Browsing by Author "Yang, Xinmin"
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Item Direct numerical simulation of pore-scale flow in a bead pack: Comparison with magnetic resonance imaging observations(2013-04) Yang, Xinmin; Scheibe, T. D.; Richmond, M. C.; Perkins, W. A.; Vogt, Sarah J.; Codd, Sarah L.; Seymour, Joseph D.; McKinley, M. I.A significant body of current research is aimed at developing methods for numerical simulation of flow and transport in porous media that explicitly resolve complex pore and solid geometries, and at utilizing such models to study the relationships between fundamental pore-scale processes and macroscopic manifestations at larger (i.e., Darcy) scales. A number of different numerical methods for pore-scale simulation have been developed, and have been extensively tested and validated for simplified geometries. However, validation of pore-scale simulations of fluid velocity for complex, three-dimensional (3D) pore geometries that are representative of natural porous media is challenging due to our limited ability to measure pore-scale velocity in such systems. Recent advances in magnetic resonance imaging (MRI) offer the opportunity to measure not only the pore geometry, but also local fluid velocities under steady-state flow conditions in 3D and with high spatial resolution. In this paper, we present a 3D velocity field measured at sub-pore resolution (tens of micrometers) over a centimeter-scale 3D domain using MRI methods. We have utilized the measured pore geometry to perform 3D simulations of Navier–Stokes flow over the same domain using direct numerical simulation techniques. We present a comparison of the numerical simulation results with the measured velocity field. It is shown that the numerical results match the observed velocity patterns well overall except for a variance and small systematic scaling which can be attributed to the known experimental uncertainty in the MRI measurements. The comparisons presented here provide strong validation of the pore-scale simulation methods and new insights for interpretation of uncertainty in MRI measurements of pore-scale velocity. This study also provides a potential benchmark for future comparison of other pore-scale simulation methods. © 2012 Elsevier Science. All rights reserved.Item Evaluation of biofilm image thresholding methods(2001-04) Yang, Xinmin; Beyenal, Haluk; Harkin, Gary; Lewandowski, ZbigniewTo evaluate biomass distribution in heterogeneous biofilms from their microscope images, it is often necessary to perform image thresholding by converting the gray-scale images to binary images consisting of a foreground of biomass material and a background of interstitial space. The selection of gray-scale intensity used for thresholding is arbitrary but under the control of the operator, which may produce unacceptable levels of variability among operators. The quality of numerical information extracted from the images is diminished by such variability, and it is desirable to find a method that improves the reproducibility of thresholding operation. Automatic methods of thresholding provide this reproducibility, but often at the expense of accuracy, as they consistently set thresholds that differ significantly from what human operators would chose. The performance of five automatic image thresholding algorithms was tested in this study; (1) local entropy; (2) joint entropy; (3) relative entropy; (4) Renyi’s entropy; and (5) iterative selection. Only the iterative selection method was satisfactory in that it was consistently setting the threshold level near that set manually. The extraction of feature information from biofilm images benefits from automatic thresholding and can be extended to other fields, such as medical imaging.Item Quantifying biofilm structure using image analysis(2000-01) Yang, Xinmin; Beyenal, Haluk; Harkin, Gary; Lewandowski, ZbigniewWe have developed and implemented methods of extracting morphological features from images of biofilms in order to quantify the characteristics of the inherent heterogeneity. This is a first step towards quantifying the relationship between biofilm heterogeneity and the underlying processes, such as mass-transport dynamics, substrate concentrations, and species variations. We have examined two categories of features, areal, which quantify the relative magnitude of the heterogeneity and textural, which quantify the microscale structure of the heterogeneous elements. The feature set is not exhaustive and has been restricted to two-dimensional images to this point. Included in this paper are the methods used to extract the structural information and the algorithms used to quantify the data. The features discussed are porosity, fractal dimension, diffusional length, angular second moment, inverse difference moment and textural entropy. We have found that some features are better predictors of biofilm behavior than others and we discuss possible future directions for research in this area.