Integrating Wind Flow Analysis in Early Urban Design: Guidelines for Practitioners

Authors

  • Ph.D. Candidate Mathieu Paris Laboratoire Innovation Formes Architectures Milieux (LIFAM), Ecole Nationale Supérieure d’Architecture de Montpellier, 34090 Montpellier, France
  • Dr. Frédéric Dubois Laboratoire de Mécanique et Génie Civil (LMGC), Université de Montpellier, CNRS, 34090 Montpellier, France https://orcid.org/0000-0003-1977-8042
  • Dr. Stéphane Bosc Laboratoire Innovation Formes Architectures Milieux (LIFAM), Ecole Nationale Supérieure d’Architecture de Montpellier, 34090 Montpellier, France
  • Prof. Dr. Philippe Devillers Laboratoire Innovation Formes Architectures Milieux (LIFAM), Ecole Nationale Supérieure d’Architecture de Montpellier, 34090 Montpellier, France https://orcid.org/0000-0002-7026-1818

DOI:

https://doi.org/10.25034/ijcua.2023.v7n2-12

Keywords:

Architectural and Environmental Sustainability, Urban Morphology, Urban Design, Wind Flow, Outdoor Thermal Comfort, Mediterranean Climate

Abstract

The research focused on simulating wind patterns in urban planning design offers substantial contributions to both the social and economic aspects of the urban planning and design field. To begin with, it addresses a critical factor in urban development, especially in Mediterranean climates, where natural ventilation significantly influences summer comfort. By incorporating predictive numerical simulations of urban wind patterns, this study provides valuable insights into improving outdoor thermal comfort within urban areas. This holds particular importance in the context of adapting to climate change, as it equips urban planners and architects with informed decision-making tools to create more sustainable and comfortable urban environments. Additionally, this research makes an economic contribution by presenting guidelines for iterative wind simulations in the early stages of designing medium-scale urban projects. Through the validation of a simulation workflow, it streamlines the design process, potentially reducing the time and resources required for urban planning and architectural design. This enhanced efficiency can result in cost savings during project development. Moreover, the study's recommendations concerning simulation parameters, such as wind tunnel cell size and refinement levels, offer practical insights for optimizing simulation processes, potentially lowering computational expenses and improving the overall economic viability of urban design projects. To summarize, this research effectively addresses climate-related challenges, benefiting both social well-being and economic efficiency in the field of urban planning and design, while also providing guidance for more efficient simulation-driven design procedures.

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References

Blocken, B., Janssen, W. D., & van Hooff, T. (2012). CFD simulation for pedestrian wind comfort and wind safety in urban areas: General decision framework and case study for the Eindhoven University campus. Environmental Modelling & Software, 30, 15-34. https://doi.org/10.1016/j.envsoft.2011.11.009

Blocken, B., Stathopoulos, T., Carmeliet, J., & Hensen, J. L. (2011). Application of computational fluid dynamics in building performance simulation for the outdoor environment: an overview. Journal of building performance simulation, 4(2), 157-184. https://doi.org/10.1080/19401493.2010.513740

Blocken, B. (2015). Computational Fluid Dynamics for urban physics: Importance, scales, possibilities, limitations and ten tips and tricks towards accurate and reliable simulations. Building and Environment, 91, 219-245. https://doi.org/10.1016/j.buildenv.2015.02.015

Chronis, A., Dubor, A., Cabay, E., & Roudsari, M. S. (2017). Integration of CFD in computational design. Proceedings of eCAADe 2017, 601-610. https://doi.org/10.52842/conf.ecaade.2017.1.601

De Luca, F. (2019). Environmental performance-driven Urban Design: Parametric design method for the integration of daylight and urban comfort analysis in cold climates. In Computer-Aided Architectural Design." Hello, Culture" 18th International Conference, CAAD Futures 2019, Daejeon, Republic of Korea, June 26–28, 2019, Selected Papers 18 (pp. 15-31). Springer Singapore. https://doi.org/10.1007/978-981-13-8410-3_2

Elwy, I., Ibrahim, Y., Fahmy, M., & Mahdy, M. (2018). Outdoor microclimatic validation for hybrid simulation workflow in hot arid climates against ENVI-met and field measurements. Energy Procedia, 153, 29-34. https://doi.org/10.1016/j.egypro.2018.10.009

Ferziger, J. H., Perić, M., & Street, R. L. (2019). Computational methods for fluid dynamics. springer. https://doi.org/10.1007/978-3-319-99693-6

Franke, J., Hirsch, C., Jensen, A. G., Krüs, H. W., Schatzmann, M., Westbury, P. S., ... & Wright, N. G. (2004, May). Recommendations on the use of CFD in predicting pedestrian wind environment. In Cost action C (Vol. 14).

