Fractured reservoirs are commonly simulated using the Dual Porosity model, but for many major fields, the model does not match field results. For these cases, it is necessary to perform a more complex simulation including either individual fractures or pseudofracture groups modeled in their own grid blocks. Discrete Fracture Modeling (DFN) is still a relatively new field, and most research on it up to this point has been done with Delaunay tessellations. This research investigates an alternative approach using Voronoi diagrams, yet applying the same DFN principles outlined in previous works. Through the careful positioning of node points, a grid of Voronoi polygons can be produced so that block boundaries fall along the fractures, allowing us to use the DFN simulation methods as proposed in the literature. Using Voronoi diagrams allows us to use far fewer polygons than the Delaunay approach, and also allows us to perfectly align flow so as to eliminate grid alignment errors that plagued previous static systems. The nature of the Voronoi polygon further allows us to simplify permeability calculations due to orthogonality and, by extension, is more accurate than the commonly used cornerpoint formulation for non-square grid blocks.

An integrated full-field study was conducted on the Monument Northwest field located in Kansas. The purpose of this study was to determine the feasibility and profitability of a waterflood using numerical simulation. Outlined in this thesis is a methodology for a deterministic approach. The data history of the wells in the field beginning from spud date were gathered and analyzed into information necessary for building an upscaled reservoir model of the field. Means of increasing production and recovery from the field via a waterflood was implemented. Usually, at the time of such a redevelopment plan or scheme to improve field performance, a tangible amount of information about the reservoir is already known. Therefore it is very useful incorporating knowledge about the field in predicting future behavior of the field under certain conditions. The need for an integrated reservoir study cannot be over-emphasized. Information known about the reservoir from different segments of the field exploration and production are coupled and harnessed into developing a representative 3D reservoir model of the field. An integrated approach is used in developing a 3D reservoir model of the Monument Northwest field and a waterflood is evaluated and analyzed by a simulation of the reservoir model. From the results of the reservoir simulation it was concluded that the waterflood project for the Monument Northwest field is a viable and economic project.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 1990. / Thesis Advisor(s): Lawphongpanich, Siriphong. Second Reader: Block, Paul. "September 1990." Description based on title screen as viewed on December 22, 2009. DTIC Descriptor(s): Maintenance, Stations, Deployment, United States, Optimization, Environments, Peacetime, Models, Training, Naval Personnel, Integer Programming, Algebra, Efficiency, Cycles, Supply Depots, Aircraft Carriers, Naval Operations, Mixing, Microcomputers, Budgets, Mathematical Models. DTIC Identifier(s): Aircraft Carriers, Deployment, Theses, Military Forces(United States), Computer programs, Computerized Simulation, Maintenance, Naval Personnel. Author(s) subject terms:Carrier, Optimization, Deployment Model. Includes bibliographical references (p. 63). Also available in print.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 1990. / Thesis Advisor(s): Parry, Samuel H. Second Reader: Hoffman, James. "September 1990." Description based on title screen as viewed on December 18, 2009. DTIC Descriptor(s): Routing, Tactical Analysis, Experimental Data, Models, Theses, Variables, Operation, Active Duty, Casualties, Officer Personnel, Army Operations, Decision Aids, Marine Corps Operations, Measurement, Methodology. DTIC Identifier(s): Optimization. Author(s) subject terms: CAMMS/SHAW, Tactical Optimum Path. Includes bibliographical references (p. 108-110). Also available in print.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references (leaves 331-337). Available also in a digital version from Dissertation Abstracts.

