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Description
This study uses Computational Fluid Dynamics (CFD) modeling to analyze the

dependence of wind power potential and turbulence intensity on aerodynamic design of a

special type of building with a nuzzle-like gap at its rooftop. Numerical simulations using

ANSYS Fluent are carried out to quantify the above-mentioned dependency due to three

major geometric parameters

This study uses Computational Fluid Dynamics (CFD) modeling to analyze the

dependence of wind power potential and turbulence intensity on aerodynamic design of a

special type of building with a nuzzle-like gap at its rooftop. Numerical simulations using

ANSYS Fluent are carried out to quantify the above-mentioned dependency due to three

major geometric parameters of the building: (i) the height of the building, (ii) the depth of

the roof-top gap, and (iii) the width of the roof-top gap. The height of the building is varied

from 8 m to 24 m. Likewise, the gap depth is varied from 3 m to 5 m and the gap width

from 2 m to 4 m. The aim of this entire research is to relate these geometric parameters of

the building to the maximum value and the spatial pattern of wind power potential across

the roof-top gap. These outcomes help guide the design of the roof-top geometry for wind

power applications and determine the ideal position for mounting a micro wind turbine.

From these outcomes, it is suggested that the wind power potential is greatly affected by

the increasing gap width or gap depth. It, however, remains insensitive to the increasing

building height, unlike turbulence intensity which increases with increasing building

height. After performing a set of simulations with varying building geometry to quantify

the wind power potential before the installation of a turbine, another set of simulations is

conducted by installing a static turbine within the roof-top gap. The results from the latter

are used to further adjust the estimate of wind power potential. Recommendations are made

for future applications based on the findings from the numerical simulations.
ContributorsKailkhura, Gargi (Author) / Huang, Huei-Ping (Thesis advisor) / Rajagopalan, Jagannathan (Committee member) / Forzani, Erica (Committee member) / Arizona State University (Publisher)
Created2017