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Evaluation of blade-strike models for estimating the biological performance of Kaplan turbines

Author

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  • Deng, Zhiqun
  • Carlson, Thomas J.
  • Ploskey, Gene R.
  • Richmond, Marshall C.
  • Dauble, Dennis D.

Abstract

Bio-indexing of hydro turbines is an important means to optimize passage conditions for fish by identifying operations for existing and new design turbines that minimize the probability of injury. Cost-effective implementation of bio-indexing requires the use of tools such as numerical and physical turbine models to generate hypotheses for turbine operations that can be tested at prototype scales using live fish. Numerical deterministic and stochastic blade-strike models were developed for a 1:25-scale physical turbine model built by the U.S. Army Corps of Engineers for the original design turbine at McNary Dam and for prototype-scale original design and replacement minimum gap runner (MGR) turbines at Bonneville Dam’s first powerhouse. Blade-strike probabilities predicted by both models were comparable with those observed in both prototype-scale live fish survival studies and a physical turbine model using neutrally buoyant beads. Predictions from the stochastic model were closer to experimental data than predictions from the deterministic model because the stochastic model considered the aspects of fish approaching to the leading edges of turbine runner blades. Therefore, the stochastic model should be the preferred method for the prediction of blade strike and injury probability for juvenile salmon and steelhead using numerical blade-strike models for evaluating the biological performance of Kaplan hydro turbines.

Suggested Citation

  • Deng, Zhiqun & Carlson, Thomas J. & Ploskey, Gene R. & Richmond, Marshall C. & Dauble, Dennis D., 2007. "Evaluation of blade-strike models for estimating the biological performance of Kaplan turbines," Ecological Modelling, Elsevier, vol. 208(2), pages 165-176.
    • Handle: RePEc:eee:ecomod:v:208:y:2007:i:2:p:165-176
    DOI: 10.1016/j.ecolmodel.2007.05.019
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    Citations

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    Cited by:

    1. Fu, Tao & Deng, Zhiqun Daniel & Duncan, Joanne P. & Zhou, Daqing & Carlson, Thomas J. & Johnson, Gary E. & Hou, Hongfei, 2016. "Assessing hydraulic conditions through Francis turbines using an autonomous sensor device," Renewable Energy, Elsevier, vol. 99(C), pages 1244-1252.
    2. Phoevos (Foivos) Koukouvinis & John Anagnostopoulos, 2023. "State of the Art in Designing Fish-Friendly Turbines: Concepts and Performance Indicators," Energies, MDPI, vol. 16(6), pages 1-25, March.
    3. Singh, Rajesh K. & Romero-Gomez, Pedro & Colotelo, Alison H. & Perkins, William A. & Richmond, Marshall C., 2022. "Computational studies of hydraulic stressors for biological performance assessment in a hydropower plant with Kaplan turbine," Renewable Energy, Elsevier, vol. 199(C), pages 768-781.
    4. Klopries, Elena-Maria & Schüttrumpf, Holger, 2020. "Mortality assessment for adult European eels (Anguilla Anguilla) during turbine passage using CFD modelling," Renewable Energy, Elsevier, vol. 147(P1), pages 1481-1490.
    5. Zhiqun Deng & Thomas J. Carlson & Dennis D. Dauble & Gene R. Ploskey, 2011. "Fish Passage Assessment of an Advanced Hydropower Turbine and Conventional Turbine Using Blade-Strike Modeling," Energies, MDPI, vol. 4(1), pages 1-11, January.
    6. Linda Vikström & Kjell Leonardsson & Johan Leander & Samuel Shry & Olle Calles & Gustav Hellström, 2020. "Validation of Francis–Kaplan Turbine Blade Strike Models for Adult and Juvenile Atlantic Salmon (Salmo Salar, L.) and Anadromous Brown Trout (Salmo Trutta, L.) Passing High Head Turbines," Sustainability, MDPI, vol. 12(16), pages 1-13, August.
    7. Ak, Mümtaz & Kentel, Elçin & Kucukali, Serhat, 2017. "A fuzzy logic tool to evaluate low-head hydropower technologies at the outlet of wastewater treatment plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 727-737.
    8. Zhu, Guojun & Guo, Yuxing & Feng, Jianjun & Gao, Luhan & Wu, Guangkuan & Luo, Xingqi, 2022. "Analysis and reduction of the pressure and shear damage probability of fish in a Francis turbine," Renewable Energy, Elsevier, vol. 199(C), pages 462-473.
    9. Martinez, Jayson J. & Deng, Zhiqun Daniel & Mueller, Robert & Titzler, Scott, 2020. "In situ characterization of the biological performance of a Francis turbine retrofitted with a modular guide vane," Applied Energy, Elsevier, vol. 276(C).

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