Modeling of the electromagnetic, structural, thermal, or acoustic response of the human body to various external and internal stimuli is limited by the availability of anatomically accurate and numerically efficient computational models. The models currently approved for use are generally of proprietary or fixed format, preventing new model construction or customization. 1. This dissertation develops a new Visible Human Project - Female (VHP-F) computational phantom, constructed via segmentation of anatomical cryosection images taken in the axial plane of the human body. Its unique property is superior resolution on human head. In its current form, the VHP-F model contains 33 separate objects describing a variety of human tissues within the head and torso. Each obejct is a non-intersecting 2-manifold model composed of contiguous surface triangular elements making the VHP-F model compatible with major commercial and academic numerical simulators employing the Finite Element Method (FEM), Boundary Element Method (BEM), Finite Volume Method (FVM), and Finite-Difference Time-Domain (FDTD) Method. 2. This dissertation develops a new workflow used to construct the VHP-F model that may be utilized to build accessible custom models from any medical image data source. The workflow is customizable and flexible, enabling the creation of standard and parametrically varying models facilitating research on impacts associated with fluctuation of body characteristics (for example, skin thickness) and dynamic processes such as fluid pulsation. 3. This dissertation identifies, enables, and quantifies three new specific computational bioelectromagnetic problems, each of which is solved with the help of the developed VHP-F model: I. Transcranial Direct Current Stimulation (tDCS) of human brain motor cortex with extracephalic versus cephalic electrodes; II. RF channel characterization within cerebral cortex with novel small on-body directional antennas; III. Body Area Network (BAN) characterization and RF localization within the human body using the FDTD method and small antenna models with coincident phase centers. Each of those problems has been (or will be) the subject of a separate dedicated MS thesis.

This thesis presents the development of a hydrologic model in the vector environment. Establishing spatial relationship between flow elements is the key for flow routing techniques. Such a relationship is called hydrologic topology, making each flow element know which other elements are upstream and which are downstream. Based on the hydrologic topology established for the flow elements, tools were developed for flow network navigation, drainage area estimation, flow length calculation and drainage divide determination. To apply the tools, data required might be obtained from different sources, which may lead to certain problems that have to do with wrong flow direction of stream lines and, mismatches in location of stream lines with respect to the corresponding drainage area polygons. Procedures to detect such inconsistencies and to correct them have been developed and are presented here. Data inconsistencies correction and parameter computation methods form the basis for the development of a routing model, which would be referred as hydrologic model. The hydrologic model consists of an overland flow routing module, two options for channel routing and a reservoir routing module. Two case studies have been presented to show the application of the tools developed.

A complete methodology has been proposed to model and evaluate IC packages in the high-speed digital and radio-frequency applications. The package types that are studied in this dissertation include BGAs, TSSOPs and BCCs. In characterization of BGAs, both frequency-domain and time-domain techniques have been applied and compared to each other. It was found that the best strategy was to find a rough coupled transmission-line model in the time domain and refine it through the optimization scheme in the frequency domain. Equivalent lumped model has been further derived from the coupled transmission-line model using the concept of distributed parameters. For RFIC applications, the electrical model of BCC, one type of lead-frame CSP, has been established based on the frequency-domain technique. To evaluate the package performance, an on-chip 50-ohm microstrip line housed in the package has been investigated. The insertion and return losses were analyzed and measured. Excellent agreement has been observed up to Ku band. The package acts as a low-pass filter to cause a cut off for the line above a certain frequency, which was predicted successfully from the established package model. The simulation results also show that BCC exhibits higher cut-off frequency and lower insertion loss in the passband when compared to TSSOP, one of the currently most popular RFIC packages.

The Unified Modeling Language (UML) is now a standard means of expressing object-oriented analysis and design (OOAD) for the Object Management Group since 1997. The UML is called a modeling language, not a method. That is, the modeling language is the graphic notation that methods use to express design. However, the principles or guidelines for each UML notation modeling are lacking and those are crucial for the UML modeling. To address this important issue, this study utilizes research and development method to investigate the guidelines for each UML notation modeling. An example of war game is used to illustrate the guideline and application. With these guidelines, analysts can more easily use the UML notations to express OOAD and thereby improve the efficiency and effectiveness of UML modeling.

