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Near-wall modeling of forests for atmosphere boundary layers using lattice Boltzmann method on GPU

Shao, X; Santasmasas, MC; Xue, X; Niu, J; Davidson, L; Revell, AJ; Yao, HD; (2022) Near-wall modeling of forests for atmosphere boundary layers using lattice Boltzmann method on GPU. Engineering Applications of Computational Fluid Mechanics , 16 (1) pp. 2142-2155. 10.1080/19942060.2022.2132420. Green open access

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Abstract

In this paper, the simulation and modeling of the turbulent atmospheric boundary layers (ABLs) in the presence of forests are studied using a lattice Boltzmann method with large eddy simulation, which was implemented in the open-source program GASCANS with the use of Graphic Processing Units (GPU). A method of modeling forests in the form of body forces injected near the wall is revisited, while the effects of leaf area density (LAD) on the model accuracy is further addressed. Since a uniform cell size is applied throughout the computational domain, the wall-normal height of the near-wall cells is very large, theoretically requiring a wall function to model the boundary layer. However, the wall function is disregarded here when the forest is modeled. This approximation is validated based on the comparison with previous experimental and numerical data. It concludes that for the ABL conditions specified in this study as well as a large body of literature, the forest forces overwhelm the wall friction so that the modeling of the latter effect is trivial. Constant and varying LAD profiles across the forest zone are defined with the same total leaf area despite the varying one being studied previously. It is found that the two LAD profiles provide consistent predictions. The present forest modeling can therefore be simplified with the use of the constant LAD without degrading the model accuracy remarkably.

Type: Article
Title: Near-wall modeling of forests for atmosphere boundary layers using lattice Boltzmann method on GPU
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/19942060.2022.2132420
Publisher version: https://doi.org/10.1080/19942060.2022.2132420
Language: English
Additional information: © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Chemistry
URI: https://discovery.ucl.ac.uk/id/eprint/10166127
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