Structured technique is the traditional and the popular systems analysis and design language. With the rapid progress and development of information technology, embedded systems have penetrated into most of the equipments which we used daily. Over the past few years a considerable effort has been made in modeling the platform independent model (PIM) for business information systems. However, the detailed guideline for modeling the PIM of embedded systems is lacking. This study proposed a PIM modeling methodology with structured technique for embedded systems. The structured modeling process is consisted of three parts: requirement modeling, process modeling and module modeling. For each part, its modeling tool, modeling processes and rules are provided. The research methodology is articulated using the design science research methodology. A usability evaluation is performed to demonstrate its applicability with a real-world embedded system case. The evaluation results indicated that with this proposed method, the system developer can easily and effectively analyze and design the embedded systems with structured technique.

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.

Traffic congestion is a serious problem in the United States and is likely to get worse. A number of strategies encompassing increasing supply and managing demand have been suggested to mitigate the problem of traffic congestion. These strategies seek to reduce travel time and/or make travel time more reliable. The use of managed lanes is one such strategy. Faced with successful implementation of a managed lane strategy, it is important to understand potential public perception of the managed lane as well as estimate the number of travelers willing to use managed lanes. Such an estimate would help estimate the toll rates for optimal usage of managed lanes by carpoolers and toll paying travelers. An online survey augmented by paper and laptop survey was conducted in Houston and Dallas to collect information about travelers’ travel behavior, socio-economic characteristics, managed lane perception, and potential use of managed lanes. A comparison of interest in using managed lanes revealed that in majority of cases there was no difference in interest in using managed lanes across user groups. Travel time reliability and ability to travel faster were indicated as top two reasons for interest in managed lanes. This was true for all travelers regardless of mode. Mode choice model using multinomial logit modeling were estimated for Houston and Dallas. Simulation studies were conducted using these mode choice models to estimate the percentage of Single Occupant Vehicle (SOV) travelers on managed lane (ML), High Occupancy Vehicle with two travelers (HOV2) on ML, High Occupancy Vehicle with three or more travelers (HOV3+) on ML, SOV travelers on general purpose lane (GPL), HOV2 travelers on GPL, and HOV3+ travelers on GPL. These scenarios compared the managed lane usage for different speeds on GPL (25 miles per hour, 30 miles per hour, and 35 miles per hour). For the case when general purpose lane speed is 25 miles per hour, an increase of $11.75 in SOV tolls ($18 from $6.25) decreases the modal share of SOV travelers on Houston ML from 23.3 percent to 16.9 percent. A similar increase in Dallas tolls decreases the modal share of SOV ML travelers from 22.0 percent to 16.3 percent.

Tularemia is a one of the most complex zoonotic diseases. Francisella tularensis McCoy and Chapin, the causative agent of tularemia is considered endemic in Texas, but outbreaks are rare and there are few human cases each year. Tularemia is listed as a Category A biological weapon and air samples are taken daily in select major metropolitan areas, including Houston, to monitor for its presence. I determined the potential risk for tularemia introduction and spread in southeast Texas through field surveillance for the pathogen and its major arthropod vector in the region, Amblyomma americanum (L.); completion of a habitat capability map for A. americanum, based on landscape analysis of the study area; and potential movement and long-term establishment of tularemia through development of a spatially explicit, agent-based, simulation model. Field and laboratory investigations resulted in the identification of two samples positive for F. tularensis. A feral cat tested positive for Type B tularemia using a new aptamer-based assay, and one sample returned positive in Amblyomma maculatum by polymerase chain reaction. This work sheds light on a complex host-pathogen-vector interaction in the rural to urban interface and establishes a framework for future tularemia field work and pathogen modeling in the rural to urban interface.

