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Influence of operational parameters on the performance of Tesla turbines: Experimental investigation of a small-scale turbine

Author

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  • Thomazoni, André Luis Ribeiro
  • Ermel, Conrado
  • Schneider, Paulo Smith
  • Vieira, Lara Werncke
  • Hunt, Julian David
  • Ferreira, Sandro Barros
  • Rech, Charles
  • Gouvêa, Vinicius Santorum

Abstract

Tesla turbines can be employed as small-scale turbines to recover waste energy in several industrial applications. However, there is no consensus on the turbine efficiency as experimental studies show significantly lower values than those obtained by analytical and CFD approaches. The present work addresses that question by performing a systematic literature review (SLR) on Tesla turbines, comparing the efficiency values reported by experimental and simulation works. To validate the SLR findings an experimental small-scale air driven Tesla turbine was built. The Design of Experiments (DoE) methodology was applied to understand the effects of selected independent variables on the turbine output power and mechanical efficiency. Inlet air pressure, temperature, and rotational speed were chosen as controllable factors of a Central Composite Design applied to the prototype of < 1 kW output power. The results indicate a 5% efficiency increase when inlet pressure increases 1 bar, on average. In the SLR, the average efficiency of 40%–60% was reported by simulation works, while experimental articles reported maximum efficiencies of 20%, on average. The experimental turbine analyzed in this paper presented a maximum efficiency of 14.2% ± 0.4% at 3 barg and 4,000 rpm, agreeing with other experimental studies.

Suggested Citation

  • Thomazoni, André Luis Ribeiro & Ermel, Conrado & Schneider, Paulo Smith & Vieira, Lara Werncke & Hunt, Julian David & Ferreira, Sandro Barros & Rech, Charles & Gouvêa, Vinicius Santorum, 2022. "Influence of operational parameters on the performance of Tesla turbines: Experimental investigation of a small-scale turbine," Energy, Elsevier, vol. 261(PB).
    • Handle: RePEc:eee:energy:v:261:y:2022:i:pb:s0360544222020527
    DOI: 10.1016/j.energy.2022.125159
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    References listed on IDEAS

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    2. Lin, Pingtao & Li, Liushuai & Zhao, Yang & Liu, Tongqing & Cui, Feifei & An, Dou & Xi, Huan, 2026. "Integrated performance analysis and Prediction for a Tesla turbine in advanced adiabatic compressed air energy storage systems," Energy, Elsevier, vol. 344(C).
    3. Kosowski, Krzysztof & Piwowarski, Marian & Stępień, Robert & Włodarski, Wojciech, 2025. "Innovative Tesla turbine devices: Concept, testing and insights," Energy, Elsevier, vol. 337(C).
    4. Li, Liushuai & Teng, Shiyang & Zhao, Yang & An, Dou & Xi, Huan, 2025. "Experimental study on a Tesla turbine integrated into a Mini-ORC system using R245fa as working fluid," Energy, Elsevier, vol. 324(C).
    5. Li, Xinyu & Teng, Shiyang & An, Dou & Hung, Tzu-Chen & Xi, Huan, 2025. "Experimental investigation of Tesla turbine under different operating parameters and load conditions using air as working fluid," Energy, Elsevier, vol. 339(C).
    6. Mohammadsadegh Pahlavanzadeh & Krzysztof Rusin & Włodzimierz Wróblewski, 2025. "Roughness Modeling Using a Porous Medium Layer in a Tesla Turbine Operating with ORC Fluids," Energies, MDPI, vol. 18(18), pages 1-17, September.
    7. Cheng, Hongzhi & Li, Ziliang & Duan, Penghao & Lu, Xingen & Zhao, Shengfeng & Zhang, Yanfeng, 2023. "Robust optimization and uncertainty quantification of a micro axial compressor for unmanned aerial vehicles," Applied Energy, Elsevier, vol. 352(C).
    8. Rusin, Krzysztof & Wróblewski, Włodzimierz & Hasani Malekshah, Emad & Pahlavanzadeh, Mohammadsadegh & Rulik, Sebastian, 2024. "Extended analytical model of Tesla turbine with advanced modelling of velocity profile in minichannel between corotating disks with consideration of surface roughness," Energy, Elsevier, vol. 307(C).

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