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A Review of Laboratory and Numerical Techniques to Simulate Turbulent Flows

Author

Listed:
  • Simone Ferrari

    (Department of Civil-Environmental Engineering and Architecture (DICAAR), University of Cagliari, 09123 Cagliari, Italy)

  • Riccardo Rossi

    (RED Fluid Dynamics, 09127 Cagliari, Italy)

  • Annalisa Di Bernardino

    (Physics Department, Sapienza University, 00185 Rome, Italy)

Abstract

Turbulence is still an unsolved issue with enormous implications in several fields, from the turbulent wakes on moving objects to the accumulation of heat in the built environment or the optimization of the performances of heat exchangers or mixers. This review deals with the techniques and trends in turbulent flow simulations, which can be achieved through both laboratory and numerical modeling. As a matter of fact, even if the term “experiment” is commonly employed for laboratory techniques and the term “simulation” for numerical techniques, both the laboratory and numerical techniques try to simulate the real-world turbulent flows performing experiments under controlled conditions. The main target of this paper is to provide an overview of laboratory and numerical techniques to investigate turbulent flows, useful for the research and technical community also involved in the energy field (often non-specialist of turbulent flow investigations), highlighting the advantages and disadvantages of the main techniques, as well as their main fields of application, and also to highlight the trends of the above mentioned methodologies via bibliometric analysis. In this way, the reader can select the proper technique for the specific case of interest and use the quoted bibliography as a more detailed guide. As a consequence of this target, a limitation of this review is that the deepening of the single techniques is not provided. Moreover, even though the experimental and numerical techniques presented in this review are virtually applicable to any type of turbulent flow, given their variety in the very broad field of energy research, the examples presented and discussed in this work will be limited to single-phase subsonic flows of Newtonian fluids. The main result from the bibliometric analysis shows that, as of 2021, a 3:1 ratio of numerical simulations over laboratory experiments emerges from the analysis, which clearly shows a projected dominant trend of the former technique in the field of turbulence. Nonetheless, the main result from the discussion of advantages and disadvantages of both the techniques confirms that each of them has peculiar strengths and weaknesses and that both approaches are still indispensable, with different but complementary purposes.

Suggested Citation

  • Simone Ferrari & Riccardo Rossi & Annalisa Di Bernardino, 2022. "A Review of Laboratory and Numerical Techniques to Simulate Turbulent Flows," Energies, MDPI, vol. 15(20), pages 1-56, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7580-:d:942036
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    References listed on IDEAS

