Treffer: Investigation of wind patterns on Marion Island using Computational Fluid Dynamics and measured data

Title:
Investigation of wind patterns on Marion Island using Computational Fluid Dynamics and measured data
Contributors:
Craig, K.J. (Kenneth), Schoombie, Janine, Goddard, Kyle Andrew
Publisher Information:
University of Pretoria
Publication Year:
2021
Collection:
University of Pretoria: UPSpace
Document Type:
Dissertation doctoral or postdoctoral thesis
File Description:
application/pdf
Language:
English
Relation:
Goddard, KA 2021, Investigation of wind patterns on Marion Island using Computational Fluid Dynamics and measured data, MEng Dissertation, University of Pretoria, Pretoria, viewed yymmdd; A2021; http://hdl.handle.net/2263/78564
Rights:
© 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
Accession Number:
edsbas.DFFA16CD
Database:
BASE

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Dissertation (MEng (Mechanical Engineering))--University of Pretoria, 2021. ; There have been countless research investigations taking place on Marion Island (MI), both ecological and geological, which have reached conclusions that must necessarily neglect the impacts of wind on the systems under study. Since only the dominant wind direction of the general atmospheric wind is known from weather and satellite data, not much can be said about local wind conditions at ground level. Therefore, a baseline Computational Fluid Dynamics (CFD) model has been developed for simulating wind patterns over Marion and Prince Edward Islands, a South African territory lying in the subantarctic Indian Ocean. A review of the current state of the art of Computational Wind Engineering (CWE) revealed that large-scale Atmospheric Boundary Layer (ABL) simulations have been successfully performed before with varying degrees of success. With ANSYS Fluent chosen as the numerical solver, the Reynolds-Averaged Navier-Stokes (RANS) equations were set up to simulate a total of 16 wind flow headings approaching MI from each of the cardinal compass directions. The standard k-epsilon turbulence closure scheme with modified constants was used to numerically approximate the atmospheric turbulence. A strategy was devised for generating a reusable mesh system to simulate multiple climatic conditions and wind directions around MI. In conjunction with the computational simulations, a wind measurement campaign was executed to install 17 wind data logging stations at key locations around MI. Raw data output from the stations were cleaned and converted into an easily accessible MySQL database format using the Python scripting language. The Marion Island Recorded Experimental Dataset (MIRED) database contains all wind measurements gathered over the span of two years. The decision was taken to focus on validating only three of the 16 cardinal wind directions against the measured wind data; North-Westerly, Westerly and South-Westerly winds. An initial ...