A proximity‐based image‐processing algorithm for colloid assignment in segmented multiphase flow datasets

Summary Colloidal transport and deposition are of both environmental and engineering importance. Easier access to x‐ray microtomography (XMT) coupled with improved imaging resolution has made XMT a unique and viable tool for visualizing and quantifying these processes. Currently, there is scant info...

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Bibliographic Details
Published in:Journal of microscopy (Oxford) Vol. 277; no. 2; pp. 118 - 129
Main Authors: BRUECK, C.L., WILDENSCHILD, D.
Format: Journal Article
Language:English
Published: England Wiley Subscription Services, Inc 01.02.2020
Wiley-Blackwell
Subjects:
Algorithms
Attachment
Chemical properties
Colloid chemistry
Colloid transport
Colloiding
Colloids
Contaminants
Contamination
Datasets
Deposition
Fluid flow
Groundwater
Image processing
Image resolution
Image segmentation
Interfaces
Microtomography
Multiphase flow
Organic chemistry
particle filtration
Partitioning
Pollutants
Porous media
Soil chemistry
Soil pollution
Soils
Surface properties
Surface water
Water resources
Wetting
x‐ray microtomography
image processing
multiphase flow
particle filtration
x-ray microtomography
porous media
Colloid transport
ISSN:0022-2720, 1365-2818, 1365-2818
Online Access:Get full text
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Summary:Summary Colloidal transport and deposition are of both environmental and engineering importance. Easier access to x‐ray microtomography (XMT) coupled with improved imaging resolution has made XMT a unique and viable tool for visualizing and quantifying these processes. Currently, there is scant information in the literature addressing colloid segmentation and analysis in saturated and unsaturated porous media, in particular related to spatial partitioning of colloids. To support this need, an approach to assign segmented colloidal particles and aggregates to different partitioning classes based on their proximity to different phases is presented here. The method uses different markers for each attachment site (e.g. wetting‐nonwetting phase interfaces). An example XMT dataset from a drainage experiment is used to demonstrate the efficacy of the image processing algorithms. Flow conditions, and fluid and colloid properties, can thus be compared to the behaviour of colloids within the porous medium. This algorithm can help elucidate colloidal deposition mechanisms and the importance of different attachment sites, explore the importance of fluid properties, as well as the arrangement and shape of the colloids. Lay Summary Chemical or biological contaminants (pollutants, bacteria etc.) may attach to soil particles, or colloids, and move throughout the environment. This leads to contamination of surface water and groundwater. Our approach to study the fate of these colloids is to use an imaging technique called x‐ray microtomography (XMT), which allows us to look inside otherwise opaque materials. Thus, we can directly observe how particles move when in the presence of multiple phases (e.g. water, air, soil) with varying chemical properties and surface characteristics. After the microtomography 3D scans are collected, a challenge that remains is how to process the data to glean meaningful quantitative results. This research provides an approach for how to design an XMT study to answer colloid transport‐related questions, how to process the raw data into a quantifiable format, and lastly provides an algorithm that groups colloids together based on where they are located in the porous medium. With this toolset, scientists can investigate the innerworkings of a flow experiment and directly observe and quantify attachment and detachment of colloids under varied experimental conditions. These analyses will complement traditional column transport studies, providing a deeper understanding of the fundamental transport behaviour, and ultimately providing insight in how best to protect our water resources.
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USDOE
ISSN:0022-2720
1365-2818
1365-2818
DOI:10.1111/jmi.12874