Master of Science, Miami University, 2011, Computational Science and Engineering

Rate-sensitivity, creep and relaxation behavior of medical grade polymers has been investigated experimentally along with an assessment of different constitutive models. Two types of modified common biomedical material A and B were tested. All materials exhibited rate-sensitivity and rate-reversal behavior during creep and relaxation testing with prior loading and unloading histories for tensile and compressive tests. Numerical modeling was performed through a modified version of the Viscoplasticity Based on Overstress (VBO) model. Simulation and prediction results with good quantitative and qualitative agreement were produced for all materials in tension and compression loading. Parameter fitting using the Hybrid and Three Network Models in PolyUMod software generated material constants for ABAQUS, and the finite element results for a knee joint were verified against experimental data. The parameter fitting was unable to produce acceptable results for MATERIAL C. Implementation of VBO into the PolyUMod library is recommended to enhance modeling capability.

Committee: Fazeel Khan (Advisor); James Moller (Committee Member); Gregory Reese (Committee Member) Subjects: Biomedical Engineering; Materials Science; Mechanical Engineering

Master of Science, University of Akron, 2007, Applied Mathematics

A second order, viscous continuum traffic flow model developed by H.M. Zhang is studied and implemented numerically using a fourth order Runge Kutta adaptive time step algorithm. This model is applied to a two section one lane highway with an entrance ramp and an exit ramp, and to a four section highway network comprised of two one lane roads. This is the first numerical implementation of Zhang's model using boundary conditions to model the traffic interchange.

Committee: Kevin Kreider (Advisor) Subjects: Transportation

MS, University of Cincinnati, 2024, Engineering and Applied Science: Mechanical Engineering

Within this thesis document we focus on the application of Nonlinear Model Predictive Control (NMPC) onto an epidemic compartmental model. The compartmental model is a partial differential equation (PDE) based Susceptible Latent Infected Recovered (SLIR) epidemic model. This model serves as the basis of the NMPC. In order to generate the necessary parameters for initializing and training the use of constrained optimization, a single-objective Genetic Algorithm (GA), and LSTM (Long-Short-Term-Memory) deep learning were explored. The spatial domains considered for the SLIR epidemic model includes Hamilton County, Ohio as well as the entire state of Ohio, USA. With respect to Hamilton County, Ohio three different time periods were evaluated in which varied levels of infection relating to COVID-19 were observed. At the state wide level only one time period was consider. The NMPC considers two control schemes. The first being control applied uniformly across the spatial domain of interest. While the second focuses on applying the control in a spatially targeted manner to specific geographical areas based on observed higher levels of infection. The NMPC also employs a cost function comprising the infection spread density and the associated cost of applied control measures. The latter of which in turn representing socioeconomic effects. Overall, the NMPC framework developed here is intended to aid in the evaluation of optimal Non-Pharmaceutical Interventions (NPI) towards spread mitigation of infectious diseases.

Committee: Manish Kumar Ph.D. (Committee Chair); Shelley Ehrlich M.D. (Committee Member); Subramanian Ramakrishnan Ph.D. (Committee Member); David Thompson Ph.D. (Committee Member) Subjects: Mechanical Engineering

Doctor of Philosophy, The Ohio State University, 2023, Earth Sciences

One of the most important features of our planet is its ability to sustain life in multi million year timescales. This ability largely depends on Earth's internal system in regulating the global carbon cycle. One of the key processes that regulates the global carbon cycle is weathering of silicate rocks. As such, a refined understanding of the silicate weathering system and its role in regulating the global carbon cycle in multi million year timescales is essential in predicting the fate of our planet amid the current and future increase in anthropogenic atmospheric CO2 concentrations. However, characterizing and identifying the direct or indirect evidence of changes in the global carbon cycle in the rock record is not trivial. First, the signals preserved in the rock record are prone to secondary alteration. Second, the traditional geochemical proxies can produce non-unique interpretations. My research is, therefore, aimed at addressing these issues by investigating and constraining the extent of diagenetic processes and elucidating possible links between tectonics and changes in silicate weathering during the Ordovician Period using novel geochemical techniques and numerical modeling. This research is broken down into three separate projects and presented in Chapter 2 through Chapter 4 of this dissertation. The study presented in Chapter 2 uses bulk carbonate measurements of calcium isotopes (δ44/40Ca) and trace element concentrations to constrain the extent of diagenetic processes affecting the δ13C record from the Middle Ordovician. The data and numerical models presented in this study suggest that variations in Sr/Ca and δ44/40Ca from Meiklejohn Peak correspond to changes in the dominant carbonate primary mineralogy and early marine diagenesis. However, the δ13C seem to reflect a primary change in the dissolved inorganic carbon (DIC). The positive shift recorded as the MDICE (Middle Darriwilian Carbon Isotope Excursion) likely represents a transient increas (open full item for complete abstract)

