Dust is ubiquitous in underground mine activities. Continuous inhalation of dust could lead to irreversible occupational diseases. Dust particles of size lower than 75.0 µm, also known as float coal dust, can trigger a coal dust explosion following a methane ignition. Ventilation air carries the float coal dust from the point of production to some distance before it’s deposited on the surfaces of underground coal mine. Sources of dust are widely studied, but study of dust transportation has been mainly based on experimental data and simplified models. An understanding of dust transportation in the mine airways is instrumental in the implementation of local dust control strategies. This thesis presents techniques for sampling float coal dust, computational fluid dynamics (CFD) analysis, and mathematical modeling to estimate average dust deposition in an underground coal mine. Dust samples were taken from roof, ribs, and floor at multiple areas along single air splits from longwall and room and pillar mines. Thermogravimetric analysis of these samples showed no conclusive trends in float coal dust deposition rate with location and origin of dust source within the mine network. CFD models were developed using the Lagrangian particle tracking approach to model dust transportation in reduced scale model of mine. Three dimensional CFD analysis showed random deposition pattern of particle on the mine model floor. A pseudo 2D model was generated to approximate the distance dust particles travel when released from a 7 ft. high coal seam. The models showed that lighter particles released in a high airflow field travel farthest. NIOSH developed MFIRE software was adopted to simulate dust transportation in a mine airway analogous to fume migration. The simulations from MFIRE can be calibrated using the dust sampling results to estimate dust transportation in the ventilation network.

During injection of a high-viscosity, non-Newtonian polymer into a long horizontal well, a significant pressure drop occurs along the well length. Computational Fluid Dynamics (CFD) modeling of the shear-thinning flow of polymer in the wellbore, coupled with the viscoelastic flow in composite gravel-pack/near-well formation zone, was carried out to develop convenient correlations for axial pressure values of both Newtonian and non-Newtonian fluids along the well length, for use in chemical EOR simulations. The detailed CFD modeling of the non-Newtonian flow behavior of polymer within the horizontal wellbore, completion zone and the near-well formation, not only allows accurate accounting of pressure distribution along the long horizontal well, but also can be employed for screening diagnosis for possible injectivity inefficiencies resulting from non-uniform pressure values. At both high and low injection rates, CFD modeling predicts non-uniform pressure distributions for highly viscous fluids. The inclusive pressure correlation was implemented into UTCHEM, a University of Texas at Austin research simulator, to determine the importance of including pressure drop in polymer injections. Early times (i.e., less than 100 days) yielded a significant oil recovery deviation from a uniform pressure wellbore. However, at later times the recovery loss generated by the pressure decrease was deemed negligible; therefore, the traditional assumption regarding uniform pressure in horizontal wellbores was still reasonable for highly viscous non-Newtonian flow. This CFD study is the first mechanistic investigation of the polymer injectivity with detailed description of the wellbore, completion zone and near-well formation, and with full accounting of the shear-thinning rheology for pipe flow and the viscoelastic rheology of polymer in porous media. With increased use of very high molecular-weight polymers for chemical EOR processes for mobility control, the latter mechanism is known to be critical. / text

Doctor of Philosophy / Biological & Agricultural Engineering / Mark E. Casada / Ronaldo G. Maghirang / Wind erosion is an important problem in many locations, including the Great Plains, that needs to be controlled to protect soil and land resources. This research was conducted to assess the effectiveness of vegetation (specifically, standing vegetation and tree barriers) as controls for wind erosion. Specific objectives were to: (1) measure sand transport and abrasion on artificial standing vegetation, (2) determine porosity and drag of a single row of Osage orange (Maclura pomifera) barrier, (3) assess effectiveness of Osage orange barriers in reducing dust, (4) predict airflow through standing vegetation, and (5) predict airflow and particle collection through Osage orange barriers. Wind tunnel tests were conducted to measure wind speed profiles, relative abrasion energies, and sand discharge rates for bare sand and for two vegetation heights (150 and 220 mm) at various densities of vegetation. Results showed that vegetation density was directly related to threshold velocity and inversely related to sand discharge. The coefficient of abrasion was adversely affected by saltation discharge but did not depend on wind speed. Field tests measured the aerodynamic and optical porosities of Osage orange trees using wind profiles and image analysis, respectively, and an empirical relationship between the two porosities was derived. Vertical wind profiles were also used to estimate drag coefficients. Optical porosity correlated well with the drag coefficient. Field measurements also showed a row of Osage orange barrier resulted in particulate concentration reduction of 15 to 54% for PM2.5 and 23 to 65% for PM10. A computational fluid dynamics (CFD) software (OpenFOAM) was used to predict airflow in a wind tunnel with artificial standing vegetation. Predicted wind speeds differed slightly from the measured values, possibly due to oscillatory motions of the standing vegetation not accounted for in the CFD simulation. OpenFOAM was also used to simulate airflow and particle transport through a row of Osage orange barrier. Predicted and measured wind speeds agreed well. Measured dust concentration reduction at two points (upwind and downwind) were also similar to the predicted results.