This research focused on expanding the capabilities of the Water Rights Analysis Package (WRAP) for incorporating salinity considerations in assessments of water availability. A simulation modeling approach was used to address this issue and a generalized simulation model called WRAP-SALT was developed. The Brazos River Basin served as a case study to test the simulation approach adopted by the model. The simulation model adopts a generalized modeling approach applicable to any river basin system. The model tracks salinity throughout a river basin system over different periods of time for alternative scenarios of water use, reservoir system operating policies, and salt control mechanisms. The model was applied to the Brazos River Basin considering different management scenarios and the results obtained were analyzed. Reservoir reliabilities were assessed under user imposed salinity constraints. It was observed that the water supply reliabilities decreased significantly if salinity constraints were considered. Salt control dams proposed by the U.S. Army Corps of Engineers were also incorporated in the simulation of the river basin. It was observed that salinity in the main stem of the Brazos River was significantly reduced. However, no significant improvement was observed in water supply reliabilities.

Mediational analysis quantifies proposed causal mechanisms through which treatments act on outcomes. In the presence of clustered data, conventional multiple regression mediational methods break down, requiring the use of hierarchical linear modeling techniques. As an additional consideration, nonlinear relationships in multilevel mediation models require unique specifications that are ignored if modeled linearly. Improper specification of nonlinear relationships can lead to a consistently overestimated mediated effect. This has direct implications for inferences regarding intervention causality and efficacy. The current investigation examined a specific nonlinear multilevel mediation model parameterization to account for nonlinear relationships in clustered data. A simulation study was conducted to compare linear and nonlinear model specifications in the presence of truly nonlinear data. MacKinnon et al.’s (2007a) empirical-M based PRODCLIN method for estimating the confidence interval surrounding the instantaneous indirect effect was used to compare confidence interval coverage rates surrounding both the linear and nonlinear models’ estimates. Overall, the nonlinear model’s estimates were less biased, more efficient, and produced higher coverage rates than the linear model specification. For conditions containing a true value of zero for the instantaneous indirect effect, bias, efficiency, and coverage rate values were similar for the linear and nonlinear estimators. For conditions with a non-zero value for the instantaneous indirect effect, both the linear and nonlinear models were substantially biased. However, the nonlinear model was always less biased and always produced higher coverage rates than the linear model. The nonlinear model was more efficient than the linear model for all but two design conditions. / text

A recently mandated change in the use of pharmaceutical propellants spurred the development and reevaluation of aerosolized pharmaceuticals. Chlorofluorocarbon (CFC) propellants were commonly used in pressurized metered dose inhalers (MDIs), but were unfortunately linked to the depletion of the ozone layer. As such, a search for new propellants was initiated and ultimately resulted in the implementation of hydrofluoroalkane (HFA) propellants in MDIs. These HFA propellants however demonstrated significantly different properties than CFCs and necessitated a considerable amount of reformulation efforts. Not only did HFAs demonstrate different physiochemical properties, but in some cases these differences necessitated reengineering of the delivery device. Unfortunately HFA propellants are considered greenhouse gasses, albeit to a lesser degree than CFCs, so the development of alternate delivery methods has been ongoing. One delivery method that has received significant attention and resources is dry powder inhalers (DPIs). DPIs are a propellant-free alternative to aerosolized drug delivery, and demonstrate some advantages and disadvantages compared to the use of MDIs and nebulizers.In addition to the modernization of pharmaceutical agents, excipients, and delivery devices, technological advances have allowed for different and/or improved characterization of pharmaceutical aerosols. Particle size characteristics of aerosols are the primary physical measure examined and are relevant to ensure proper and reproducible drug delivery to the lung. Likewise, chemical analysis of the pharmaceutical agent is extremely important for pharmaceutical development and monitoring, including solubility determination, stability monitoring, and ultimately, dose emitted. Because many limitations exist in characterization however, and because experimental means can be costly with regard to labor and materials, prediction of aerosol performance characteristics based on formulation and device variables are valuable.Previous work predicting the performance of solution based MDIs has opened the door for improved prediction of suspension based MDI systems. Suspension aerosol prediction has been examined in the past, but additional information is now available to more appropriately model suspension MDI systems that include polydisperse drug material and emit polydisperse droplets.

