Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/102923
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Title: Modelling of pedestrian level wind environment on a high-quality mesh : a case study for the HKPolyU campus
Authors: Du, Y 
Mak, CM 
Ai, Z
Issue Date: May-2018
Source: Environmental modelling & software, May 2018, v. 103, p. 105-119
Abstract: Quality and efficiency of computational fluid dynamics (CFD) simulation of pedestrian level wind environment in a complex urban area are often compromised by many influencing factors, particularly mesh quality. This paper first proposes a systematic and efficient mesh generation method and then performs detailed sensitivity analysis of some important computational parameters. The geometrically complex Hong Kong Polytechnic University (HKPolyU) campus is taken as a case study. Based on the high-quality mesh system, the influences of three important computational parameters, namely, turbulence model, near-wall mesh density and computational domain size, on the CFD predicted results of pedestrian level wind environment are quantitatively evaluated. Validation of CFD models is conducted against wind tunnel experimental data, where a good agreement is achieved. It is found that the proposed mesh generation method can effectively provide a high-quality and high-resolution structural grid for CFD simulation of wind environment in a complex urban area.
Keywords: Complex urban environment
Computational fluid dynamics (CFD) simulation
Mesh generation method
Pedestrian level wind environment
Sensitivity analysis
Publisher: Elsevier
Journal: Environmental modelling & software 
ISSN: 1364-8152
EISSN: 1873-6726
DOI: 10.1016/j.envsoft.2018.02.016
Rights: © 2018 Elsevier Ltd. All rights reserved.
© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.
The following publication Du, Y., Mak, C. M., & Ai, Z. (2018). Modelling of pedestrian level wind environment on a high-quality mesh: A case study for the HKPolyU campus. Environmental Modelling and Software, 103, 105-119 is available at https://doi.org/10.1016/j.envsoft.2018.02.016.
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