IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i14p3602-d1440398.html
   My bibliography  Save this article

Computational Fluid Dynamics Simulation on Blade Geometry of Novel Axial FlowTurbine for Wave Energy Extraction

Author

Listed:
  • Mohammad Nasim Uddin

    (Department of Mechanical Engineering, North Carolina A&T State University, Greensboro, NC 27411, USA)

  • Yang Gao

    (Department of Mechanical Engineering, North Carolina A&T State University, Greensboro, NC 27411, USA)

  • Paul M. Akangah

    (Department of Mechanical Engineering, North Carolina A&T State University, Greensboro, NC 27411, USA)

Abstract

Wave energy converters (WECs) utilizing the Oscillating Water Column (OWC) principle have gained prominence for harnessing kinetic energy from ocean waves. This study explores an innovative approach by transforming the pivoting Denniss–Auld turbine blades into a fixed configuration, offering a simplified alternative. The fixed-blade design emulates the maximum pivot points during the OWC’s exhalation and inhalation phases. Traditional Denniss–Auld turbines rely on complex hub systems to enable controllable blade rotation for performance optimization. This research examines the turbine’s efficiency without mechanical actuation. The simulations were conducted using ANSYS™ CFX 2023 R2 to solve the three-dimensional, incompressible, steady-state Reynolds-Averaged Navier–Stokes (RANS) equations, employing the k-ω SST turbulence model to close the system of equations. A grid convergence study was performed, and the numerical results were validated against available experimental and numerical data. An in-depth analysis of the intricate flow field around the turbine blades was also conducted. The modified Denniss–Auld turbine demonstrated a broad operating range, avoiding stalling at high flow coefficients and exhibiting performance characteristics like an impulse turbine. However, the peak efficiency was 12%, significantly lower than that of conventional Denniss–Auld and impulse turbines. Future research should focus on expanding the design space through parametric studies to enhance turbine efficiency and power output.

