailing-Edge Flap Based on Adaptive Reaching Law and Minimum Parameter Learning of Neural Networks

et al. 2020

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Theoretical modeling and the sliding mode control (SMC) of an active trailing-edge flap of a wind turbine blade based on the adaptive reaching law are investigated. The blade is a single-celled thin-walled composite structure using circumferentially asymmetric stiffness (CAS) design, exhibiting displacements of flap-wise/twist coupling. A reduced structural model originated from the variation method is used to model the structure of the blade, the structural damping of which is computed. The trailing-edge flap is a rigid structure that is embedded in and hinged to the blade host structure, and it is driven by two pairs of pneumatic cylinders moving in reverse. Flutter suppression for the large-amplitude vibration of the blade tip is investigated based on an active trailing-edge flap structure and SMC algorithm using the adaptive reaching law. The controlled responses of flap-wise/twist displacements and control inputs (the angles of the trailing-edge flap) are illustrated, with obvious simulation effects demonstrated. An experimental platform for driving the pneumatic cylinders verifies the effectiveness of the control algorithm using the adaptive reaching law and the effectiveness of the selected pneumatic transmission scheme controlled by another adaptive SMC based on the minimum parameter learning of neural networks.

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“…Simulation of aero-elastic behavior in a composite wind turbine blade was studied by Rafieeet. al [10]. Aero-elastic analysis of a full scale composite wind turbine blade was investigated using 3D model and aerodynamic loading was determined using modified Blade Element Momentum (BEM) theory and Computational Fluid Dynamics (CFD) method.…”

Section: Introductionmentioning

confidence: 99%

Research on Hyper pipes and Voting Feature Intervals Classifier for Condition Monitoring of Wind Turbine Blades using Vibration Signals

2019

IJRTE

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Renewable energy is viewed as a vital energy field due to the present energy devastations. Among the vital substitutions being considered, wind energy is a strong challenger as a result of its reliability. “To yield wind energy more effectively, the structure of wind turbines has designed bigger, making protection and restoration works difficult. Because of different natural conditions, wind turbine blades are exposed to vibration and it prompts failure. If the failure is not analyzed initially, then it will haste dreadful destruction of the turbine structure. To increase safety perceptions, to decrease down time and to cut down the repeat of unpredictable breakdowns, the wind turbine blades must be examined from time to time to guarantee that they are in great condition. In this paper, a three bladed wind turbine was preferred and using vibration source through statistical features, the state of a wind turbine blade is inspected. The fault classification is carried out using machine learning techniques like hyperpipes (HP) and voting feature intervals (VFI) algorithm. The performance of these algorithms is compared and better algorithm is suggested for fault prediction on wind turbine blades.”

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Simulation of aeroelastic behavior in a composite wind turbine blade

Cited by 65 publications

References 32 publications

Effects of Bend-Twist Coupling Deformation on the Aerodynamic Performance of a Wind Turbine Blade

Effects of Bend-Twist Coupling Deformation on the Aerodynamic Performance of a Wind Turbine Blade

Sliding Mode Control of Active Trailing-Edge Flap Based on Adaptive Reaching Law and Minimum Parameter Learning of Neural Networks

Research on Hyper pipes and Voting Feature Intervals Classifier for Condition Monitoring of Wind Turbine Blades using Vibration Signals

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