Committee: Matthew Saltzman (Advisor); John Olesik (Committee Member); Derek Sawyer (Committee Member); Elizabeth Griffith (Committee Member) Subjects: Earth; Geology

Doctor of Philosophy, The Ohio State University, 2022, Welding Engineering

The automotive industry wants to advance integrated computational materials engineering (ICME) approaches that combine models of joining processes and microstructural evolution for prediction of material property gradients and ultimately the mechanical performance of multi-sheet lap joints. Despite the increasing demand for computational optimization within vehicle structures and the increased use of low-density materials, modern integrated modeling frameworks of automotive lap joining are often limited to the resistance spot welding (RSW) of conventional steels. Moreover, important phenomena in steel weldments, like decomposition of austenite on-cooling, tempering of martensite, and microstructure-dependent flow stress and damage properties are too material-specific for universal application. In this research, generalized metallurgical and mechanical modeling strategies are investigated for increased applicability to a wider range of steels and joining processes. The study evaluates: the reliability of heat transfer predictions within state-of-the-art numerical models of RSW, the accuracy of existing austenite decomposition models, the readiness of steel time-temperature-transformation (TTT) diagram tools containing CALPHAD-calculated parameters, the generality of a recently developed martensite tempering model, and the determination of RSW fusion and heat-affected zone flow stress and fracture behavior. Results show that state-of-the art finite element models of RSW that are validated using experimental weld nugget dimensions have a propensity to underpredict cooling rates. A JMAK and additivity rule approach calibrated with experimental TTT diagram data exhibited the greatest accuracy when predicting AHSS austenite decomposition; however, calibrations using calculated TTT diagrams better facilitated material optimization. Generalized parameters within a JMAK-type model of martensite tempering successfully predicted HAZ softening within martensitic and dual-phase (open full item for complete abstract)

Committee: Antonio Ramirez (Advisor); Avraham Benatar (Committee Member); Boian Alexandrov (Committee Member) Subjects: Materials Science

Doctor of Philosophy (PhD), Wright State University, 2020, Engineering PhD

Lattice cell structures (LCS) are the engineered porous structures that are composed of periodic unit cells in three dimensions. Such structures have many scientific and engineering applications, such as in vessel gas technology, thermal systems, mechanical and aerospace structures, etc. for which lightweight, high strength, and energy absorption capabilities are essential properties. To have an optimized design, finite element analysis (FEA) based computational approach can be used for detailed analysis of such structures, sometime in full scale. However, developing a large-scale model for a lattice-based structure is computationally expensive. If an equivalent solid FE model can be developed using the equivalent solid mechanical properties of a lattice structure, the computational time will be greatly reduced. The main objective of this research is to develop a material model which is equivalent to the mechanical response of a lattice structure. In this study, the mechanical behavior of body centered cubic (BCC) configuration and its derivative such as a BCC placed inside boxed frame (here, termed as `InsideBCC') under compression and within elastic limit is considered. The BCC and InsideBCC configurations are chosen because they provide the bounds of the mechanical properties of LCS involving BCC derivatives. First, the finite element analysis approach and theoretical calculations are used on a single unit cell of BCC and InsideBCC for several cases (different strut diameters and cell sizes) to predict equivalent solid properties. The equivalent quasi-isotropic properties required to describe the material behavior of both BCC and InsideBCC unit cells are equivalent Young's modulus (E_e), equivalent shear modulus (G_e), and equivalent Poisson's ratio (ν_e). The results are then used to develop two separate neural networks (NN) models so that the equivalent solid properties of a BCC or InsideBCC lattice of any geometrical parameters can be predicted. The input dat (open full item for complete abstract)

Committee: Ahsan Mian Ph.D. (Advisor); Raghavan Srinivasan Ph.D. (Committee Member); Henry Young Ph.D. (Committee Member); Joy Gockel Ph.D. (Committee Member); Uttam Chakravarty Ph.D. (Committee Member) Subjects: Mechanical Engineering