Franke, J., Hellsten, A., Schlunzen, K. H., & Carissimo, B. (2011). The COST 732 Best Practice Guideline for CFD simulation of flows in the urban environment: a summary. International Journal of Environment and Pollution, 44(1-4), 419-427. https://doi.org/10.1504/IJEP.2011.038443

Hu, Y., Peng, Y., Gao, Z., & Xu, F. (2023). Application of CFD plug-ins integrated into urban and building design platforms for performance simulations: A literature review. Frontiers of Architectural Research, 12(1), 148-174. https://doi.org/10.1016/j.foar.2022.06.005

Ibrahim, Y., Kershaw, T., Shepherd, P., & Coley, D. (2021). On the optimisation of urban form design, energy consumption and outdoor thermal comfort using a parametric workflow in a hot arid zone. Energies, 14(13), 4026. https://doi.org/10.3390/en14134026

Loh, N., & Bhiwapurkar, P. (2022). Urban heat-mitigating building form and façade framework. Architectural Science Review, 65(1), 57-71. https://doi.org/10.1080/00038628.2021.1924610

Ma, X. N., Zhao, J., & Guo, P. (2019). The urban computing on the distribution of inhalable particulate matters to Smart City–based residential groups. Concurrency and Computation: Practice and Experience, 31(9), e4803. https://doi.org/10.1002/cpe.4803

Mackey, C., Galanos, T., Norford, L., Roudsari, M. S., & Architects, P. (2017, August). Wind, sun, surface temperature, and heat island: Critical variables for high-resolution outdoor thermal comfort. In Proceedings of the 15th international conference of building performance simulation association. San Francisco, USA. https://doi.org/10.26868/25222708.2017.260

Maffessanti, V. (2019). Wind and Urban Spaces. Evaluation of a CFD Parametric Framework for Early‐Stage Design. In 4th IBPSA-Italy Conference Bozen-Bolzano, 19th–21st June 2019, 16.

https://doi.org/10.13124/9788860461766

Magnusson, S., Dallman, A., Entekhabi, D., Britter, R., Fernando, H. J., & Norford, L. (2014). On thermally forced flows in urban street canyons. Environmental Fluid Mechanics, 14, 1427-1441. https://doi.org/10.1007/s10652-014-9353-4

Mauree, D., Naboni, E., Coccolo, S., Perera, A. T. D., Nik, V. M., & Scartezzini, J. L. (2019). A review of assessment methods for the urban environment and its energy sustainability to guarantee climate adaptation of future cities. Renewable and Sustainable Energy Reviews, 112, 733-746.

https://doi.org/10.1016/j.rser.2019.06.005

Mirzaei, P. A. (2021). CFD modeling of micro and urban climates: Problems to be solved in the new decade. Sustainable Cities and Society, 69, 102839. https://doi.org/10.1016/j.scs.2021.102839

Mochida, A., Tabata, Y., Iwata, T., & Yoshino, H. (2008). Examining tree canopy models for CFD prediction of wind environment at pedestrian level. Journal of Wind Engineering and Industrial Aerodynamics, 96(10-11), 1667-1677. https://doi.org/10.1016/j.jweia.2008.02.055

Naboni, E., Natanian, J., Brizzi, G., Florio, P., Chokhachian, A., Galanos, T., & Rastogi, P. (2019). A digital workflow to quantify regenerative urban design in the context of a changing climate. Renewable and Sustainable Energy Reviews, 113, 109255. https://doi.org/10.1016/j.rser.2019.109255

Paris, M., Sansen, M., Bosc, S., & Devillers, P. (2022). Simulation Tools for the Architectural Design of Middle-Density Housing Estates. Sustainability, 14(17), 10696. https://doi.org/10.3390/su141710696

Pak, M., Smith, A., & Gill, G. (2013). Ladybug: A Parametric Environmental Plugin For Grasshopper To Help Designers Create An Environmentally-conscious Design. Building Simulation Conference Proceedings. https://doi.org/10.26868/25222708.2013.2499

Sansen, M., Martínez, A., & Devillers, P. (2021). Mediterranean Morphologies in Hot Summer Conditions: Learning from France’s “Glorious Thirty” Holiday Housing. Journal of Contemporary Urban Affairs, 5(1), 19-34. https://doi.org/10.25034/ijcua.2021.v5n1-2

Sun, C., & Rao, J. (2020). Study on performance-oriented generation of urban block models. In Proceedings of the 2019 DigitalFUTURES: The 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019) 1 (pp. 179-188). Springer Singapore. https://doi.org/10.1007/978-981-13-8153-9_16

Tamura, T., Nozawa, K., & Kondo, K. (2008). AIJ guide for numerical prediction of wind loads on buildings. Journal of Wind Engineering and Industrial Aerodynamics, 96(10-11), 1974-1984. https://doi.org/10.1016/j.jweia.2008.02.020

Tominaga, Y., Mochida, A., Yoshie, R., Kataoka, H., Nozu, T., Yoshikawa, M., & Shirasawa, T. (2008). AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings. Journal of wind engineering and industrial aerodynamics, 96(10-11), 1749-1761. https://doi.org/10.1016/j.jweia.2008.02.058

Toparlar, Y., Blocken, B., Maiheu, B., & Van Heijst, G. J. F. (2017). A review on the CFD analysis of urban microclimate. Renewable and Sustainable Energy Reviews, 80, 1613-1640. https://doi.org/10.1016/j.rser.2017.05.248

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Published

2023-11-28

How to Cite

Paris, M., Dubois, F., Bosc, S., & Devillers, P. (2023). Integrating Wind Flow Analysis in Early Urban Design: Guidelines for Practitioners. Journal of Contemporary Urban Affairs, 7(2), 194–211. https://doi.org/10.25034/ijcua.2023.v7n2-12

Issue

Section

Resilience and Built Environment