Impact Of Fines On Gas Relative Permeability Through Sand Using Pore Networks From 3d Synchrotron Micro-Computed Tomography

Fines migration and transport in sand systems have huge influence on vital applications, including the storage and recovery of water and energy resources from the subsurface. Multi-phase flow of gas through saturated unconsolidated media takes place between the pores of sediments, physical phenomenon at the pore-scale control the flow properties. Given a sandy sediment media, gas permeability is highly affected by fine particles due to migration, clogging and bridging reducing gas flow or causing sand particles to displace creating fractures. There is a knowledge gap of fines effects on gas production from sandy sediments, especially at the pore-scale. Therefore, there is a need to model and quantify effects of fines in multi-phase flow using pore networks to better understand gas recovery systems. Three-dimensional, synchrotron micro-computed tomography images of sand sediments were obtained at Argonne National Laboratory at a resolution of 3.89 micron per voxel. Kaolinite and Montmorillonite fine particles were added in varied concentrations in six soil specimens, each system was scanned at four stages with varied saturations of brine and CO2, resulting in 20 systems. Micro-computed tomography images were processed for 3D visualization, quantification and pore network modeling. Pore Network Models were generated, and relative permeability properties were then computed for each system. Findings revealed that fines accumulate at sand-brine and brine-gas interfaces. As fines concentration increased, gas percolation decreased. Further increase in fines concentrations resulted in blocking local gas flow causing pressure variations enough to create fractures that allows gas to escape and permeability to increase back. Pore Networks and Computer-Based Two-Phase Flow Simulations can effectively be used to characterize flow in porous media. In unconsolidated media the pore space geometry will change due to sand grains movements. At high concentrations, different fines type produces altered gas flow regimes, Kaolinite resulted in fractures while montmorillonite resulted in detached gas ganglia. Generally, increasing fines reduces gas percolation and further injection of gas reduced permeability. The finds herein are critical in understanding the impact of fines migration during gas flow in sand, they can be applied to characterizing and predicting two phase properties of unconsolidated sediments

Motion cueing in driving simulators for research applications

This research investigated the perception of self-motion in driving simulation, focussing on the dynamic cues produced by a motion platform. The study was undertaken in three stages, evaluating various motion cueing techniques based on both subjective ratings of realism and objective measures of driver performance. Using a Just Noticeable Difference methodology, Stage 1 determined the maximum perceptible motion scaling for platform movement in both translation and tilt. Motion cues scaled by 90% or more could not be perceptibly differentiated from unscaled motion. This result was used in Stage 2‟s examination of the most appropriate point in space at which the platform translations and rotations should be centred (Motion Reference Point, MRP). Participants undertook two tracking tasks requiring both longitudinal (braking) and lateral (steering) vehicle control. Whilst drivers appeared unable to perceive a change in MRP from head level to a point 1.1m lower, the higher position (closer to the vestibular organs) did result in marginally smoother braking, corresponding to the given requirements of the longitudinal driving task. Stage 3 explored the perceptual trade-off between the specific force error and tilt rate error generated by the platform. Three independent experimental factors were manipulated: motion scale-factor, platform tilt rate and additional platform displacement afforded by a XY-table. For the longitudinal task, slow tilt that remained sub-threshold was perceived as the most realistic, especially when supplemented by the extra surge of the XY-table. However, braking task performance was superior when a more rapid tilt was experienced. For the lateral task, perceived realism was enhanced when motion cues were scaled by 50%, particularly with added XY-sway. This preference was also supported by improvements in task accuracy. Participants ratings were unmoved by changing tilt rate, although rapid tilt did result in more precise lane control. Several interactions were also observed, most notably between platform tilt rate and XY-table availability. When the XY-table was operational, driving task performance varied little between sub-threshold and more rapid tilt. However, while the XY-table was inactive, both driving tasks were better achieved in conditions of high tilt rate. An interpretation of these results suggests that without the benefit of significant extra translational capability, priority should be given to the minimisation of specific force error through motion cues presented at a perceptibly high tilt rate. However, XY-table availability affords the simulator engineer the luxury of attaining a slower tilt that provides both accurate driving task performance and accomplishes maximum perceived realism

Master of Science

thesisFine coal filtration and dewatering are of great importance to the coal industry due to the significant impact in the quality, shipping, and handling of clean coal. High moisture content in the clean coal product reduces its heating value, increases costs, and reduces the coke yield in the case of metallurgical coal. In this regard, it is of significant importance to improve our fundamental understanding of water removal from the pore network structures present in filtration cakes. This thesis research presents the results obtained from the analysis regarding fluid flow through packed particle beds such as those occurring during filtration in an effort to expand the studies of particle characterization and its influence on coal dewatering. The study shows the importance of high resolution x-ray microtomography (HRXMT) as an important analytical tool for the three-dimensional study of particle beds. The multiphase flow and dewatering that occurs during fine coal filtration is described, and important factors that influence the efficiency of filtration, including the particle size distribution, pressure drop, shape, and wetting characteristics of the coal particles are considered. The experiments are designed to simulate the process of coal filtration using the Lattice-Boltzmann methodology, and identify the conditions that lead to the improved water removal and moisture reduction. The thesis and research reported herein demonstrate how HRXMT and the Lattice-Boltzmann Method (LBM) can help in the short-term prediction and understanding of water removal from the pore network structures present in coal filtration cakes. Based on the analysis of HRXMT images, it is shown that the pore network structure has a significant influence on the retention of water in the filter cake. Narrow capillaries were found in the filter cakes with hydrophilic particles, while wider capillaries were mostly found in the filter cakes with hydrophobic particles. In addition, tests with different pressure drops were performed. Although the pore network structure analysis showed that the capillaries were narrower at higher initial pressures, the increase in pressure drop decreased the amount of water retained in the filter cake. The pressure drop increase helped overcome the capillary forces that retain the water in the filter cakes

Machine Learning in Aerodynamic Shape Optimization

Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep learning. We review the applications of ML in ASO to date and provide a perspective on the state-of-the-art and future directions. We first introduce conventional ASO and current challenges. Next, we introduce ML fundamentals and detail ML algorithms that have been successful in ASO. Then, we review ML applications to ASO addressing three aspects: compact geometric design space, fast aerodynamic analysis, and efficient optimization architecture. In addition to providing a comprehensive summary of the research, we comment on the practicality and effectiveness of the developed methods. We show how cutting-edge ML approaches can benefit ASO and address challenging demands, such as interactive design optimization. Practical large-scale design optimizations remain a challenge because of the high cost of ML training. Further research on coupling ML model construction with prior experience and knowledge, such as physics-informed ML, is recommended to solve large-scale ASO problems