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Boundary-layer transition model for icing simulations of rotating wind turbine blades

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  • Son, Chankyu
  • Kelly, Mark
  • Kim, Taeseong

Abstract

Icing simulations for wind turbine blades should consider the roughness-induced flow transition. Adding a transport equation for ‘roughness amplification’ to the Langtry-Menter model, the roughness-induced transition can be predicted for rough flat plates. However, this approach exhibits a limitation that it cannot predict the skin friction in the shadow zone of blunt bodies. Such an approach depends on the boundary condition(s) of specific dissipation rate (ω). Typically boundary conditions for turbulent kinetic energy (k) and ω have been investigated for various roughness heights, but have been applied only for fully turbulent conditions. This study introduces an approach to predict the flow transition and the skin friction for a roughened surface, whereby the Langtry-Menter model including roughness amplification is coupled with the k and ω boundary conditions. The proposed method shows good agreement with the experiments for turbulent onset and the distributions of skin friction and heat convection for a roughened flat plate and a circular cylinder. Using the turbulent models under fully turbulent and transitional assumptions, the effects of the flow transition on the ice accretion shape on a rotating wind turbine are compared. The modified turbulent model showed better performance for the icing simulations without any tuning.

Suggested Citation

  • Son, Chankyu & Kelly, Mark & Kim, Taeseong, 2021. "Boundary-layer transition model for icing simulations of rotating wind turbine blades," Renewable Energy, Elsevier, vol. 167(C), pages 172-183.
    • Handle: RePEc:eee:renene:v:167:y:2021:i:c:p:172-183
    DOI: 10.1016/j.renene.2020.11.070
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    References listed on IDEAS

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    1. Zanon, Alessandro & De Gennaro, Michele & Kühnelt, Helmut, 2018. "Wind energy harnessing of the NREL 5 MW reference wind turbine in icing conditions under different operational strategies," Renewable Energy, Elsevier, vol. 115(C), pages 760-772.
    2. Dalili, N. & Edrisy, A. & Carriveau, R., 2009. "A review of surface engineering issues critical to wind turbine performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(2), pages 428-438, February.
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    1. Fahed Martini & Adrian Ilinca & Patrick Rizk & Hussein Ibrahim & Mohamad Issa, 2022. "A Survey of the Quasi-3D Modeling of Wind Turbine Icing," Energies, MDPI, vol. 15(23), pages 1-32, November.
    2. Wang, Zixuan & Qin, Bo & Sun, Haiyue & Zhang, Jian & Butala, Mark D. & Demartino, Cristoforo & Peng, Peng & Wang, Hongwei, 2023. "An imbalanced semi-supervised wind turbine blade icing detection method based on contrastive learning," Renewable Energy, Elsevier, vol. 212(C), pages 251-262.
    3. Guo, Wenfeng & Shen, He & Li, Yan & Feng, Fang & Tagawa, Kotaro, 2021. "Wind tunnel tests of the rime icing characteristics of a straight-bladed vertical axis wind turbine," Renewable Energy, Elsevier, vol. 179(C), pages 116-132.
    4. Xu, Zhi & Zhang, Ting & Li, Xiaojuan & Li, Yan, 2023. "Effects of ambient temperature and wind speed on icing characteristics and anti-icing energy demand of a blade airfoil for wind turbine," Renewable Energy, Elsevier, vol. 217(C).
    5. Sun, Haoyang & Lin, Guiping & Jin, Haichuan & Bu, Xueqin & Cai, Chujiang & Jia, Qi & Ma, Kuiyuan & Wen, Dongsheng, 2021. "Experimental investigation of surface wettability induced anti-icing characteristics in an ice wind tunnel," Renewable Energy, Elsevier, vol. 179(C), pages 1179-1190.

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