LES SENSITIVITY TO DOMAIN SIZE AND GRID RESOLUTION  IN IDEALIZED URBAN STREET CANYON

Main Article Content

Norharyati Saleh
Mohd Hisbany Mohd Hashim
Mohd Faizal Mohamad
Roslin Ramli
Herlien D. Setio

Abstract

A series of large-eddy simulations (LES) was performed to investigate the effects of computational domain size and grid resolution on flow prediction within an idealized urban street canyon. Three streamwise domain lengths were examined in combination with coarse, medium, and fine grid resolutions. The building height, H, was kept constant, and the canyon aspect ratio (street width to building height) was set to unity. Flow statistics were evaluated at the central canyon of each configuration and compared with available wind-tunnel data.The LES results indicate that the simulated mean velocity profiles agree well with experimental measurements for all cases. Both domain size and grid resolution exhibited minimal influence on the mean velocity components, suggesting that mean flow within a street canyon can be reliably predicted using a relatively small computational domain when combined with medium or fine grid resolutions. This offers a computationally efficient option for mean flow analysis. In contrast, turbulence statistics were found to be more sensitive to grid resolution than to domain size. Fine grid resolution significantly improved the prediction of velocity fluctuations and momentum transport, whereas smaller domains tended to produce less consistent turbulence results. Consequently, while small or medium domains may be suitable for mean flow assessment, they are not recommended for detailed turbulence analysis.Overall, this study highlights the importance of balancing domain size and grid resolution to obtain reliable LES results while minimizing computational cost, providing practical guidance for CFD–LES studies of urban street canyon flows.


 

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Saleh, N., Hashim, M. H. M., Mohamad, M. F. ., Ramli, R., & Setio, H. D. (2026). LES SENSITIVITY TO DOMAIN SIZE AND GRID RESOLUTION  IN IDEALIZED URBAN STREET CANYON. International Journal for Computational Civil and Structural Engineering, 22(2), 51-72. https://doi.org/10.22337/2587-9618-2026-22-2-51-72

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