Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.770212
Title: Developing fundamental models of colloid transport and absorption in sand filters
Author: Killeen, Matthew
ISNI:       0000 0004 7651 6732
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2018
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Abstract:
This work was undertaken as part of an Industrial Collaborative Awards in Science and Engineering (iCASE) research programme, jointly funded by the National Nuclear Laboratory (NNL) and the Engineering and Physical Sciences Research Council (EPSRC). The aim was to probe the mechanisms of clogging of sand bed filters using particle based computer simulation methods. Existing models take a top down approach, making use of an empirical clogging parameter. Simulation holds the prospect of relating this parameter to properties of the effluent and the sand bed. The problem was approached using two computational methods: molecular dynamics, and smooth particle applied mechanics. The molecular dynamics model yielded successful results, qualitatively agreeing with existing experimental data with regards to the rate of deposition within the bed, and the associated observed pressure drop. The model was systematically explored by varying the nature of the colloidfluid-sand forces, the geometry and packing fraction of the sand bed, and the concentration of the colloids. An investigation into the fractal nature of the deposits was also performed, suggesting that a lower fractal dimension creates greater physical hinderance to the flow. This serves as additional validation for existing theories. The smooth particle model yielded less successful results. Substantial parameterisation of the model was undertaken, however, the model still showed signs of instability under certain conditions. Again, it produced qualitative agreement with existing literature, but showed substantial deviation from the results gained from the molecular dynamics model. Ultimately, further parameterisation of this model is required to allow for a more effective comparison of the models.
Supervisor: Travis, Karl ; Dean, Julian ; Bankhead, Mark Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.770212  DOI: Not available
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