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CFD Prediction of Wind Turbine Blade Compressible Aerodynamics

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Computational Science and Its Applications – ICCSA 2023 (ICCSA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13956 ))

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Abstract

Computational fluid dynamics (CFD) analysis is carried out to evaluate the compressible aerodynamics of a large horizontal axis wind turbine blade. The mean turbulent flow around the rotating blade is simulated by adopting the unsteady Reynolds-averaged Navier-Stokes modelling approach, where the governing equations are solved by means of a finite volume-based numerical method, supplied with a two-equation eddy-viscosity turbulence model. The present CFD model using an open-source code for computational wind engineering applications was verified to have significant practical potential by making a comparison with a reference steady solution.

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Authors and Affiliations

  1. Engineering Department, University of Campania Luigi Vanvitelli, Aversa, 81031, Italy

    A. Mezzacapo, M. C. Vitulano, A. D. Tomasso & G. De Stefano

Authors
  1. A. Mezzacapo
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  2. M. C. Vitulano
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  3. A. D. Tomasso
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  4. G. De Stefano
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Corresponding author

Correspondence to G. De Stefano .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Monash University, Clayton, VIC, Australia

    David Taniar

  4. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  5. University of Minho, Braga, Portugal

    Ana Cristina Braga

  6. University of Cagliari, Cagliari, Italy

    Chiara Garau

  7. National Technical University of Athens, Athens, Greece

    Anastasia Stratigea

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Mezzacapo, A., Vitulano, M.C., Tomasso, A.D., De Stefano, G. (2023). CFD Prediction of Wind Turbine Blade Compressible Aerodynamics. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023. ICCSA 2023. Lecture Notes in Computer Science, vol 13956 . Springer, Cham. https://doi.org/10.1007/978-3-031-36805-9_8

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  • DOI: https://doi.org/10.1007/978-3-031-36805-9_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36804-2

  • Online ISBN: 978-3-031-36805-9

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