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    1. Shifeng Fu & Yaqing Jin & Jin-Tae Kim & Zhongyu Mao & Yuan Zheng & Leonardo P. Chamorro, 2018. "On the Dynamics of Flexible Plates under Rotational Motions," Energies, MDPI, vol. 11(12), pages 1-11, December.
    2. Roberto Pacciani & Michele Marconcini & Francesco Bertini & Simone Rosa Taddei & Ennio Spano & Yaomin Zhao & Harshal D. Akolekar & Richard D. Sandberg & Andrea Arnone, 2021. "Assessment of Machine-Learned Turbulence Models Trained for Improved Wake-Mixing in Low-Pressure Turbine Flows," Energies, MDPI, vol. 14(24), pages 1-17, December.
    3. Damien Le Bideau & Philippe Mandin & Mohamed Benbouzid & Myeongsub Kim & Mathieu Sellier & Fabrizio Ganci & Rosalinda Inguanta, 2020. "Eulerian Two-Fluid Model of Alkaline Water Electrolysis for Hydrogen Production," Energies, MDPI, vol. 13(13), pages 1-14, July.
    4. Sławomir Grądziel & Karol Majewski & Marek Majdak & Łukasz Mika & Karol Sztekler & Rafał Kobyłecki & Robert Zarzycki & Małgorzata Pilawska, 2021. "Testing of Heat Transfer Coefficients and Frictional Losses in Internally Ribbed Tubes and Verification of Results through CFD Modelling," Energies, MDPI, vol. 15(1), pages 1-17, December.
    5. Vyacheslav Volov & Nikolay Elisov & Anton Lyaskin, 2021. "Numerical Investigation of the Secondary Swirling in Supersonic Flows of Various Nature Gases," Energies, MDPI, vol. 14(23), pages 1-25, December.
    6. Michelangelo Balmelli & Norbert Zsiga & Laura Merotto & Patrik Soltic, 2020. "Effect of the Intake Valve Lift and Closing Angle on Part Load Efficiency of a Spark Ignition Engine," Energies, MDPI, vol. 13(7), pages 1-16, April.
    7. Linrong Zhang & Guangjian Zhang & Mingming Ge & Olivier Coutier-Delgosha, 2020. "Experimental Study of Pressure and Velocity Fluctuations Induced by Cavitation in a Small Venturi Channel," Energies, MDPI, vol. 13(24), pages 1-12, December.
    8. Florian Ries & Yongxiang Li & Dario Klingenberg & Kaushal Nishad & Johannes Janicka & Amsini Sadiki, 2018. "Near-Wall Thermal Processes in an Inclined Impinging Jet: Analysis of Heat Transport and Entropy Generation Mechanisms," Energies, MDPI, vol. 11(6), pages 1-23, May.
    9. Krzysztof Kurec & Janusz Piechna, 2019. "Influence of Side Spoilers on the Aerodynamic Properties of a Sports Car," Energies, MDPI, vol. 12(24), pages 1-22, December.
    10. Jose J. Aguilar-Fuertes & Francisco Noguero-Rodríguez & José C. Jaen Ruiz & Luis M. García-RAffi & Sergio Hoyas, 2021. "Tracking Turbulent Coherent Structures by Means of Neural Networks," Energies, MDPI, vol. 14(4), pages 1-15, February.
    11. Roman I. Egorov & Alexandr S. Zaitsev & Eugene A. Salgansky, 2018. "Activation of the Fuels with Low Reactivity Using the High-Power Laser Pulses," Energies, MDPI, vol. 11(11), pages 1-8, November.
    12. Tomasz Janoszek & Wojciech Masny, 2021. "CFD Simulations of Allothermal Steam Gasification Process for Hydrogen Production," Energies, MDPI, vol. 14(6), pages 1-28, March.
    13. Srivastav, Vivek Kumar & Paul, Akshoy R. & Jain, Anuj, 2019. "Capturing the wall turbulence in CFD simulation of human respiratory tract," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 160(C), pages 23-38.
    14. Gregory Duthé & Imad Abdallah & Sarah Barber & Eleni Chatzi, 2021. "Modeling and Monitoring Erosion of the Leading Edge of Wind Turbine Blades," Energies, MDPI, vol. 14(21), pages 1-33, November.
    15. Mateusz Prończuk & Anna Krzanowska, 2021. "Experimental Investigation of the Heat Transfer and Pressure Drop inside Tubes and the Shell of a Minichannel Shell and Tube Type Heat Exchanger," Energies, MDPI, vol. 14(24), pages 1-21, December.
    16. Jakub Mularski & Norbert Modliński, 2020. "Impact of Chemistry–Turbulence Interaction Modeling Approach on the CFD Simulations of Entrained Flow Coal Gasification," Energies, MDPI, vol. 13(23), pages 1-25, December.
    17. A. La Porta & Greg A. Voth & Alice M. Crawford & Jim Alexander & Eberhard Bodenschatz, 2001. "Fluid particle accelerations in fully developed turbulence," Nature, Nature, vol. 409(6823), pages 1017-1019, February.
    18. Donghyun Hwang & Kyubok Ahn, 2021. "Experimental Study on Dynamic Combustion Characteristics in Swirl-Stabilized Combustors," Energies, MDPI, vol. 14(6), pages 1-14, March.
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