Research Data Leeds Repository

Dataset associated with 'Modelling urban airflow and natural ventilation using a GPU-based lattice-Boltzmann method'

Citation

King, Marco-Felipe and Khan, Amirul and Delbosc, Nicolas and Gough, Hannah L. and Halios, Christos and Barlow, Janet F. and Noakes, Catherine J. (2018) Dataset associated with 'Modelling urban airflow and natural ventilation using a GPU-based lattice-Boltzmann method'. University of Leeds. [Dataset] https://doi.org/10.5518/245

Dataset description

Simulation of urban airflow and ventilation potential is desirable for building design, however the complex and transient nature of flows in urban environments makes this a challenging task. This study aims to evaluate the capability of a lattice-Boltzmann method (LBM) code deployed on a graphical processing unit (GPU) using a large eddy sub-grid turbulence model for cross-flow ventilation of an idealised cubical building at wind-tunnel scale. ANSYS Fluent is used as a numerical comparison. Façade pressure and ventilation of the cube are investigated for parallel and perpendicular wind directions with the building in isolation and regular array format. Pressures, velocities and ventilation rates are compared to experimental data from wind tunnel and full-scale experiments of the Silsoe cube. Simulations compare favourably with experimental values and between each other. When the cube was surrounded by other cubes, simulations suggest that vortex shedding from up-wind buildings provides pulsating ventilation, improving airflow ingress in the parallel wind cases. A parametric study showed that doubling surrounding building height had a small negative effect on ventilation but was mitigated by high levels of downdraft and flow fluctuations in the vertical plane. Comparatively, doubling the central building height had a net positive effect but caused high internal airspeeds for both angles. The LBM code running on one GPU was several orders of magnitude faster than Fluent with similar accuracy. Simulation time using the LBM approach was several orders of magnitude lower than Fluent.

Keywords:

lattice-Boltzmann method, GPU, CFD, ventilation, urban flow

Subjects:

H000 - Engineering > H200 - Civil engineering

Divisions:

Faculty of Engineering and Physical Sciences > School of Civil Engineering

Related resources:

Location	Type
http://eprints.whiterose.ac.uk/120807/	Publication
https://doi.org/10.1016/j.buildenv.2017.08.048	Publication

License:

Creative Commons Attribution 4.0 International (CC BY 4.0)

Date deposited:

25 Sep 2018 12:35

URI:

https://archive.researchdata.leeds.ac.uk/id/eprint/427

Additional details

Creators or authors:

Creators	ORCID	Primary affiliation	Primary affiliation ID	Primary affiliation ID type
King, Marco-Felipe	https://orcid.org/0000-0001-7010-476X	University of Leeds	https://ror.org/024mrxd33	ror
Khan, Amirul	https://orcid.org/0000-0002-7521-5458	University of Leeds	https://ror.org/024mrxd33	ror
Delbosc, Nicolas		University of Leeds	https://ror.org/024mrxd33	ror
Gough, Hannah L.	https://orcid.org/0000-0002-4693-5931	University of Reading	https://ror.org/05v62cm79	ror
Halios, Christos	https://orcid.org/0000-0001-8301-8449	University of Reading	https://ror.org/05v62cm79	ror
Barlow, Janet F.	https://orcid.org/0000-0002-9022-6833	University of Reading	https://ror.org/05v62cm79	ror
Noakes, Catherine J.	https://orcid.org/0000-0003-3084-7467	University of Leeds	https://ror.org/024mrxd33	ror

Type of data:

Dataset

Research funders:

EPSRC

Grant numbers:

EP/K021834/1

Publication date:

2018

Resource language:

English

Metadata language:

English

Publisher:

University of Leeds

Contact email:

m.f.king@leeds.ac.uk

Last Modified:

31 Jul 2024 11:45

Files

Documentation

README.txt [172B]