Development of a prediction model of the pedestrian mean velocity based on LES of random building arrays

Wind speed in urban areas is influenced by the interaction between wind flow and building geometry, at the pedestrian level, the interaction is more complex, particularly with high building density. This study investigated the wind velocity distribution and the mean velocity ratio at the pedestrian...

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Main Authors: Sheikh Ahmad Zaki, Sheikh Ahmad Zaki, Shuhaimi, Saidatul Sharin, Mohammad, Ahmad Faiz, Mat Ali, Mohamed Sukri, Jamaludin, Khairur Rijal, Ahmad, Mardiana Idayu
Format: Article
Language:English
Published: MDPI 2022
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Online Access:http://eprints.utm.my/id/eprint/101278/1/SheikhAhmadZaki2022_DevelopmentofaPredictionModelofthePedestrianMean.pdf
http://eprints.utm.my/id/eprint/101278/
http://dx.doi.org/10.3390/buildings12091362
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spelling my.utm.1012782023-06-08T08:25:28Z http://eprints.utm.my/id/eprint/101278/ Development of a prediction model of the pedestrian mean velocity based on LES of random building arrays Sheikh Ahmad Zaki, Sheikh Ahmad Zaki Shuhaimi, Saidatul Sharin Mohammad, Ahmad Faiz Mat Ali, Mohamed Sukri Jamaludin, Khairur Rijal Ahmad, Mardiana Idayu TH Building construction Wind speed in urban areas is influenced by the interaction between wind flow and building geometry, at the pedestrian level, the interaction is more complex, particularly with high building density. This study investigated the wind velocity distribution and the mean velocity ratio at the pedestrian level using the large-eddy simulation (LES) database based on random building arrays of several plan area densities, ?p. The heights of random buildings are between 0.36 h and 3.76 h where h = 0.025 m. Mean streamwise velocity profiles were obtained at the pedestrian level for all arrays and were found to decrease as ?p increased. Wind flow patterns at the pedestrian level were highly influenced by adjacent buildings, especially in denser conditions, ?p > 0.17. The pedestrian-level mean velocity was obtained around each building, and the relationship between the local mean velocity ratio, Vp(t) and the local frontal area density, ?f(t) was analyzed. Subsequently, a prediction model was formulated based on the building’s aspect ratio, ap, the correlation for high-rise buildings with 2.64 h = ap = 3.76 h was high at 0.8, while a lower correlation was obtained for lower buildings due to random positioning and surrounding geometric effects. Therefore, the impact of high-rise buildings on pedestrian wind velocity can be estimated more accurately using the formulated model. MDPI 2022 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/101278/1/SheikhAhmadZaki2022_DevelopmentofaPredictionModelofthePedestrianMean.pdf Sheikh Ahmad Zaki, Sheikh Ahmad Zaki and Shuhaimi, Saidatul Sharin and Mohammad, Ahmad Faiz and Mat Ali, Mohamed Sukri and Jamaludin, Khairur Rijal and Ahmad, Mardiana Idayu (2022) Development of a prediction model of the pedestrian mean velocity based on LES of random building arrays. Buildings, 12 (9). pp. 1-14. ISSN 2075-5309 http://dx.doi.org/10.3390/buildings12091362 DOI : 10.3390/buildings12091362
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TH Building construction
spellingShingle TH Building construction
Sheikh Ahmad Zaki, Sheikh Ahmad Zaki
Shuhaimi, Saidatul Sharin
Mohammad, Ahmad Faiz
Mat Ali, Mohamed Sukri
Jamaludin, Khairur Rijal
Ahmad, Mardiana Idayu
Development of a prediction model of the pedestrian mean velocity based on LES of random building arrays
description Wind speed in urban areas is influenced by the interaction between wind flow and building geometry, at the pedestrian level, the interaction is more complex, particularly with high building density. This study investigated the wind velocity distribution and the mean velocity ratio at the pedestrian level using the large-eddy simulation (LES) database based on random building arrays of several plan area densities, ?p. The heights of random buildings are between 0.36 h and 3.76 h where h = 0.025 m. Mean streamwise velocity profiles were obtained at the pedestrian level for all arrays and were found to decrease as ?p increased. Wind flow patterns at the pedestrian level were highly influenced by adjacent buildings, especially in denser conditions, ?p > 0.17. The pedestrian-level mean velocity was obtained around each building, and the relationship between the local mean velocity ratio, Vp(t) and the local frontal area density, ?f(t) was analyzed. Subsequently, a prediction model was formulated based on the building’s aspect ratio, ap, the correlation for high-rise buildings with 2.64 h = ap = 3.76 h was high at 0.8, while a lower correlation was obtained for lower buildings due to random positioning and surrounding geometric effects. Therefore, the impact of high-rise buildings on pedestrian wind velocity can be estimated more accurately using the formulated model.
format Article
author Sheikh Ahmad Zaki, Sheikh Ahmad Zaki
Shuhaimi, Saidatul Sharin
Mohammad, Ahmad Faiz
Mat Ali, Mohamed Sukri
Jamaludin, Khairur Rijal
Ahmad, Mardiana Idayu
author_facet Sheikh Ahmad Zaki, Sheikh Ahmad Zaki
Shuhaimi, Saidatul Sharin
Mohammad, Ahmad Faiz
Mat Ali, Mohamed Sukri
Jamaludin, Khairur Rijal
Ahmad, Mardiana Idayu
author_sort Sheikh Ahmad Zaki, Sheikh Ahmad Zaki
title Development of a prediction model of the pedestrian mean velocity based on LES of random building arrays
title_short Development of a prediction model of the pedestrian mean velocity based on LES of random building arrays
title_full Development of a prediction model of the pedestrian mean velocity based on LES of random building arrays
title_fullStr Development of a prediction model of the pedestrian mean velocity based on LES of random building arrays
title_full_unstemmed Development of a prediction model of the pedestrian mean velocity based on LES of random building arrays
title_sort development of a prediction model of the pedestrian mean velocity based on les of random building arrays
publisher MDPI
publishDate 2022
url http://eprints.utm.my/id/eprint/101278/1/SheikhAhmadZaki2022_DevelopmentofaPredictionModelofthePedestrianMean.pdf
http://eprints.utm.my/id/eprint/101278/
http://dx.doi.org/10.3390/buildings12091362
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score 13.214268