Suggested Citation

  • Mohammad Nasim Uddin & Yang Gao & Paul M. Akangah, 2024. "Computational Fluid Dynamics Simulation on Blade Geometry of Novel Axial FlowTurbine for Wave Energy Extraction," Energies, MDPI, vol. 17(14), pages 1-28, July.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:14:p:3602-:d:1440398
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/14/3602/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/14/3602/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Reguero, B.G. & Losada, I.J. & Méndez, F.J., 2015. "A global wave power resource and its seasonal, interannual and long-term variability," Applied Energy, Elsevier, vol. 148(C), pages 366-380.
    2. Opoku, F. & Uddin, M.N. & Atkinson, M., 2023. "A review of computational methods for studying oscillating water columns – the Navier-Stokes based equation approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 174(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tunde Aderinto & Hua Li, 2020. "Effect of Spatial and Temporal Resolution Data on Design and Power Capture of a Heaving Point Absorber," Sustainability, MDPI, vol. 12(22), pages 1-17, November.
    2. Morim, Joao & Cartwright, Nick & Hemer, Mark & Etemad-Shahidi, Amir & Strauss, Darrell, 2019. "Inter- and intra-annual variability of potential power production from wave energy converters," Energy, Elsevier, vol. 169(C), pages 1224-1241.
    3. Seongho Ahn & Kevin A. Haas & Vincent S. Neary, 2020. "Dominant Wave Energy Systems and Conditional Wave Resource Characterization for Coastal Waters of the United States," Energies, MDPI, vol. 13(12), pages 1-26, June.
    4. Yang, Zhaoqing & García Medina, Gabriel & Neary, Vincent S. & Ahn, Seongho & Kilcher, Levi & Bharath, Aidan, 2023. "Multi-decade high-resolution regional hindcasts for wave energy resource characterization in U.S. coastal waters," Renewable Energy, Elsevier, vol. 212(C), pages 803-817.
    5. Shi, Xueli & Liang, Bingchen & Li, Shaowu & Zhao, Jianchun & Wang, Junhui & Wang, Zhenlu, 2024. "Wave energy resource classification system for the China East Adjacent Seas based on multivariate clustering," Energy, Elsevier, vol. 299(C).
    6. Cuttler, Michael V.W. & Hansen, Jeff E. & Lowe, Ryan J., 2020. "Seasonal and interannual variability of the wave climate at a wave energy hotspot off the southwestern coast of Australia," Renewable Energy, Elsevier, vol. 146(C), pages 2337-2350.
    7. Shadmani, Alireza & Nikoo, Mohammad Reza & Gandomi, Amir H. & Chen, Mingjie & Nazari, Rouzbeh, 2024. "Advancements in optimizing wave energy converter geometry utilizing metaheuristic algorithms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 197(C).
    8. Atan, Reduan & Goggins, Jamie & Nash, Stephen, 2018. "Galway Bay – The 1/4 scale wave energy test site? A detailed wave energy resource assessment and investigation of scaling factors," Renewable Energy, Elsevier, vol. 119(C), pages 217-234.
    9. Hao, Daning & Qi, Lingfei & Tairab, Alaeldin M. & Ahmed, Ammar & Azam, Ali & Luo, Dabing & Pan, Yajia & Zhang, Zutao & Yan, Jinyue, 2022. "Solar energy harvesting technologies for PV self-powered applications: A comprehensive review," Renewable Energy, Elsevier, vol. 188(C), pages 678-697.
    10. Américo S. Ribeiro & Maite deCastro & Liliana Rusu & Mariana Bernardino & João M. Dias & Moncho Gomez-Gesteira, 2020. "Evaluating the Future Efficiency of Wave Energy Converters along the NW Coast of the Iberian Peninsula," Energies, MDPI, vol. 13(14), pages 1-15, July.
    11. Simon Krüner & Christoph M. Hackl, 2022. "Nonlinear Modelling and Control of a Power Smoothing System for a Novel Wave Energy Converter Prototype," Sustainability, MDPI, vol. 14(21), pages 1-17, October.
    12. Neary, Vincent S. & Ahn, Seongho, 2023. "Global atlas of extreme significant wave heights and relative risk ratios," Renewable Energy, Elsevier, vol. 208(C), pages 130-140.
    13. Delpey, Matthias & Lastiri, Ximun & Abadie, Stéphane & Roeber, Volker & Maron, Philippe & Liria, Pedro & Mader, Julien, 2021. "Characterization of the wave resource variability in the French Basque coastal area based on a high-resolution hindcast," Renewable Energy, Elsevier, vol. 178(C), pages 79-95.
    14. Liu, Jin & Li, Rui & Li, Shuo & Meucci, Alberto & Young, Ian R., 2024. "Increasing wave power due to global climate change and intensification of Antarctic Oscillation," Applied Energy, Elsevier, vol. 358(C).
    15. Francisco Francisco & Jennifer Leijon & Cecilia Boström & Jens Engström & Jan Sundberg, 2018. "Wave Power as Solution for Off-Grid Water Desalination Systems: Resource Characterization for Kilifi-Kenya," Energies, MDPI, vol. 11(4), pages 1-14, April.
    16. Satymov, Rasul & Bogdanov, Dmitrii & Dadashi, Mojtaba & Lavidas, George & Breyer, Christian, 2024. "Techno-economic assessment of global and regional wave energy resource potentials and profiles in hourly resolution," Applied Energy, Elsevier, vol. 364(C).
    17. Penalba, Markel & Ulazia, Alain & Ibarra-Berastegui, Gabriel & Ringwood, John & Sáenz, Jon, 2018. "Wave energy resource variation off the west coast of Ireland and its impact on realistic wave energy converters’ power absorption," Applied Energy, Elsevier, vol. 224(C), pages 205-219.
    18. Rusu, Liliana, 2019. "Evaluation of the near future wave energy resources in the Black Sea under two climate scenarios," Renewable Energy, Elsevier, vol. 142(C), pages 137-146.
    19. Lavidas, George & Venugopal, Vengatesan, 2017. "A 35 year high-resolution wave atlas for nearshore energy production and economics at the Aegean Sea," Renewable Energy, Elsevier, vol. 103(C), pages 401-417.
    20. José Manuel Oliver & Maria Dolores Esteban & José-Santos López-Gutiérrez & Vicente Negro & Maria Graça Neves, 2021. "Optimizing Wave Overtopping Energy Converters by ANN Modelling: Evaluating the Overtopping Rate Forecasting as the First Step," Sustainability, MDPI, vol. 13(3), pages 1-25, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:14:p:3602-:d:1440398. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.