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An Experimental Study on the Actuator Line Method with Anisotropic Regularization Kernel

Author

Listed:
  • Zhe Ma

    (Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China)

  • Liping Lei

    (Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China)

  • Earl Dowell

    (Department of Mechanical Engineering & Material Science, Duke University, Durham, NC 27704, USA)

  • Pan Zeng

    (Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China)

Abstract

Nowadays, actuator line method (ALM) has become the most potential method in wind turbine simulations, especially in wind farm simulations and fluid-structure interaction simulations. The regularization kernel, which was originally introduced to ALM to avoid numerical singularity, has been found to have great influence on rotor torque predictions and wake simulations. This study focuses on the effect of each parameter used in the standard kernel and the anisotropic kernel. To validate the simulation, the torque and the wake characteristics of a model wind turbine were measured. The result shows that the Gaussian width ϵ (for standard kernel) and the parameter in chord length direction ϵ c (for anisotropic kernel) mainly affect the normal velocity of each blade element when using ALM but have little effect on the tangential velocity calculation. Therefore, these parameters have great influence on the attack angle and rotor torque prediction. The thickness parameter ϵ t is the main difference between the standard kernel and the anisotropic kernel and it has a strong effect on the wind turbine wakes simulation. When using the anisotropic kernel, the wake structure is clearer and less likely to disperse, which is more consistent with the experimental results. Based on the studies above, a non-uniform mesh is recommended when using the anisotropic regularization kernel. Using a mesh refined in the main flow direction, ALM with anisotropic kernel can predict torque and wake characteristics better while maintaining low computational costs.

Suggested Citation

  • Zhe Ma & Liping Lei & Earl Dowell & Pan Zeng, 2020. "An Experimental Study on the Actuator Line Method with Anisotropic Regularization Kernel," Energies, MDPI, vol. 13(4), pages 1-19, February.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:4:p:977-:d:323618
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    References listed on IDEAS

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    1. Zhong, Hongmin & Du, Pingan & Tang, Fangning & Wang, Li, 2015. "Lagrangian dynamic large-eddy simulation of wind turbine near wakes combined with an actuator line method," Applied Energy, Elsevier, vol. 144(C), pages 224-233.
    2. Meng, Hang & Lien, Fue-Sang & Li, Li, 2018. "Elastic actuator line modelling for wake-induced fatigue analysis of horizontal axis wind turbine blade," Renewable Energy, Elsevier, vol. 116(PA), pages 423-437.
    3. Storey, R.C. & Cater, J.E. & Norris, S.E., 2016. "Large eddy simulation of turbine loading and performance in a wind farm," Renewable Energy, Elsevier, vol. 95(C), pages 31-42.
    4. Dou, Bingzheng & Guala, Michele & Lei, Liping & Zeng, Pan, 2019. "Experimental investigation of the performance and wake effect of a small-scale wind turbine in a wind tunnel," Energy, Elsevier, vol. 166(C), pages 819-833.
    5. Na, Ji Sung & Koo, Eunmo & Muñoz-Esparza, Domingo & Jin, Emilia Kyung & Linn, Rodman & Lee, Joon Sang, 2016. "Turbulent kinetics of a large wind farm and their impact in the neutral boundary layer," Energy, Elsevier, vol. 95(C), pages 79-90.
    6. Wang, Zhenyu & Ozbay, Ahmet & Tian, Wei & Hu, Hui, 2018. "An experimental study on the aerodynamic performances and wake characteristics of an innovative dual-rotor wind turbine," Energy, Elsevier, vol. 147(C), pages 94-109.
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    Cited by:

    1. Giovanni Ferrara & Alessandro Bianchini, 2021. "Special Issue “Numerical Simulation of Wind Turbines”," Energies, MDPI, vol. 14(6), pages 1-2, March.

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