Nanoparticle transport modelling in saturated porous media

Moghadas Mehrabi, S

Nanoparticle transport modelling in saturated porous media

Moghadas Mehrabi, S

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Publication Type:: Thesis
Issue Date:: 2014

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Field	Value	Language
dc.contributor.author	Moghadas Mehrabi, S
dc.date.accessioned	2014-08-27T08:23:54Z
dc.date.available	2014-08-27T08:23:54Z
dc.date.issued	2014
dc.identifier.uri	http://hdl.handle.net/10453/29234
dc.description	University of Technology, Sydney. Faculty of Engineering and Information Technology.	en_US
dc.description.abstract	This research deals with multi-scale descriptions of nano-colloidal transport in saturated porous media. Colloidal transport has been simulated, historically, by employing a pore-scale model. I argue that the use of such simulations on a continuum-scale where formulations are generally phenomenological, may be unsuitable if at all possible due to requirements for pore-scale parameterization. I propose to up-scale the pore-scale equation by inclusion of natural heterogeneity of porous media which consequently substitutes the pore-scale parameters (often unobtainable in real cases) with continuum-scale parameters (measurable at field). This approach transforms the pore-scale formulation into a Darcy-scale formulation, making it usable for real-world simulations. I demonstrate a closer agreement with experimental data once porous media’s natural heterogeneity is considered compared with the use of a mean value for media grain size in the conventional methods. These results can be explained by noting the fact that hydraulic conductivity of a porous medium is not controlled by the coarser or the median size grains. Rather, it is the smaller grains which ultimately determine (or in other words, restrict) the permeability of any given porous medium. By comparing various modelled scenarios, I also assess the magnitude of difference in predicted results which displays a significant divergence from the case where the porous medium is assumed to be homogeneous. Finally I aim to estimate the uncertainty associated with scenarios A (Yao’s equation) and B (Mehrabi_ Milne-Home equation) in the absence and presence of natural heterogeneity, respectively. The results showed a noticeable decrease of 9% to 87% in the uncertainty caused by the most prominent source of uncertainty in groundwater modelling; porous media’s heterogeneity. The uncertainty is generally lower closer to the contaminant release point and increases as the plume moves away from the source point. The more substantial improvements (reduction of uncertainty) was observed at selected point which were located further away from the release point. A framework for the assessment of nanoparticle transport in aquifers follows in which the extent of movement is estimated based on available field measured data and the probabilities of various potential realizations can be measured. This will help provide a much needed set of information for the policy-making processes with regards to new and emerging contaminants including engineered nanoparticles.	en_US
dc.format	Thesis (PhD)	en_US
dc.language.iso	en	en_US
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/29234/2/02whole.pdf
dc.rights	au.edu.uts.lib/ppc
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Groundwater modelling.	en
dc.subject	Nanoparticle transport.	en
dc.subject	Hydrogeology.	en
dc.subject	Nanoremediation.	en
dc.subject	Environmental aspects.	en
dc.title	Nanoparticle transport modelling in saturated porous media	en_US
dc.type	Thesis
utslib.copyright.status	open_access

Abstract:

This research deals with multi-scale descriptions of nano-colloidal transport in saturated porous media. Colloidal transport has been simulated, historically, by employing a pore-scale model. I argue that the use of such simulations on a continuum-scale where formulations are generally phenomenological, may be unsuitable if at all possible due to requirements for pore-scale parameterization. I propose to up-scale the pore-scale equation by inclusion of natural heterogeneity of porous media which consequently substitutes the pore-scale parameters (often unobtainable in real cases) with continuum-scale parameters (measurable at field). This approach transforms the pore-scale formulation into a Darcy-scale formulation, making it usable for real-world simulations. I demonstrate a closer agreement with experimental data once porous media’s natural heterogeneity is considered compared with the use of a mean value for media grain size in the conventional methods. These results can be explained by noting the fact that hydraulic conductivity of a porous medium is not controlled by the coarser or the median size grains. Rather, it is the smaller grains which ultimately determine (or in other words, restrict) the permeability of any given porous medium. By comparing various modelled scenarios, I also assess the magnitude of difference in predicted results which displays a significant divergence from the case where the porous medium is assumed to be homogeneous. Finally I aim to estimate the uncertainty associated with scenarios A (Yao’s equation) and B (Mehrabi_ Milne-Home equation) in the absence and presence of natural heterogeneity, respectively. The results showed a noticeable decrease of 9% to 87% in the uncertainty caused by the most prominent source of uncertainty in groundwater modelling; porous media’s heterogeneity. The uncertainty is generally lower closer to the contaminant release point and increases as the plume moves away from the source point. The more substantial improvements (reduction of uncertainty) was observed at selected point which were located further away from the release point. A framework for the assessment of nanoparticle transport in aquifers follows in which the extent of movement is estimated based on available field measured data and the probabilities of various potential realizations can be measured. This will help provide a much needed set of information for the policy-making processes with regards to new and emerging contaminants including engineered nanoparticles.

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