The Hohokam Water Management Simulation (HWM) is a computer simulation for exploring the operation of the Hohokam irrigation systems in southern Arizona. The simulation takes a middle road between two common kinds of archaeological simulation: large-scale, detailed landscape and environmental reconstructions and highly abstract hypothesis-testing simulations. Given the apparent absence in the Hohokam context of a central authority, the specific aim of the HWM is approaching the Hohokam as a complex system, using principles such as resilience, robustness, and self-organization. The Hohokam case is reviewed, and general questions concerning how the irrigation systems operated are shown to subsume multiple crosscutting and unresolved issues. Existing proposals about the relevant aspects of Hohokam society and of its larger long-term trajectory are based on widely varying short- and long-term processes that invoke different elements, draw different boundaries, and operate at different spatial and temporal scales, and many rely on information that is only incompletely available. A framework for pproaching problems of this kind is put forward. A definition of modeling is offered that specifies its epistemological foundations, permissible patterns of inference, and its role in our larger scientific process. Invoking Logical Positivism, a syntactic rather than semantic view of modeling is proposed: modeling is the construction of sets of assertions about the world and deductions that can be drawn from them. This permits a general model structure to be offered that admits hypothetical or provisional assertions and the flexible interchange of model components of varying scope and resolution. Novel goals for archaeological inquiry fall from this flexible approach; these move from specific reconstruction to a search for more universal and general dynamics. A software toolkit that embodies these principles is introduced: the Assertion-Based Computer Modeling toolkit (ABCM), which integrates simulation with the logical architecture of a relational database, and further provides an easy means for linking models of natural and social processes (including agent-based modeling). The application of this to the Hohokam context is described, and an extended example is presented that demonstrates the flexibility, utility and challenges of the approach. An attached file provides sample output.

This thesis presents the development of a hydrologic model in the vector environment. Establishing spatial relationship between flow elements is the key for flow routing techniques. Such a relationship is called hydrologic topology, making each flow element know which other elements are upstream and which are downstream. Based on the hydrologic topology established for the flow elements, tools were developed for flow network navigation, drainage area estimation, flow length calculation and drainage divide determination. To apply the tools, data required might be obtained from different sources, which may lead to certain problems that have to do with wrong flow direction of stream lines and, mismatches in location of stream lines with respect to the corresponding drainage area polygons. Procedures to detect such inconsistencies and to correct them have been developed and are presented here. Data inconsistencies correction and parameter computation methods form the basis for the development of a routing model, which would be referred as hydrologic model. The hydrologic model consists of an overland flow routing module, two options for channel routing and a reservoir routing module. Two case studies have been presented to show the application of the tools developed.

Reservoir simulation is an important tool for decision making and field development management. It enables reservoir engineers to predict reservoir production performance, update an existing model to reproduce monitoring data, assess alternative field development scenarios and design robust production optimization strategies by taking into account the existing uncertainties. A big obstacle in automating model calibration and production optimization approaches is the massive computation required to predict the response of real reservoirs under proposed changes in the model inputs. To speed up reservoir response predictions without compromising accuracy, fast surrogate models have been proposed. These models are either derived by preserving the physics of the involved processes (e.g. mass balance equations) to provide reliable long-range predictions or are developed based solely on statistical relations, in which case they can only provide short-range predictions due to the absence of the physical processes that govern the long-term behavior of the reservoir. We present an alternative solution that combines the advantages of both statistics-based and physics-based methods by deriving the flow predictions in complex two-dimensional models from one-dimensional flow network models. The existing injection/production wells in the original model form the nodes or vertices of the flow network. Each pair of wells (nodes) in the flow network is connected using a one-dimensional numerical simulation model; hence, the entire reservoir is reduced to a connected network of one-dimensional simulation models where the coupling between the individual one-dimensional models is enforced at the nodes where network edges intersect. The proposed flow network model provides a useful and fast tool for characterizing inter-well connectivity, estimating drainage volume between each pair of wells, and predicting reservoir production over an extended period of time for optimization purposes. We estimate the parameters of the flow network model using a robust training approach to ensure that the flow network model reproduces the response of the original full model under a wide range of development strategies. This step helps preserve the flow network model's predictive power during the production optimization when development strategies can change at different iterations. The robust networks training and the subsequent production optimization iterations are computationally efficient as they are performed with the faster flow network model. We demonstrate the effectiveness and applicability of our proposed flow network modeling approach to rapid production optimization using two-phase waterflooding simulations in synthetic and benchmark models.