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Forecasting of average surface pressure coefficient of polygonal building models

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Abstract

The consideration of wind loads in the development of lateral load-resisting systems for tall buildings is of utmost importance, given their vulnerability to such loads. Hence, in the design of tall buildings, a meticulous evaluation of wind loads is imperative. To tackle this issue, aerodynamic modifications can be deployed as effective techniques to mitigate wind loads. Building shape and size are also significant parameters that influence wind loads on tall buildings, which can be experimentally measured in wind tunnels and computationally analyzed using Computational Fluid Dynamics (CFD). In this study, the average surface pressure coefficient is computed for various polygonal building models under different Angle of Attack (AOA) conditions. The average surface pressure coefficient varies among the different faces of the building models. One variable is the position of the building surfaces from the centreline of the frontal face, expressed as a percentage, while the other variables are the side number of the polygon (N) and AOA. The average surface pressure coefficient is measured for different scenarios and positions, and the results are utilized to train an Artificial Neural Network (ANN). The ANN training demonstrates a commendable conformity between the predicted models and the input data.

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Acknowledgements

Authors would like to express their sincere gratitude to Delhi Technological University, Delhi, India for providing funding to conduct the research work. First authors would like to express thanks to Punjab Engineering College, Chandigarh, India for providing facilities used to complete writeup for the research work. Second author would like to thanks to the Meghnad Saha Institute of Technology, Kolkata, India to complete the manuscript on the time.

Funding

Authors would like to express their sincere gratitude to Delhi Technological University, Delhi, India for providing funding to conduct the research work.

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Authors and Affiliations

  1. Punjab Engineering College, Chandigarh, India

    Rahul Kumar Meena

  2. Meghnad Saha Institute of Technology, Kolkata, India

    Prasenjit Sanyal

  3. Delhi Technological University, Delhi, India

    Abhishek Prakash Paswan & Ritu Raj

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  1. Rahul Kumar Meena
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  2. Prasenjit Sanyal
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  3. Abhishek Prakash Paswan
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  4. Ritu Raj
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Contributions

R.K.M. analysis, CFD, Writing original draft P.S. ANN, writing original draft A.P.S. Editing English R.R. Supervison

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Correspondence to Ritu Raj.

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All data and models used during the study appear in the submitted article.

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Meena, R.K., Sanyal, P., Paswan, A.P. et al. Forecasting of average surface pressure coefficient of polygonal building models. Asian J Civ Eng 24, 3907–3918 (2023). https://doi.org/10.1007/s42107-023-00716-z

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