Master of Science, University of Toledo, 2020, Civil Engineering

Debris flows are a potentially catastrophic geological hazard worldwide destroying lives, properties, and infrastructure. It is characterized as one of the most destructive among different types of landslide phenomena. They are gravity-driven mass flows involving multiple interacting phases in contact with the environment and with each other during its propagation. The wide range of material sizes ranging from clay to huge boulders with varying compositions poses significant modeling challenges. Lack of monitoring stations, event data, and effective physical models renders it necessary to employ numerical simulations to study the process of the debris flows and predict possibilities for potential hazards. The present study explores a recently developed multi-phase model, implemented in a novel computation tool r.avaflow for simulation of complex multi-phase flows. The present study aims to understand the difference in flow characteristics of different types of mass flows, which vary in material type and composition. First, a numerical simulation of debris flow, mudflows, earth flow, and complex flows, on an idealized slope is conducted to analyze the differences in their flow behavior in the form of run-out distance, velocity, the height of flow, peak discharge, final deposition, kinetic energy, and flow pressure, etc. The results demonstrate the high destructive potential of different types of flows and can be utilized for the delineation of hazard-prone areas. Subsequently, two case studies of well-documented debris flow events in active debris flow sites are also carried out. The first case study focuses on a debris flow event of August 2009 in Tyrol, Austria, and the second case study investigates a debris flow incident of the Chalk Cliff region in Colorado, USA. These studies allow extensive utilization of the important features of numerical simulations in actual landscapes. The case studies are validated using available event data and show reasonably good (open full item for complete abstract)

Committee: Liangbo Hu (Committee Chair); Eddie Y. Chou (Committee Member); James M. Martin-Hayden (Committee Member) Subjects: Civil Engineering; Geology; Geomorphology; Geotechnology

Doctor of Philosophy (PhD), Ohio University, 2020, Chemical Engineering (Engineering and Technology)

Pesticides volatilize from soil and plant surfaces to the atmosphere after spray applications in agricultural fields which can cause inhalational exposure to bystanders. It is important to quantify such volatilization with reasonable confidence for risk assessment of the inhalation exposure. A mechanistic model was developed here to simulate the underlying transport processes and deploy it as a standalone tool that a regulatory body can use to predict volatilization emissions of various pesticides for determination of inhalation exposure. The overall volatilization model includes a soil sub-model and a plant sub-model. The model accounts for the effect of meteorology, soil conditions, pesticide adsorption and volatilization. The soil model simultaneously resolves the soil profile of temperature, moisture, and pesticide concentrations to compute the time-dependent volatilization. The numerical model for soil treatment was in good agreement with an analytical solution at stagnant boundary conditions. The model performance of 14 pesticides against the analytical solution showed coefficient of determination (R2) values of 0.76 to 0.99 and index of agreement (IOA) values of 0.43 to 0.98. The soil model was also validated with observations at field conditions with variable meteorology. The time-dependent predicted volatilization compared well against measurements of two surface treated pesticides - metolachlor and triallate with R2 value of 0.4 and 0.7, respectively. The model prediction of the fumigant volatilization of 1,3-dichloropropene was in good agreement with the field observations (R2=0.8 and IOA=0.9). The plant model utilizes a simple resistance scheme with mass transfer of the pesticide on the leaf surface through a diffusive canopy boundary and an atmospheric boundary layer above the canopy. The model also accounts the loss of pesticide mass on the leaf surface due to penetration into leaf cuticle and photo-degradation as first-order kinetic rates. Volat (open full item for complete abstract)

Committee: Valerie Young (Advisor); Sumit Sharma (Committee Member); Guy Riefler (Committee Member); Michele Morrone (Committee Member); Jared DeForest (Committee Member) Subjects: Agricultural Chemicals; Agricultural Engineering; Atmospheric Sciences; Environmental Engineering; Environmental Science; Soil Sciences

PhD, University of Cincinnati, 2018, Engineering and Applied Science: Electrical Engineering

A multiscale model of field emission (FE) from a carbon nanotube fiber (CNF) is developed which takes into account Joule heating within the fiber and radiative cooling and the energy exchange mechanism at the tip of the individual carbon nanotubes (CNTs ) in the array located at the fiber apex. The model predicts the fraction of CNTs being destroyed as a function of the applied external electric field and reproduces many experimental features observed in some recently investigated CNFs such as, order of magnitude of the emission current (mA range), low turn on electric field (fraction of V/µm), deviation from pure Fowler-Nordheim behavior at large applied electric field, hysteresis of the FE characteristics, and a spatial variation of the temperature along the CNF axis with a maximum close to its tip of a few hundred degree Celsius. The multiscale model is in qualitative agreement with the FE characteristics of CNFs measured by collaborators at Wright-Patterson Air Force Base (WPAFB). The model is used to predict the FE characteristics of both linear and hexagonal arrays of seven CNFs taking into account the effects of electrostatic shielding between adjacent CNFs. The multiscale model described in this dissertation can provide a tool to develop cold cathodes that can provide a current density of a few times 10^5 A/m^2 and a total current of at least 10 mA for at least several hundred hours of continuous waveform (CW) operation, when operated at temperature less than 1000 degree Celsius.