Modeling of changing pressure, temperature, and density profiles in a wellbore as a function of time is crucial for design and analysis of pressure-transient tests (particularly when data are gathered above perforations), real-time management of annular-pressure buildup (ABP) and identifying potential flow-assurance issues. Other applications of this modeling approach include improving design of production tubulars and artificial-lift systems and gathering pressure data for continuous reservoir management. This work presents a transient wellbore model coupled with a semianalytic temperature model for computing wellbore-fluid-temperature profile in flowing and shut-in wells. The accuracy of the analytic heat-transfer calculations improved with a variable-formation temperature model and a newly developed numerical-differentiation scheme. Surrounding formation temperature is updated in every timestep up to a user specified distance to account for changes in heat-transfer rate between the hotter wellbore fluid and the cooler formation. Matrix operations are not required for energy calculations because of the semianalytic formulation. This efficient coupling with the semianalytic heat-transfer model increased the computational speed significantly. Either an analytic or a numeric reservoir model can be coupled with the transient wellbore model for rapid computations of pressure, temperature, and velocity. The wellbore simulator is used for modeling a multirate test from a deep offshore well. Thermal distortion and its effects on pressure data is studied using the calibrated model, resulting in development of correlations for optimum gauge location in both oil and gas wells. Finally, predictive capabilities of the wellbore model are tested on multiple onshore wells experiencing annular-pressure buildup problems. Modeling results compare quite well with the field data and also with the state-of-the-art commercial wellbore simulator.

Foot and mouth disease (FMD) is a highly contagious viral infection that affects all Artiodactyls (cloven-hoofed) species. The United States has been free of FMD since 1929, and the entire population of cloven-hoofed species is therefore susceptible to FMD virus infection. In the face of an outbreak, it is crucial that appropriate control measures be applied rapidly to control the disease. However, in most cases decisions on mitigation strategies must be made with little current or empirical data and in the context of political, economic and social pressures. Disease spread models can be used to evaluate the design of optimal control strategies, for policy formulation, for gap analysis and to develop and refine research agendas when disease is not present. This research project is designed to investigate the potential role of wildlife (deer) in the transmission and spread of FMD in an extensive livestock management system in southern Texas. The spread of FMD was simulated in white tailed deer populations using a Geographic Automata model. Past research has focused primarily on modeling the spread of FMD in livestock populations. There has been limited research into the potential role of wildlife in the spread and maintenance of FMD, specifically in the United States and using a spatial modeling approach. The study area is a nine-county area located in southern Texas, bordering Mexico. It is a region of concern for the introduction of foreign animal diseases, particularly through the movement of wild and feral animal species. It is both a strategic location and is generally representative of the many similar eco-climatic regions throughout the world. It is an ideal model landscape to simulate FMD incursions. In this research project, the potential spread of FMD is simulated based on various spatial estimates of white tailed deer distribution, various estimates of critical model parameters (such as the latent and infectious periods), seasonal population variability and in the face of potential pre-emptive mitigation strategies. Significant differences in the predicted spread were found for each group of simulations. The decision-support system developed in the studies described in this dissertation provide decision-makers and those designing and implementing disease response and control policy with information on the potential spread of a foreign animal disease incursion with a likely wildlife reservoir. Use of such a decision-support system would enhance the disease incursion preparedness and response capacity of the United States.