abstract: Gnamma pit is an Australian aboriginal term for weathering pit. A mix of weathering and aeolian processes controls the formation of gnamma pits. There is a potential to utilize gnamma as an indicator of paleowind intensity because gnamma growth is promoted by the removal of particles from gnamma pits by wind, a process referred to as deflation. Wind tunnel tests determining the wind velocity threshold of deflation over a range of pit dimensions and particles sizes are conducted. Computational fluid dynamics (CFD) modeling utilizing the Re-Normalisation Group (RNG) K-Epsilon turbulence closure is used to investigate the distribution of wall shear stress and turbulent kinetic energy. An empirical equation is proposed to estimate shear stress as a function of the wind velocity and pit depth dimensions. With this equation and Shields Diagram, the wind velocity threshold for evacuating particles in the pit can be estimated by measuring the pit depth ratio and particle size. It is expected that the pit would continue to grow until this threshold is reached. The wind speed deflation threshold is smaller in the wind tunnel than predicted by the CFD and Shields diagram model. This discrepancy may be explained by the large turbulent kinetic energy in the gnamma pit as predicted by the CFD model as compared to the flat bed experiments used to define the Shields diagram. An empirical regression equation of the wind tunnel data is developed to estimate paleowind maximums. / Dissertation/Thesis / Masters Thesis Geography 2015

Cette thèse s’inscrit dans le cadre du développement d’un procédé de décarbonation directe du méthane par voie plasma pour la coproduction de noir de carbone et d’hydrogène. Ce procédé est particulièrement intéressant dans la contexte d'un mix électrique faiblement carboné en offrant une solution pour diminuer drastiquement les émissions des procédés actuels de production de noir de carbone et d’hydrogène qui comptent parmi les procédés actuels les plus polluants en termes d'émissions de CO2. A court terme, la viabilité économique de ce procédé passe par la valorisation simultanée de ces deux produits : noir de carbone et hydrogène. À plus long terme, il pourrait représenter une réelle alternative à la capture et le stockage du CO2.Cette étude a pour but de proposer des méthodes numériques fiables et robustes afin de mieux comprendre, contrôler, voire optimiser les caractéristiques morphologiques des noirs de carbone issus de ce procédé, caractéristiques qui jouent un rôle primordial sur la qualité et les applications des noirs de carbone. Elle traite ainsi de l’évolution de systèmes carbonés en partant du combustible sous sa forme moléculaire jusqu’à la formation de nanoparticules puis de microstructures solides et aborde les phénomènes de nucléation, de croissance chimique, de croissance par coagulation, de maturation et d’agrégation.Des outils et des méthodes numériques ont ainsi pu être développés afin de simuler la formation de particules solides au sein d’un écoulement fluide. Ceux-ci purent être implémentés avec succès à un code CFD. Enfin des simulations numériques du procédé en question ont été réalisées en intégrant les phénomènes de transferts thermiques et de turbulence spécifiques aux plasmas thermiques. / This thesis takes part of the development of a direct decarbonation process of methane by plasma to produce both carbon black and hydrogen. This process is particularly interesting in an electrical mix context with low carbon emission. It proffers a solution to reduce drastically CO2 emissions rejected by the current carbon black and hydrogen ways of production, which are ones of the most polluting industrial processes.This study aims to develop reliable and robust numerical methods for a better understanding and a greater control of the morphologic features of the carbon black generated. These features play a key role in the quality and applications of the carbon black produced. This research retraces the evolution of the carbon structure from the molecules of the fuel to the formation of nanoparticles and solid microstructures. It tackles different phenomenon such as: nucleation, chemical growth, coagulation, maturity and aggregation.Numerical tools and methods were developed thereby and enable to simulate carbon particle formation. They were successfully implemented in a commercial CFD software. Eventually numerical simulation of the plasma process were performed, integrating heat transfers and turbulence.