Committee: Marc Cahay Ph.D. (Committee Chair); Je-Hyeong Bahk Ph.D. (Committee Member); Punit Boolchand Ph.D. (Committee Member); Rashmi Jha Ph.D. (Committee Member); Hans Peter Wagner Ph.D. (Committee Member) Subjects: Electrical Engineering

MS, University of Cincinnati, 2008, Engineering : Mechanical Engineering

The growth dynamics of a single gas bubble from inception to departure, emanating from a submerged capillary tube orifice in quiescent liquid pools has been theoretically modeled. The mathematical model represents a fundamental balance of forces due to buoyancy, viscosity, surface tension, liquid inertia, and gas momentum transport, and the consequent motion of the evolving gas-liquid interface. Theoretical solutions describe the dynamic bubble behavior (incipience, growth, necking and departure) as it grows from the tip of a capillary tube orifice in an isothermal pure liquid pool. Also complete Navier Stokes equations are solved using VOF model to simulate the different stages in the evolution of the bubble. Variations in bubble shapes and sizes, equivalent diameter, and growth times with capillary orifice diameter and air flow rates are outlined. These results are also found to be in excellent agreement with the experimental data available in the literature. The parametric trends suggest a two-regime ebullient transport: (a) a constant volume regime where the bubble diameter is not affected by the flow rate, and (b) a growing bubble regime where bubble size increases with flow rate. The experimental data available in the literature for a wide range of liquids, flow rates and orifice sizes are analyzed to develop regime maps that characterize these two regimes. For a given liquid, the transition from the constant volume regime and the growing bubble regime is determined by the non-dimensional parameter, BoFr0.5 = 1 , that defines the interaction between buoyancy, surface tension and inertial forces. Correlation for isolated adiabatic bubble departure diameters is also developed based on a non-linear regression analysis of experimental data. The correlation considers the effects of thermo physical properties of the gas and liquid phases, orifice diameters and gas flow rates, and describes the experimental data published in the literature with in ± 10 percent.

Committee: Dr. Raj Manglik (Committee Chair); Dr. Milind Jog (Committee Member); Dr. Sang Young Son (Committee Member); Dr. Dion Dionysiou (Committee Member) Subjects: Chemical Engineering; Mathematics; Mechanical Engineering; Plastics

MS, University of Cincinnati, 2006, Engineering : Mechanical Engineering

Anti tank mines pose a serious threat to the occupants of armored vehicles. High acceleration pulses and impact forces are transmitted to the occupant through vehicle-occupant contact interfaces posing the risk of fatality. The use of an energy absorbing seat in conjunction with vehicle armor plating greatly improves occupant survivability during such an explosion. The axial crushing of aluminum tubes over a steel rail constitutes the principal energy absorption mechanism. The explicit non-linear finite element software LSDYNA is used to perform all numerical simulations. The occupant is modeled using a HYBRID III dummy. Numerical simulations are also conducted of the dummy's foot impact by the floor whose upward motion is comparable to an armored vehicle's reaction to a mine blast. A simple numerical formulation is presented to predict the deceleration response during dynamic axial crushing of cylindrical tubes. The formulation uses an energy balance approach and is coded in MATLAB. It can be used for injury assessment and survivability studies. The impact resistance of high strength fabrics makes them desirable in applications involving protection against penetration. A material model based on a micromechanical approach has been developed to realistically simulate ballistic impact of loose woven fabrics with elastic crimped fibers. The material model is implemented in LSDYNA.