A rigorous kinetic model of hydrodesulfurization (HDS) of complex mixtures such as light cycle oil (LCO) or diesel has been developed. An experimental setup was constructed to investigate the hydrotreatment of complex mixtures. The hydrodesulfurization of LCO on a commercial CoMo/Al2O3 (IMP) catalyst was investigated in a Robinson Mahoney perfectly mixed flow stationary basket reactor. An experimental investigation of the HDS of the dibenzothiophene (DBT) and substituted dibenzothiophenes in the LCO was carried out at temperatures between 290 and 330°C, space time for dibenzothiophene (W/F0 DBT) between 1000 and 6500 kgcat-h/kmol, and H2/HC molar ratio constant of 2.8. To avoid having to deal with a huge number of parameters in the model, a methodology based on structural contributions was applied. DENs and DENt are the denominators of the Hougen-Watson rate expressions for hydrodesulfurization of dibenzothiophene (DBT) and methyl-substituted dibenzothiophenes contained in the LCO. Both denominators comprise the concentration of all adsorbing species of the LCO multiplied by their adsorption equilibrium constants. The estimation of the denominators DENs and DENt was performed using the Levenberg-Marquardt algorithm and the results in terms of conversion for DBT, biphenyl and cyclohexylbenzene obtained in the hydrodesulfurization of the LCO. The evolution of DENs and DENt values with the composition was calculated for each LCO experiment. Structural contributions were taken from Vanrysselberghe and Froment for hydrogenolysis and hydrogenation of methyl-substituted dibenzothiophenes with a significant reduction in the number of parameters to be estimated in the HDS of the LCO. The multiplication factors, fsDBT, which are products of structural contributions for hydrogenolysis and hydrogenation of the mono- and dimethyl-dibenzothiophenes were also taken from Vanrysselberghe and Froment. These multiplication factors are based on experimental results with model components such as DBT, 4-Methyl dibenzothiophene and 4,6-Dimethyl dibenzothiophene. The results obtained in the modeling are in good agreement with the experimental data because the model reproduces very well the observed total conversions of DBT, conversions of DBT into biphenyl and conversions of DBT into cyclohexylbenzene as a function of temperature.

Near-road air quality studies have indicated the presence of high levels of pollutants. In this study, a three dimensional Eulerian model is developed which can be used to study the air quality near freeways. A vehicle-induced turbulence parameterization is included in the model to estimate better the turbulent diffusion of pollutants. The near-road air quality model is used to study two different cases. In the first case, the model is validated using the data from General Motor's SF6 dispersion experiment, conducted at Michigan in 1976. Sensitivity of the model to meteorology and traffic-related parameters are studied in detail. In the second case, the spatial distribution of ozone, carbon monoxide, NOx and 1,3-Butadiene near a simulated 8-lane freeway was studied. Model simulation for the first case yielded better results than US EPA's CALINE models which were previously used for regulatory purposes. Model performance when analyzed at different wind directions shows an overall good performance. The results also show that the model performs well at surface but slightly over predicts pollutant concentration at higher elevations. The simulation results for second case at different directions of wind and at different boundary conditions for model species, places emphasis on the importance of the inclusion of the chemical mechanism in the study of near-road air quality.

Today, software development approach has been shifted from structure-oriented to object-oriented. UML has become a standard modeling language in object-oriented systems analysis and design. Over the past few years a considerable effort has been made in the model driven architecture transformation area. However, little attention has been paid to the issue of transformation from sequence diagram to class diagram for modeling platform independent model (PIM). This study, therefore, presents a systematic methodology, extended from Selonen et al (2003), for sequence diagram to class diagram transformation. A case is used to illustrate the concept, application, and advantage of using the proposed methodology. With this methodology, the system developer can construct PIM efficiently and thereby enhance the efficiency and quality of system development.

In a more competitive environment, load forecast serves two different applications. First, load forecast results can be used by the retailers of power to study their opportunities and plan their business strategies. Second, accurate projections of load are useful for T&D operators in performing system operation and expansion studies. Several key elements in their market and system planning studies have strong location factors that the spatial load forecast can address. In this dissertation, a package that integrates a Geographic Information System (GIS) used for automatic mapping and facility management (AM/FM) and a spatial load forecast module is presented. The interface functions and the procedure of the fuzzy logic based spatial load forecast module are described. Simulation studies are performed on a metropolitan area of Kaohsiung, Taiwan. The conventional fuzzy modeling has a drawback in that the fuzzy rules or the fuzzy membership functions are determined by trial and error. In this dissertation an automatic model identification procedure is proposed to construct the fuzzy model for short-term load forecast. In this method an analysis of variance is used to identify the influential variables on the system load. To setup the fuzzy rules, a cluster estimation method is adopted to determine the number of rules and the membership functions of variables involved in the premises of the rules. A recursive least square method is then used to determine the coefficients in the conclusion parts of the rules. None of these steps involves nonlinear optimization and all steps have well-bounded computation time.