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

No description available.

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

abstract: Over the past century, the world has become increasingly more complex. Modern systems (i.e blockchain, internet of things (IoT), and global supply chains) are inherently difficult to comprehend due to their high degree of connectivity. Understanding the nature of complex systems becomes an acutely more critical skill set for managing socio-technical infrastructure systems. As existing education programs and technical analysis approaches fail to teach and describe modern complexities, resulting consequences have direct impacts on real-world systems. Complex systems are characterized by exhibiting nonlinearity, interdependencies, feedback loops, and stochasticity. Since these four traits are counterintuitive, those responsible for managing complex systems may struggle in identifying these underlying relationships and decision-makers may fail to account for their implications or consequences when deliberating systematic policies or interventions. This dissertation details the findings of a three-part study on applying complex systems modeling techniques to exemplar socio-technical infrastructure systems. In the research articles discussed hereafter, various modeling techniques are contrasted in their capacity for simulating and analyzing complex, adaptive systems. This research demonstrates the empirical value of a complex system approach as twofold: (i) the technique explains systems interactions which are often neglected or ignored and (ii) its application has the capacity for teaching systems thinking principles. These outcomes serve decision-makers by providing them with further empirical analysis and granting them a more complete understanding on which to base their decisions. The first article examines modeling techniques, and their unique aptitudes are compared against the characteristics of complex systems to establish which methods are most qualified for complex systems analysis. Outlined in the second article is a proof of concept piece on using an interactive simulation of the Los Angeles water distribution system to teach complex systems thinking skills for the improved management of socio-technical infrastructure systems. Lastly, the third article demonstrates the empirical value of this complex systems approach for analyzing infrastructure systems through the construction of a systems dynamics model of the Arizona educational-workforce system, across years 1990 to 2040. The model explores a series of dynamic hypotheses and allows stakeholders to compare policy interventions for improving educational and economic outcome measures. / Dissertation/Thesis / Doctoral Dissertation Systems Engineering 2020

Carbon sequestration is paramount to reducing climate change. Grasslands, representing 40% of all terrestrial area, can serve as a primary sequestration location if optimal management strategies can be realized. This study used system dynamics modeling to examine the temporal dynamics of carbon stocks and flows in response to grass species composition, grazing intensity, and temperature and precipitation changes at the landscape level. While there are other biogeochemical models in existence, they are either meant to model large areas, including globally, or are meant to be at a farm level and have limited plot sizes, limiting the options for rangeland managers to test management strategies in larger areas. The aims included conducting a field study of the rangeland, create an initial model; evaluate how the model responded to grazing, temperature, and precipitation changes; and compare the model outcomes to prior work to test the behavior of the model as the start of validation. This thesis used four plant functional groups (C3 and C4 grasses, forbs, and legumes) as the base groups for the model. C4 grasses were not found in in the field study but served to test whether the model detected changes in sequestration when grassland composition is changed. The results demonstrated an approach of using functional groups in system dynamics modeling to optimize carbon sequestration while accounting for diverse management strategies, as has been seen in other biogeochemical models. The model was aligned with prior field research in terms of carbon sequestration levels. The model was able to note differences in grazing regimes, temperature, and precipitation changes in terms of carbon sequestration. Grazing scenarios showed that while increased grazing impacted aboveground litter, it had little impact on sequestration; there was only a 4% increase in carbon with no grazing, Changes in temperature, up to 3°C, were predicted to increase carbon sequestration by 16% from 0.442 to 0.514 kg*m-2*day-1 while decreases in precipitation, both alone and in combination with increasing temperatures, was predicted to decrease sequestration up to 44%. This has to do with the grassland composition, ii especially as this was a C3 dominated grassland which grows in the winter and early spring and required more water but lower temperatures for growth. Future research should continue model validation, test additional functional groups like shrubs, implement more soil carbon pools and flows and add a nitrogen component to the model.

