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published_or_final_version / Computer Science and Information Systems / Master / Master of Philosophy

published_or_final_version / Chemistry / Doctoral / Doctor of Philosophy

published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

This thesis concerns healthcare management and specifically addresses the problems of operating room planning and waiting list management. The operating room department is one of the most expensive areas within the healthcare system which necessitates many expensive resources such as staff, equipment and medicine. The planning of operating rooms is a complex task involving many dependencies and conflicting factors and hence careful operating room planning is critical to attain high productivity. One part of the planning process is to determine a Master Surgery Schedule (MSS). An MSS is a cyclic timetable that specifies the allocation of the surgical groups into different blocks of operating room time. Using an optimization-based approach, this thesis investigates whether the MSS can be adapted to better meet the varying surgery demand. Secondly, an extended optimization-based approach, including post-operative beds, is presented in which different policies related to priority rules are simulated to demonstrate their affect on the average waiting time. The problem of meeting the uncertainty in demand of patient arrival, as well as surgery duration, is then incorporated. With a combination of simulation and optimization techniques, different policies in reserving operating room capacity for emergency cases together with a policy to increase staff in stand-by, are demonstrated. The results show that, by adopting a certain policy, the average patient waiting time and surgery cancellations are decreased while operating room utilization is increased. Furthermore, the thesis focuses on how different aspects of surgery pre-conditions affect different performance measures related to operating room planning. The emergency surgery cases are omitted and the studies are delimited to concern the elective healthcare process only. With a proposed simulation model, an experimental tool is offered, in which a number of analyses related to the process of elective surgeries can be conducted. The hypothesis is that, sufficiently good estimates of future surgery demand can be assessed at the referral stage. Based on this assumption, an experiment is conducted to explore how different policies of managing incoming referrals affect patient waiting times. Related to this study, possibility of using data mining techniques to find indicators that can help to estimate future surgery demand is also investigated. Finally, in parallel, an agent-based simulation approach is investigated to address these types of problems. An agent-based approach would probably be relevant to consider when multiple planners are considered. In a survey, a framework for describing applications of agent based simulation is provided.

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In looking to the future of naval warfare, the US Navy has committed itself to development of future classes of an All-Electric Ship (AES) that will incorporate significant technological advancements in the areas of power management, advanced sensor equipment and weaponry, reconfigurability, and survivability systems while simultaneously increasing overall system efficiencies and decreasing the operational costs of the future naval fleet. As part of the consortium responsible for investigating the viability of numerous next-generation technologies, the University of Texas at Austin is dedicated to providing the capabilities and tools to better address thermal management issues aboard the future AES. Research efforts at the University of Texas in Austin have focused on the development of physics-based, dynamic models of components and subsystems that simulate notional future AES, system-level, thermal architectures. This research has resulted in the development of an in-house thermal management tool, known as the Dynamic Thermal Modeling and Simulation (DTMS) Framework. The work presented herein has sought to increase the modeling capabilities of the DTMS Framework and provide valuable tools to aid both developers and users of this simulation environment. Using numerical approximations of complex physical behaviors, the scope of the DTMS Framework has been expanded beyond elements of thermal-fluid behaviors to capture the dynamic, transient nature of far broader, more complex architectures containing interconnected thermal-mechanical-electrical components. Sophisticated interfacial systems have also been developed that allow integration of the DTMS Framework with external software products that improve and enhance the user experience. Developmental tools addressing customizable presentation of simulation data, debugging systems that aid in introduction of new features into the existing framework, and error-reporting mechanisms to ease the process of utilizing the power of the simulation environment have been added to improve the applicability and accessibility of the DTMS Framework. Finally, initial efforts in collaboration with Mississippi State University are presented that provide a graphical user interface for the DTMS Framework and thus provide far more insight into the complex interactions of numerous shipboard systems than would ever be possible using raw numerical data. / text

