Golzar, Mahshid (2018) CFD MODELLING OF DISPERSION WITHIN RANDOMLY DISTRIBUTED CYLINDER ARRAYS. PhD thesis, University of Sheffield.
Abstract
Vegetation has a significant role in reducing the negative effects of polluted water on natural water bodies. However, a lack of understanding with respect to vegetation-flow interactions may result in poorer performance than expected. The most common vegetation types have been modelled as cylinders by many researchers both in the laboratory and numerical studies. However, experimental studies face practical issues, such as the need for expensive equipment. The quality of the velocity and scalar transport data collected from laboratory setups is also often lower than expected. On the other hand, attempts to model flow and mixing within cylinder arrays using advanced CFD models, e.g. LES, are extremely computationally expensive and cannot be used to produce comparable data to that recorded in laboratory setups.
This thesis proposes and validates the use of commercial less-computationally expensive CFD models (RSM models available in ANSYS FLUENT) as a complementary tool. This tool allows cylinder arrays to be modelled at the same scale as laboratory setups, provides high-resolution flow and turbulence data of high accuracy, and in combination with scalar transport modelling, provides estimated mixing coefficients of the same level of accuracy as those observed in laboratory studies.
The general modelling methodology is built based on the results of a series of preliminary studies. These include novel studies on estimating the advective zone length and the minimum required mixing reach length necessary to provide the desired accuracy, both presented for the first time, as well a validation of the general methodology. The developed methodology was used to produce a new high-resolution and high-accuracy dataset.
The main outcome of this thesis is a very convincing set of evidence that justifies the use of the CFD model as an alternative to traditional lab-based work. A few future studies are suggested to develop a deeper understanding of the processes that control mixing.
Metadata
Supervisors: | Stovin , Virginia and Sonnenwald , Fred |
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Awarding institution: | University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Civil and Structural Engineering (Sheffield) |
Identification Number/EthosID: | uk.bl.ethos.766552 |
Depositing User: | Miss Mahshid Golzar |
Date Deposited: | 18 Feb 2019 09:26 |
Last Modified: | 01 Mar 2020 10:53 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:22887 |
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