Numerical and experimental investigations of wind-turbine blade aerodynamics in the presence of ice accretion

Knobbe-Eschen, Henry; Stemberg, Jochen; Abdellaoui, Khalid; Altmikus, Andree; Knop, Inken; Bansmer, Stefan; Balaresque, Nicholas; Suhr, Janick

doi:10.2514/6.2019-0805

Cited by 6 publications

(3 citation statements)

References 3 publications

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“…The table reveals that there is a gap when it comes to datasets that can be used for the validation of predicting aerodynamic icing penalties at low Reynolds numbers. The existing datasets in the literature lack well-defined experimental ice geometries [22][23][24], have no or limited performance data [25,26], offer only one data point for lift and drag for each icing case [27,28], or are performed at low or high Reynolds numbers [16,29]. Additionally, none of these datasets share the coordinates of the ice geometries or the tabularized data of lift and drag.…”

Section: Introductionmentioning

confidence: 99%

Experimental and Numerical Icing Penalties of an S826 Airfoil at Low Reynolds Numbers

et al. 2020

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Most icing research focuses on the high Reynolds number regime and manned aviation. Information on icing at low Reynolds numbers, as it is encountered by wind turbines and unmanned aerial vehicles, is less available, and few experimental datasets exist that can be used for validation of numerical tools. This study investigated the aerodynamic performance degradation on an S826 airfoil with 3D-printed ice shapes at Reynolds numbers Re = 2 × 105, 4 × 105, and 6 × 105. Three ice geometries were obtained from icing wind tunnel experiments, and an additional three geometries were generated with LEWICE. Experimental measurements of lift, drag, and pressure on the clean and iced airfoils have been conducted in the low-speed wind tunnel at the Norwegian University of Science and Technology. The results showed that the icing performance penalty correlated to the complexity of the ice geometry. The experimental data were compared to computational fluid dynamics (CFD) simulations with the RANS solver FENSAP. Simulations were performed with two turbulence models (Spalart Allmaras and Menter’s k-ω SST). The simulation data showed good fidelity for the clean and streamlined icing cases but had limitations for complex ice shapes and stall.

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Section: Introductionmentioning

confidence: 99%

Experimental and Numerical Icing Penalties of an S826 Airfoil at Low Reynolds Numbers

et al. 2020

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“…Numerous research studies have been conducted to improve the understanding of ice formation and how ice accretion changes with variations in meteorological parameters. Some examples can be found in references [7,12,13,18,19,[43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58], and the consequences for energy production in [19,50,[59][60][61]. Better comprehension and quantification of losses due to icing is crucial for developers and investors in wind farms who have to correctly estimate a project's expected energy generation to quantify its risks and evaluate its financial viability [50].…”

Section: Estimating Power Loss In Wind Turbines Under Icing Conditionsmentioning

confidence: 99%

A Review on the Estimation of Power Loss Due to Icing in Wind Turbines

2022

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The objective of this article is to review the methodologies used in the last 15 years to estimate the power loss in wind turbines due to their exposure to adverse meteorological conditions. Among the methods, the use of computational fluid dynamics (CFD) for the three-dimensional numerical simulation of wind turbines is highlighted, as well as the use of two-dimensional CFD simulation in conjunction with the blade element momentum theory (BEM). In addition, a brief review of other methodologies such as image analysis, deep learning, and forecasting models is also presented. This review constitutes a baseline for new investigations of the icing effects on wind turbines’ power outputs. Furthermore, it contributes to a continuous improvement in power-loss prediction and the better response of icing protection systems.

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“…However, using these two programs, various investigations have devised approaches for replicating ice accumulation on wind turbine blades [15,[26][27][28]. Homola et al [29] employed FENSAP-ICE to anticipate the formation of ice on the airfoils of the NREL 5MW benchmark wind turbine.…”

Section: Introductionmentioning

confidence: 99%

Influence of Surface Roughness Modeling on the Aerodynamics of an Iced Wind Turbine S809 Airfoil

Contreras Montoya,

Ilinca,

Lain

2023

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Ice formation on structures like wind turbine blade airfoils significantly reduces their aerodynamic efficiency. The presence of ice on airfoils causes deformation in their geometry and an increase in their surface roughness, enhancing turbulence, particularly on the suction side of the airfoil at high angles of attack. An approach for understanding this phenomenon and assessing its impact on wind turbine operation is modeling and simulation. In this contribution, a computational fluid dynamics (CFD) study is conducted using FENSAP-ICE 2022 R1 software available in the ANSYS package. The objective was to evaluate the influence of surface roughness modeling (Shin et al. and beading models) in combination with different turbulence models (Spalart–Allmaras and k-ω shear stress transport) on the estimation of the aerodynamic performance losses of wind turbine airfoils not only under rime ice conditions but also considering the less studied case of glaze ice. Moreover, the behavior of the commonly less explored pressure and skin friction coefficients is examined in the clean and iced airfoil scenarios. As a result, the iced profile experiences higher drag and lower lift than in the no-ice conditions, which is explained by modifying skin friction and pressure coefficients by ice. Overall, the outcomes of both turbulence models are similar, showing maximum differences not higher than 10% in the simulations for both ice regimes. However, it is demonstrated that the influence of blade roughness was critical and cannot be disregarded in ice accretion simulations on wind turbine blades. In this context, the beading model has demonstrated an excellent ability to manage changes in roughness throughout the ice accretion process. On the other hand, the widely used roughness model of Shin et al. could underestimate the lift and overestimate the drag coefficients of the wind turbine airfoil in icy conditions.

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Numerical and experimental investigations of wind-turbine blade aerodynamics in the presence of ice accretion

Cited by 6 publications

References 3 publications

Experimental and Numerical Icing Penalties of an S826 Airfoil at Low Reynolds Numbers

Experimental and Numerical Icing Penalties of an S826 Airfoil at Low Reynolds Numbers

A Review on the Estimation of Power Loss Due to Icing in Wind Turbines

Influence of Surface Roughness Modeling on the Aerodynamics of an Iced Wind Turbine S809 Airfoil

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