Most available data from shale production zones tends to point towards the presence of complex hydraulic fracture networks, especially in the Barnett and Marcellus formations. Representing these complex hydraulic fracture networks in reservoir simulators while incorporating the geo-mechanical parameters and fracture apertures is a challenge. In our work we developed a fracture to production simulation workflow using complex hydraulic fracture propagation model and a commercial reservoir simulator. The workflow was applied and validated using geological, stimulation and production data from the Marcellus shale. For validation, we used published data from a 5200 ft. long horizontal well drilled in the lower Marcellus. There were 14 fracturing stages with micro-seismic data and an available production history of 9 months. Complex hydraulic fractures simulations provided the fracture network geometry and aperture distributions as the output, which were up-scaled to grid block porosity and permeability values and imported into a reservoir model for production simulation and history match. The approach of using large grid blocks with conductivity adjustment to represent hydraulic fractures in a reservoir simulator which has been employed in this workflow was validated by comparing with published numerical and analytical solutions. Our results for history match were found to be in reasonable agreement with published results. The incorporation of apertures, complexity and geo-mechanics into reservoir models through this workflow reduces uncertainty in reservoir simulation of shale plays and leads to more realistic production forecasting. The workflow was utilized to study the effect of fracture conductivity damage on production. Homogenous and heterogeneous damage cases were considered. Capillary pressures, determined using empirical relationships and experimental data, were studied using the fracture to production workflow. Assuming homogenous instead of heterogeneous permeability damage in reservoir simulations was shown to have a significant impact on production forecasting, overestimating production by 70% or more over the course of two years. Capillary pressure however was less significant and ignoring capillary pressure in damaged hydraulic fractures led to only 3% difference in production in even the most damaged cases. / text

Conformance control has long been a compelling subject in improving waterflood oil recovery. By blocking the areas previously swept by water, subsequently injected water is allowed to sweep the remaining unswept portions of the reservoir and thereby increase the ultimate oil recovery. One technique that has received a great deal of attention recently in achieving this in-depth water shut-off is crosslinked gel injection. However, processing and predicting the performance of these gels in complex petroleum reservoirs is known to be extremely challenging. A model that accurately represents the reservoir features, chemical properties, and displacement mechanisms is, therefore, required. In this study, we further developed the UT in-house numerical reservoir simulator, branded as UTGEL. Our first focus was to enable UTGEL to simulate a new type of temperature-resistant and salt-tolerant pre-crosslinked swellable particle gel, known as Preformed Particle Gel or PPG. A series of numerical simulations have been conducted to match with experimental data and generate parameters for full field scale simulation. Five laboratory experimental matching attempts were successfully performed using the UTGEL simulator in this study. The matched experiments included a fracture model, two sandpack models, a sandstone coreflood experiment, and a parallel sandpack model. The second focus of this study was to investigate the applications of PPG in blocking high-permeability layers, fractures, and conduits. A number of synthetic and actual field cases were generated to study the performance of PPG in (1) reservoirs with various layered permeability contrasts, from extremely low to extremely high permeability contrasts, (2) reservoirs containing extensive conduits or channels, and (3) real field cases where heterogeneity had been identified unfavorable to the waterflood efficiency. The simulation outcomes indicated significant incremental oil recovery from PPG treatment ranging from less than 5% to almost 30%. A number of sensitivity analyses were also conducted to provide some insights on the optimal PPG treatment design. Lastly, to enhance the capability of UTGEL in simulating gel transport in diverse scenarios, a novel Embedded Discrete Fracture Modeling (EDFM) concept was implemented into UTGEL in this study, allowing multiple sets of fracture planes and conduits with dip angles and orientations to be modeled and simulated with gel treatments for the first time with a rather computationally inexpensive method. Although the developed simulator requires further improvement and validation against wider reservoir and fluid conditions, the representative results from a number of generated models in this study have suggested another step forward towards achieving realistic reservoir modeling and advanced gel transport simulation. / text

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