The internet has become a more prominent part of people’s lives. Clickstream and other online data have enabled researchers to better understand consumers’ decision-making behavior in a variety of application areas. This dissertation focuses on using clickstream data in two application areas: the airline industry and the field of education. The first study investigates if airline passengers departing from or arriving to a multi-airport city actually consider itineraries at the airports not considered to be their preferred airport. It was found that customers do consider fares at multiple airports in multi-airport cities. However, other trip characteristics, typically linked to whether a customer is considered business or leisure, were found to have a larger impact on customer behavior than offered fares at competing airports. The second study evaluates airline customer search and purchase behavior near the advance purchase deadlines, which typically signify a price increase. Search and purchase demand models were constructed using instrumented two-stage least squares (2SLS) models with valid instruments to correct for endogeneity. Increased demand was found before each deadline, even though these deadlines are not well-known among the general public. It is hypothesized that customers are able to use two methods to unintentionally book right before these price increases: (1) altering their travel dates by one or two days using the flexible dates tools offered by an airline’s or online travel agency’s (OTA) website to receive a lower fare, (2) booking when the coefficient of variation across competitor fares is high, as the dynamics of one-way and roundtrip pricing differ near these deadlines. The third study uses clickstream data in the field of education to compare the success of the traditional, flipped, and micro-flipped classrooms as well as their impacts on classroom attitudes. Students’ quiz grades were not significantly different between the traditional and flipped classrooms. The flipped classroom reduced the impact of procrastination on success. In the end, it was found that micro-flipped was most preferred by students as it incorporated several benefits of the flipped classroom without the effects of a learning curve.

The goal of this master's thesis research is to enhance the stroke generation capabilities and musical expressivity in robotic drummers. The approach adopted is to understand the physics of human fingers-drumstick-drumhead interaction and try to replicate the same behavior in a robotic drumming system with the minimum number of degrees of freedom. The model that is developed is agnostic to the exact specifications of the robotic drummer that will attempt to emulate human like drum strokes, and therefore can be used in any robotic drummer that uses actuators with complete control over the motor position angle. Initial approaches based on exploiting the instability of a PID control system to generate multiple bounces and the limitations of this approach are also discussed in depth. In order to assess the success of the model and the implementation in the robotic platform a subjective evaluation was conducted. The evaluation results showed that, the observed data was statistically equivalent to the subjects resorting to a blind guess in order to distinguish between a human playing a multiple bounce stroke and a robot playing a similar kind of stroke.

Understanding flow processes of sea and fresh water through complex coastal regions is of utmost importance for a number of applications of interest to the scientific and engineering community, including wetland health and restoration, inland flooding due to tropical storms and hurricanes, and navigation through coastal waters. In such regions, the existence of vegetation increases flow resistance, which is a major factor in determining velocity and water level distribution in wetlands and inland. Commonly, the momentum loss due to vegetation is included in a bottom friction term in the model equations; however, such models may oversimplify the complex resistance characteristics of such a system. With recent increases in computational capabilities, it is now feasible to develop and implement more intricate resistance models that more accurately capture these characteristics. We present two methods for modeling flow through vegetated regions. With the first method, we employ mathematical and computational upscaling techniques from the study of subsurface flow to parametrize drag in a complex heterogeneous region. These parameterizations vary greatly depending on Reynolds number. For the coastal flows in which we are interested the Reynolds number at different locations in the domain may vary from order 1 to order 1000, so we must consider laminar and fully turbulent flows. Large eddy simulation (LES) is used to model the effects of turbulence. The geometry of a periodic cell of vegetative obstacles is completely resolved in the fluid mesh with a standard no-slip boundary condition imposed on the fluid-vegetation boundaries. The corresponding drag coefficient is calculated and upscaling laws from the study of inertial flow through porous media are used to parametrize the drag coefficient over a large range of Reynolds numbers. Simulations are performed using a locally conservative, stabilized continuous Galerkin finite element method on highly-resolved, unstructured 2D and 3D meshes. The second method we present is an immersed structure approach. In this method, separate meshes are used for the fluid domain and vegetative obstacles. Taking techniques from immersed boundary finite element methods, the effects of the fluid on the vegetative structures and vice versa are calculated using integral transforms. This method allows us to model flow over much larger scales and containing much more complicated obstacle geometry. Using a simple elastic structure model we can incorporate bending and moving obstacles which would be extremely computationally expensive for the first method. We model flexible vegetation as thin, elastic, inextensible cantilever beams. We present two numerical methods for modeling the beam motion and analyze their computational expense, stability, and accuracy. Using the immersed structure approach, a fully coupled steady-state fluid-vegetation interaction model is developed as well as a dynamic interaction model assuming dynamic fluid flow and quasi-static beam bending. This method is verified using channel flow and wave tank test problems. We calculate the bulk drag coefficient in these flow scenarios and analyze their trends with changing model parameters including stem population density and flow Reynolds number. These results are compared to well-respected experimental results. We model real-life beds of Spartina alterniflora grass with representative beds of flexible beams and perform similar comparisons. / text