The role of sensor technology is obvious in improvement and optimization of many industrial processes. The sensor films, which are considered the core of chemical sensors, have the capability to detect the presence and concentration of a specific chemical substance. Such sensor films achieve selectivity by detecting the interaction of the specific chemical substance with the sensor material through selective binding, adsorption and permeation of analyte. This research focuses on development and verification of a comprehensive mathematical model of mixed metal oxide thin film growth using spray pyrolysis technique (SPT). An experimental setup is used to synthesize mixed metal oxide films on a heated substrate. The films are analyzed using a variety of characterization tools. The results are used to validate the mathematical model. There are three main stages to achieve this goal: 1) A Lagrangian-Eulerian method is applied to develop a CFD model of atomizing multi-component solution. The model predicts droplet characteristics in flight, such as spatial distribution of droplet size and concentration. 2) Upon reaching the droplets on the substrate, a mathematical model of multi-phase transport and chemical reaction phenomena in a single droplet is developed and used to predict the deposition of thin film. The various stages of droplet morphology associated with surface energy and evaporation are predicted. 3) The processed films are characterized for morphology and chemical composition (SEM, XPS) and the data are used to validate the models as well as investigate the influence of process parameters on the structural characteristics of mixed metal oxide films. The structural characteristics are investigated of nano structured thin films comprising of ZnO, SnO2, ZnO+In2O3 and SnO2+In2O3 composites. The model adequately predicts the size distribution and film thickness when the nanocrystals are well-structured at the controlled temperature and concentration.

<p>Uncertainty analysis is of great use both for calculating outputs that are more akin to real<br> flight, and for optimization to more robust shapes. However, implementation of uncertainty<br> has been a longstanding challenge in the field of aerodynamics due to the computational cost<br> of simulations. Geometric uncertainty in particular is often left unexplored in favor of uncer-<br> tainties in freestream parameters, turbulence models, or computational error. Therefore, this<br> work proposes a method of geometric uncertainty analysis for aerodynamic shapes that miti-<br> gates the barriers to its feasible computation. The process takes a two- or three-dimensional<br> shape and utilizes a combination of multifidelity meshes and Gaussian process regression<br> (GPR) surrogates in a multifidelity Monte Carlo (MFMC) algorithm. Multifidelity meshes<br> allow for finer sampling with a given budget, making the surrogates more accurate. GPR<br> surrogates are made practical to use by parameterizing major factors in geometric uncer-<br> tainty with only four variables in 2-D and five in 3-D. In both cases, two parameters control<br> the heights of steps that occur on the top and bottom of airfoils where leading and trailing<br> edge devices are attached. Two more parameters control the height and length of waves<br> that can occur in an ideally smooth shape during manufacturing. A fifth parameter controls<br> the depth of span-wise skin buckling waves along a 3-D wing. Parameters are defined to<br> be uniformly distributed with a maximum size of 0.4 mm and 0.15 mm for steps and waves<br> to remain within common manufacturing tolerances. The analysis chain is demonstrated<br> with two test cases. The first, the RAE2822 airfoil, uses transonic freestream parameters<br> set by the ADODG Benchmark Case 2. The results show a mean drag of nearly 10 counts<br> above the deterministic case with fixed lift, and a 2 count increase for a fixed angle of attack<br> version of the case. Each case also has small variations in lift and angle of attack of about<br> 0.5 counts and 0.08◦, respectively. Variances for each of the three tracked outputs show that<br> more variability is possible, and even likely. The ONERA M6 transonic wing, popular due<br> to the extensive experimental data available for computational validation, is the second test<br> case. Variation is found to be less substantial here, with a mean drag increase of 0.5 counts,<br> and a mean lift increase of 0.1 counts. Furthermore, the MFMC algorithm enables accurate<br> results with only a few hours of wall time in addition to GPR training. </p>