Committee: Dr. Ala Tabiei (Advisor) Subjects:

PhD, University of Cincinnati, 2005, Engineering : Mechanical Engineering

Microslip friction plays an important role in determining vibratory response to external excitation of frictional interfaces. Surfaces in contact undergo partial slip prior to gross slip. This mechanism provides significant energy dissipation as a result of interface friction, thereby considerably reducing vibratory response of the system. Developing physics-based phenomological models for frictional contacts is the underlying aim of our study. Both analytical and numerical approaches have been employed for characterizing the interface friction behavior. Numerical approaches have traditionally employed bilinear hysteresis elements to simulate frictional contact. Single degree of freedom (SDOF) models that only include a single hysteresis element have been the focus of research in the past. Though these models capture the interface behavior qualitatively, they cannot be truly representative or predictive of the underlying physics of frictional joints. A multiple degree of freedom (MDOF) model built from a finite number of hysteresis elements can discretize the continuous friction interface, and is inclusive of the microslip approach. However, parameter estimation constitutes an important aspect of these models, and currently it is carried out using a calibration approach rather than physical motivation. We have developed a class of multiple degree of freedom (MDOF) model that account for microslip behavior of friction joints. The models take into account the damper mass, which was studied by very few models in the past. This adds significant dynamics to the phenomological model, thereby providing a more efficient tool to simulate friction joints using numerical models. These models are successful in capturing hysteresis behavior of frictional contacts. They also depict the exponential scaling of frictional energy dissipation with applied forcing level. As such, the richness of the frictional interface can be captured using these models. A complimentary analytical sol (open full item for complete abstract)

Committee: Dr. Edward Berger (Advisor) Subjects: Engineering, Mechanical

Doctor of Philosophy, The Ohio State University, 2011, Psychology

Numerical estimation—a process of mapping a non-numerical quantity to an approximate numerical one (and vice-versa)—improves greatly with age and experience. What this change entails and how it occurs has engendered a lively and provocative debate in the literature on numerical cognition. At the center of this debate lies a range of potential cognitive processes that are theoretically capable of generating observed changes in estimation performance. Choice of the most likely model of these cognitive processes is a difficult problem: models vary greatly in complexity, leading to a trade-off between their ability to fit any one data set and their ability to predict new data. In this dissertation, I argue that conventional attempts to evaluate models have not been adequately sensitive to this trade-off. As a result, conventional model selection techniques run the risk of favoring complex models that fail to predict the likelihood of future responses on the same laboratory task, on similar laboratory tasks, and on real-world analogues. To address this issue, I (1) applied conventional model selection procedures to analyze the performance of 740 subjects in 9 experiments using one numerical estimation task (number line estimation), (2) contrasted conventional model fits with a hierarchical Bayesian analysis of the same data set in order to identify the models most likely to have generated the data, and (3) evaluated the model parameters and fits of competing models to predict performance in other numerical estimation tasks (i.e., measurement estimation, numerosity estimation, and number categorization) as well as real-world numerical performance (i.e., math achievement scores and memory for numbers). Results indicated that conventional model fits differed based on whether the models were fit to individual children's estimates or to fictional estimates obtained by averaging over them. Analyses of individual and averaged data supported the logarithmic, linear and segme (open full item for complete abstract)

Committee: John Opfer (Advisor); Mark Pitt (Committee Member); Vladimir Sloutsky (Committee Member) Subjects: Cognitive Psychology

Master of Arts, The Ohio State University, 2009, Psychology

A core finding in the development of numerical estimation has been that performance improves with age. This change has often explained by children switching from inaccurate, logarithmic representations of numeric magnitude to more accurate, linear representations. In this thesis, I propose that developmental changes are more usefully seen as decompression in the magnitudes associated with numbers. To test this decompression hypothesis, I reevaluated the numerical estimates of 728 children with a measure sensitive to slight differences in curvature of response pattern, a power function, and compared it to alternative models of numerical estimation (Study 1a). The power function proved nearly as accurate and unbiased in characterizing “logarithmic” patterns of estimates as the logarithmic function, and it allowed accurate characterization of all children's estimates (including “linear” patterns, which tended to show some degree of compression). Further, in Study 1b, I found that the compression parameter of the power function (its exponent) proved a better predictor of accuracy than logarithmic/linear status, and it was just as sensitive to differences in age, sex, and experimental conditions as was log/lin status. In Study 2, I then applied the power function to assess the representations used to estimate symbolic and non-symbolic numeric magnitude (Study 2), with the finding that the power function was more sensitive to the similarity of the representations used across the two tasks. Finally, in Study 3, I applied the power function to test the hypothesis that differences between symbolic and non-symbolic numerical estimation are verbally mediated, finding that interference of verbal processes did increase the similarity of estimates across the symbolic and non-symbolic estimation tasks, specifically by making non-symbolic estimation more similar to symbolic.