Modern day networks, both physical and virtual, are designed to support increasingly sophisticated applications based on complex manipulation of information flows. On the flip side, the ever-growing scale of the underlying networks necessitate the use of low-complexity algorithms. Exploring this tension needs an understanding of the relation between these flows and the network structure. In this thesis, we undertake a study of three such processes: aggregation, dissemination and filtering. In each case, we characterize how the network topology imposes limits on these processes, and how one can use knowledge of the topology to design simple yet efficient control algorithms. Aggregation: We study data-aggregation in sensor networks via in-network computation, i.e., via combining packets at intermediate nodes. In particular, we are interested in maximizing the refresh-rate of repeated/streaming aggregation. For a particular class of functions, we characterize the maximum achievable refresh-rate in terms of the underlying graph structure; furthermore we develop optimal algorithms for general networks, and also a simple distributed algorithm for acyclic wired networks. Dissemination: We consider dissemination processes on networks via intrinsic peer-to-peer transmissions aided by external agents: sources with bounded spreading power, but unconstrained by the network. Such a model captures many static (e.g. long-range links) and dynamic/controlled (e.g. mobile nodes, broadcasting) models for long-range dissemination. We explore the effect of external sources for two dissemination models: spreading processes, wherein nodes once infected remain so forever, and epidemic process, in which nodes can recover from the infection. The main takeaways from our results demonstrate: (i) the role of graph structure, and (ii) the power of random strategies. In spreading processes, we show that external agents dramatically reduce the spreading time in networks that are spatially constrained; furthermore random policies are order-wise optimal. In epidemic processes, we show that for causing long-lasting epidemics, external sources must scale with the number of nodes -- however the strategies can be random. Filtering: A common phenomena in modern recommendation systems is the use of user-feedback to infer the 'value' of an item to other users, resulting in an exploration vs. exploitation trade-off. We study this in a simple natural model, where an 'access-graph' constrains which user is allowed to see which item, and the number of items and the number of item-views are of the same order. We want algorithms that recommend relevant content in an online manner (i.e., instantaneously on user arrival). To this end, we consider both finite-population (i.e., with a fixed set of users and items) and infinite-horizon settings (i.e., with user/item arrivals and departures) -- in each case, we design algorithms with guarantees on the competitive ratio for any arbitrary user. Conversely, we also present upper bounds on the competitive ratio, which show that in many settings our algorithms are orderwise optimal. / text

This dissertation focuses on inverse problems for partial differential equations with multiscale coefficients in which the goal is to determine the coefficients in the equation using solution data. Such problems pose a huge computational challenge, in particular when the coefficients are of multiscale form. When faced with balancing computational cost with accuracy, most approaches only deal with models of large scale behavior and, for example, account for microscopic processes by using effective or empirical equations of state on the continuum scale to simplify computations. Obtaining these models often results in the loss of the desired fine scale details. In this thesis we introduce ways to overcome this issue using a multiscale approach. The first part of the thesis establishes the close relation between computational grids in multiscale modeling and sampling strategies developed in information theory. The theory developed is based on the mathematical analysis of multiscale functions of the type that are studied in averaging and homogenization theory and in multiscale modeling. Typical examples are two-scale functions f (x, x/[epsilon]), (0 < [epsilon] ≪ 1) that are periodic in the second variable. We prove that under certain band limiting conditions these multiscale functions can be uniquely and stably recovered from nonuniform samples of optimal rate. In the second part, we present a new multiscale approach for inverse homogenization problems. We prove that in certain cases where the specific form of the multiscale coefficients is known a priori, imposing an additional constraint of a microscale parametrization results in a well-posed inverse problem. The mathematical analysis is based on homogenization theory for partial differential equations and classical theory of inverse problems. The numerical analysis involves the design of multiscale methods, such as the heterogeneous multiscale method (HMM). The use of HMM solvers for the forward model has unveiled theoretical and numerical results for microscale parameter recovery, including applications to inverse problems arising in exploration seismology and medical imaging. / text