IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i5p1310-d507542.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/5/1310/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/5/1310/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    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. Henrik Skaug Sætra, 2021. "AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    2. Xi Liu & Yugang He & Renhong Wu, 2024. "Revolutionizing Environmental Sustainability: The Role of Renewable Energy Consumption and Environmental Technologies in OECD Countries," Energies, MDPI, vol. 17(2), pages 1-21, January.
    3. Gianluca MISURACA & Colin van Noordt, 2020. "AI Watch - Artificial Intelligence in public services: Overview of the use and impact of AI in public services in the EU," JRC Research Reports JRC120399, Joint Research Centre.
    4. Fabian Dvorak & Regina Stumpf & Sebastian Fehrler & Urs Fischbacher, 2024. "Generative AI Triggers Welfare-Reducing Decisions in Humans," Papers 2401.12773, arXiv.org.
    5. Sergio Genovesi & Julia Maria Mönig, 2022. "Acknowledging Sustainability in the Framework of Ethical Certification for AI," Sustainability, MDPI, vol. 14(7), pages 1-10, March.
    6. Tan Yigitcanlar & Rashid Mehmood & Juan M. Corchado, 2021. "Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    7. Ricardo Vinuesa & Soledad Le Clainche, 2022. "Machine-Learning Methods for Complex Flows," Energies, MDPI, vol. 15(4), pages 1-5, February.
    8. Qian, Yu & Xu, Zeshui & Qin, Yong & Gou, Xunjie & Skare, Marinko, 2023. "Measuring the varying relationships between sustainable development and oil booms in different contexts: An empirical study," Resources Policy, Elsevier, vol. 85(PB).
    9. Krzysztof Rusek & Agnieszka Kleszcz & Albert Cabellos-Aparicio, 2022. "Bayesian inference of spatial and temporal relations in AI patents for EU countries," Papers 2201.07168, arXiv.org.
    10. Hanna Obracht-Prondzyńska & Ewa Duda & Helena Anacka & Jolanta Kowal, 2022. "Greencoin as an AI-Based Solution Shaping Climate Awareness," IJERPH, MDPI, vol. 19(18), pages 1-25, September.
    11. Aras Bozkurt & Abdulkadir Karadeniz & David Baneres & Ana Elena Guerrero-Roldán & M. Elena Rodríguez, 2021. "Artificial Intelligence and Reflections from Educational Landscape: A Review of AI Studies in Half a Century," Sustainability, MDPI, vol. 13(2), pages 1-16, January.
    12. Heather M. Stoll & Isabel Cacho & Edward Gasson & Jakub Sliwinski & Oliver Kost & Ana Moreno & Miguel Iglesias & Judit Torner & Carlos Perez-Mejias & Negar Haghipour & Hai Cheng & R. Lawrence Edwards, 2022. "Rapid northern hemisphere ice sheet melting during the penultimate deglaciation," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    13. Hernandez-Matheus, Alejandro & Löschenbrand, Markus & Berg, Kjersti & Fuchs, Ida & Aragüés-Peñalba, Mònica & Bullich-Massagué, Eduard & Sumper, Andreas, 2022. "A systematic review of machine learning techniques related to local energy communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    14. Olga Pilipczuk, 2020. "Sustainable Smart Cities and Energy Management: The Labor Market Perspective," Energies, MDPI, vol. 13(22), pages 1-24, November.
    15. Raghu Raman & Krishnashree Achuthan & Ricardo Vinuesa & Prema Nedungadi, 2021. "COVIDTAS COVID-19 Tracing App Scale—An Evaluation Framework," Sustainability, MDPI, vol. 13(5), pages 1-19, March.
    16. Jon Truby, 2020. "Governing Artificial Intelligence to benefit the UN Sustainable Development Goals," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 946-959, July.
    17. Arasteh, Mohammad Ali & Farjami, Yaghoub, 2021. "Supporting Sustainable Rural Groundwater Demand Management with Fuzzy Decision Analysis: A Case Study in Iran," Utilities Policy, Elsevier, vol. 70(C).
    18. Galaz, Victor & Centeno, Miguel A. & Callahan, Peter W. & Causevic, Amar & Patterson, Thayer & Brass, Irina & Baum, Seth & Farber, Darryl & Fischer, Joern & Garcia, David & McPhearson, Timon & Jimenez, 2021. "Artificial intelligence, systemic risks, and sustainability," Technology in Society, Elsevier, vol. 67(C).
    19. Olga Pilipczuk, 2021. "Determinants of Managerial Competences Transformation in the Polish Energy Industry," Energies, MDPI, vol. 14(20), pages 1-27, October.
    20. Naudé, Wim & Dimitri, Nicola, 2021. "Public Procurement and Innovation for Human-Centered Artificial Intelligence," IZA Discussion Papers 14021, Institute of Labor Economics (IZA).

    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:14:y:2021:i:5:p:1310-:d:507542. 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.