Bovine respiratory disease (BRD) is a significant health problem for cattle producers in terms of economic cost and animal welfare. In the United States (US), it is one of the leading causes of sickness and death in beef calves prior to weaning. Although much research has been conducted to develop vaccines for prevention and antibiotics for treatment, the morbidity and mortality of BRD in beef calves prior to weaning has not improved over the years. The identification of risk factors associated with BRD is an area of focus which might ultimately allow producers to minimize morbidity and mortality from BRD. Little research has been performed to understand factors contributing to the risk of BRD in beef calves prior to weaning. BRD affects the beef cattle industry through losses due to mortality, prevention cost, treatment cost, or morbidity effect on productivity. Currently, the economic losses due to BRD for beef calves prior to weaning is not available. Price paid for feeder cattle is a major factor influencing the income of producers. The effect of BRD is a complicated problem since the parameters associated with the cost of BRD in beef cow-calf production are variable and interrelated. To better understand the economic effect of BRD in beef calves prior to weaning, concepts of uncertainty, variability, stochasticity, nonlinearity, and feedback might be involved during the process of assessing risk. The objectives of this dissertation are the following: 1) to test if calf sex, birth weight, and age of dam are associated with BRD of beef calves prior to weaning in different age periods; 2) to identify factors affecting the national market price of beef feeder cattle in the US and how the prices change over time; 3) to investigate the prevention and treatment cost of BRD in beef calves prior to weaning; 4) to estimate the economic cost of BRD in US beef calves prior to weaning; and 5) to understand the effect of BRD occurrence or absence on the national net income of the US beef cow-calf industry.

No description available.

Experimental Spatial Dynamics Modeling (ESDM) is the new process of constructing a three dimensional, complex-valued dynamic model of a harmonically vibrating structure using numerical models and laser-based experimental data obtained from a Scanning Laser Doppler Vibrometer (SLDV). In ESDM process, a finite element formulation is used to construct a numerical model of a structure. A conventional finite element such as rod, beam, or plate element, can be used to construct the numerical model of a structure from its mid-plane. In this research, the damped flat shell element is developed to construct the numerical models of a cantilever beam and a simply supported flat plate. The velocity transformation function developed in this research will make possible to use the FE model, constructed by the damped flat shell element, and the laser-based experimental data within a framework of ESDM in the consistent manner. / Master of Science

Estimating the cost of new technology insertion into an existing (or new) operating environment is of great concern and interest for those entities that own and operate that technology. New technology has many cost requirements associated with it, for instance; design, manufacturing, operation, maintenance and disposal all add to the life-cycle cost of a technology. Estimation and planning methods are needed to better match the costs associated with technology life-cycle requirements (design, manufacturing, etc.) in order to optimize the spending of funds. By optimizing (or closely matching) predicted technology life-cycle costs to a budget the new technology system will have a high probability of operating more efficiently and will minimize costs. System Dynamics has been used to understand and simulate how complex systems of people and technologies operate over time. Decisions (such as how much funding is allocated when in a technology life-cycle) that occur temporally or in a complex environment (i.e., many causes and effects) can be simulated to evaluate the impact the decision may have. Currently, the majority of decision theories and tools are focused on one moment in time (event-focused) rather than including the dynamic nature that decisions can have over time. Evaluating decisions at one instant versus taking into account the life-cycle impact a decision can have, is especially important to the US Government, where investment decisions can involve billions of dollars today, but potentially hundreds of billions later for technology life-cycle requirements. The Navy has experienced large cost overruns in the implementation of new technologies especially in the operations, support and disposal life-cycle phases. There is a lack of detailed knowledge of the dynamic nature of the technology operations, support and disposal (OS&D) processes undertaken by aircraft-carrier builders and planners. This research effort is to better understand and simulate the dynamics prevalent in the new technology implementation process and use a dynamic modeling technique, namely, System Dynamics in our study. A System Dynamics model based on the information and data obtained from experts including; General Dynamics - Newport News Shipbuilding, the Naval Sea Command Cost Estimating Group, and Virginia Polytechnic and State University - System Performance Laboratory. The model was constructed to simulate and predict the cost of operating, maintaining and disposing of a new technology. The investigation of the dynamics yields four dominant behaviors that characterize the technology OS&D process. These four dynamic behaviors are; exponential growth, goal seeking, overshoot & collapse and S-shaped growth with overshoot. Furthermore, seven dynamic hypotheses in the system are investigated. The model predicts an increase in the risk and degradation of new technologies leads to an increase in the total costs in the technology OS&D process. Three interesting insights that lead to increased total OS&D costs were; an inequality between the requirements for OS&D and provided budget, any delay in additional funding being provided and that as the new technology system grew older, it became less costly to maintain. / Master of Science