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On the Experimental, Numerical and Data-Driven Methods to Study Urban Flows

Author

Listed:
  • Pablo Torres

    (SimEx/FLOW, Engineering Mechanics, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden)

  • Soledad Le Clainche

    (School of Aerospace Engineering, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • Ricardo Vinuesa

    (SimEx/FLOW, Engineering Mechanics, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden)

Abstract

Understanding the flow in urban environments is an increasingly relevant problem due to its significant impact on air quality and thermal effects in cities worldwide. In this review we provide an overview of efforts based on experiments and simulations to gain insight into this complex physical phenomenon. We highlight the relevance of coherent structures in urban flows, which are responsible for the pollutant-dispersion and thermal fields in the city. We also suggest a more widespread use of data-driven methods to characterize flow structures as a way to further understand the dynamics of urban flows, with the aim of tackling the important sustainability challenges associated with them. Artificial intelligence and urban flows should be combined into a new research line, where classical data-driven tools and machine-learning algorithms can shed light on the physical mechanisms associated with urban pollution.

Suggested Citation

  • Pablo Torres & Soledad Le Clainche & Ricardo Vinuesa, 2021. "On the Experimental, Numerical and Data-Driven Methods to Study Urban Flows," Energies, MDPI, vol. 14(5), pages 1-38, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:5:p:1310-:d:507542
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    References listed on IDEAS

    as
    1. Soledad Le Clainche & Esteban Ferrer, 2018. "A Reduced Order Model to Predict Transient Flows around Straight Bladed Vertical Axis Wind Turbines," Energies, MDPI, vol. 11(3), pages 1-24, March.
    2. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    3. Frederik Schenk & Minna Väliranta & Francesco Muschitiello & Lev Tarasov & Maija Heikkilä & Svante Björck & Jenny Brandefelt & Arne V. Johansson & Jens-Ove Näslund & Barbara Wohlfarth, 2018. "Warm summers during the Younger Dryas cold reversal," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
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    Cited by:

    1. Jesús Amo-Navarro & Ricardo Vinuesa & J. Alberto Conejero & Sergio Hoyas, 2021. "Two-Dimensional Compact-Finite-Difference Schemes for Solving the bi-Laplacian Operator with Homogeneous Wall-Normal Derivatives," Mathematics, MDPI, vol. 9(19), pages 1-13, October.

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