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An Acoustic Source Model for Applications in Low Mach Number Turbulent Flows, Such as a Large-Scale Wind Turbine Blade

Author

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  • Hui Tang

    (College of Automotive Engineering, Jilin University, Renmin Street No. 5988, Changchun 130012, China
    State Key Laboratory of Automotive Simulation and Control, Jilin University, Renmin Street No. 5988, Changchun 130012, China)

  • Yulong Lei

    (College of Automotive Engineering, Jilin University, Renmin Street No. 5988, Changchun 130012, China
    State Key Laboratory of Automotive Simulation and Control, Jilin University, Renmin Street No. 5988, Changchun 130012, China)

  • Xingzhong Li

    (College of Automotive Engineering, Jilin University, Renmin Street No. 5988, Changchun 130012, China
    State Key Laboratory of Automotive Simulation and Control, Jilin University, Renmin Street No. 5988, Changchun 130012, China)

Abstract

Aerodynamic noise from wind turbine blades is one of the major hindrances for the widespread use of large-scale wind turbines generating green energy. In order to more accurately guide wind turbine blade manufacturers to optimize the blade geometry for aerodynamic noise reduction, an acoustic model that not only understands the relation between the behavior of the sound source and the sound generation, but also accounts for the compressibility effect, was derived by rearranging the continuity and Navier–Stokes equations as a wave equation with a lump of source terms, including the material derivative and square of the velocity divergence. Our acoustic model was applied to low Mach number, weakly compressible turbulent flows around NACA0012 airfoil. For the computation of flow fields, a large-eddy simulation (LES) with the dynamic Smagorinsky subgrid scale (SGS) model and the cubic interpolated pseudo particle (CIP)-combined unified numerical procedure method were conducted. The reproduced turbulent flow around NACA0012 airfoil was in good agreement with the experimental data. For the estimation of acoustic fields, our acoustic model and classical sound source models, such as Lighthill and Powell, were performed using our LES database. The investigation suggested that the derived material derivative of the velocity divergence plays a dominant role as sound source. The distribution of the sources in our acoustic model was consistent with that of the classical sound source models. The sound pressure level (SPL) predicted based on the above-mentioned LES and our newly derived acoustic model was in reasonable agreement with the experimental data. The influence of the increase of Mach number on the acoustic field was investigated. Our acoustic source model was verified to be capable of treating the influence of Mach numbers on the acoustic field.

Suggested Citation

  • Hui Tang & Yulong Lei & Xingzhong Li, 2019. "An Acoustic Source Model for Applications in Low Mach Number Turbulent Flows, Such as a Large-Scale Wind Turbine Blade," Energies, MDPI, vol. 12(23), pages 1-18, December.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:23:p:4596-:d:293539
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    References listed on IDEAS

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    1. Li, Qing'an & Maeda, Takao & Kamada, Yasunari & Murata, Junsuke & Kawabata, Toshiaki & Shimizu, Kento & Ogasawara, Tatsuhiko & Nakai, Alisa & Kasuya, Takuji, 2016. "Wind tunnel and numerical study of a straight-bladed Vertical Axis Wind Turbine in three-dimensional analysis (Part II: For predicting flow field and performance)," Energy, Elsevier, vol. 104(C), pages 295-307.
    2. Li, Qing'an & Maeda, Takao & Kamada, Yasunari & Murata, Junsuke & Kawabata, Toshiaki & Shimizu, Kento & Ogasawara, Tatsuhiko & Nakai, Alisa & Kasuya, Takuji, 2016. "Wind tunnel and numerical study of a straight-bladed vertical axis wind turbine in three-dimensional analysis (Part I: For predicting aerodynamic loads and performance)," Energy, Elsevier, vol. 106(C), pages 443-452.
    3. Zhu, Wei Jun & Shen, Wen Zhong & Barlas, Emre & Bertagnolio, Franck & Sørensen, Jens Nørkær, 2018. "Wind turbine noise generation and propagation modeling at DTU Wind Energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 133-150.
    4. Wenlei Bai & Duehee Lee & Kwang Y. Lee, 2017. "Stochastic Dynamic AC Optimal Power Flow Based on a Multivariate Short-Term Wind Power Scenario Forecasting Model," Energies, MDPI, vol. 10(12), pages 1-19, December.
    5. Hui Tang & Yulong Lei & Xingzhong Li & Yao Fu, 2019. "Numerical Investigation of the Aerodynamic Characteristics and Attitude Stability of a Bio-Inspired Corrugated Airfoil for MAV or UAV Applications," Energies, MDPI, vol. 12(20), pages 1-25, October.
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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.
    2. Hui Tang & Yulong Lei & Xingzhong Li & Ke Gao & Yanli Li, 2020. "Aerodynamic Shape Optimization of a Wavy Airfoil for Ultra-Low Reynolds Number Regime in Gliding Flight," Energies, MDPI, vol. 13(2), pages 1-27, January.

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