Committee: John Opfer (Advisor); Jay Myung (Committee Member); Vladimir Sloutsky (Committee Member) Subjects: Psychology

Doctor of Philosophy, The Ohio State University, 2006, Geological Sciences

Three-dimensional, field-scale (~ 100 m) convective mixing processes in heterogeneous porous media are examined. The focus is on fluid mixing rates and density-dependent macrodispersion, and the influence of small-scale (~ centimeters) instability development on large-scale variable-density flow and solute transport behavior. Dynamic adaptive mesh refinement methods (AMR) and a higher-order (solute advection term), mass-conservative Eulerian-Lagrangian discretization scheme for the solute transport equation are used to construct a new numerical code (DensTransAMR) that automatically adjusts to multiple scales of convective mixing processes by translating and adding/removing telescoping levels of progressively finer subgrids during a simulation. Because the flow and transport solutions for each subgrid are computed independently, field-scale simulations are broken into multiple smaller problems that can be modeled more efficiently and with finer detail. Two types of numerical experiments are performed: freshwater injection in a saltwater aquifer and dense fluid injection in a freshwater aquifer. Convective mixing rates are related to the geostatistical properties of the aquifer (variance and mean of the log permeability distribution, horizontal and vertical correlation scales), the fluid density difference, the magnitude of local small-scale dispersion, the effects of different permeability field realizations, the injection well size and orientation, hydraulic parameters such as injection rate and regional hydraulic gradient, and the spatial resolution. Convective mixing in heterogeneous porous media is shown to be more amenable to prediction than previously concluded. Computed three-dimensional fluid mixing rates are related to mathematical expressions for density-dependent macrodispersivity that are based on stochastic flow and solute transport theory and are a function of log permeability variance, the correlation scale, and a time-dependent parameter. Different i (open full item for complete abstract)

Committee: Motomu Ibaraki (Advisor) Subjects:

Master of Science (MS), Ohio University, 1992, Civil Engineering (Engineering)

A full-scale field test was conducted to determine the response of a corrugated metal pipe arch culvert for the exceptional live load. The design span and rise of the culvert were 15 feet 8 inches and 9 feet 6 inches respectively. The cover for the first and second day of testing were approximately 7.5 feet and 3 feet respectively. Position transducer and strain gage techniques were used to measure the deflection and strains. Data was collected by using computer controlled data acquisition system. A tape extensometer was used to determine the shape of the culvert before and after the testing. Exceptional live load was applied through the two seven inch diameter piston rod hydraulic cylinders. They had a capacity of 230 tons and connected to a hydraulic control unit for simultaneous operation. A total of three loading sequences were applied, one on the first day and two on the second day. The ultimate load carrying capacity of this type of culvert under 3 feet cover was determined to be 100 tons approximately. Maximum vertical deflection of 6.989 inches occured at the crown point during the third loading sequence. During the first sequence the magnitude of moment and thrust was insignificant. In the first loading sequence symmetric nature prevailed in the culvert response. No section exceeded its ultimate moment capacity of 3.745 kips-ft/ft. During the second and third loading sequences of only section four exceeded its plastic moment capacity and formed a plastic hinge. The formation of creases at both sides of the instrumented section were reported. The slip occured at a bolted connection near to the crown was also reported. A numerical analysis was done using the CANDE finite element program. Parameters for Duncan's hyperbolic model were derived from the triaxial tests conducted using the undisturbed soil samples from the field. The numerical predictions were compared with the field response. Although the magnitude didn't agree well an identical trend was observed (open full item for complete abstract)

Committee: Shad Sargand (Advisor) Subjects: Engineering, Civil

Doctor of Philosophy (PhD), Ohio University, 2004, Physics (Arts and Sciences)

Physical nanoscale systems have been analyzed both from an electrostatic point of view and quantum mechanically with respect to quantum computation. We introduce an elaborate code for the efficient numerical simulation of nanoscale electrostatics via a higher – order relaxation algorithm with a large variety of boundary conditions which then is applied to a set of physically relevant problems. Great emphasis is put on screening effects as well as capacitive coupling between spatially separated conducting regions. Specifically, we analyze the depletion of a two – dimensional electron gas using different methods. The effect of surface charges due to the pinning of the Fermi level at a semiconductor surface is shown to play an important role in that it can shift the whole system characteristics, underlining the importance of chemical potentials and work functions. The capacitive coupling is further used to model the interactions in an interacting network of quantum dots, and the use of the capacitance formalism in the quantum mechanical context is explicitly justified. Quantum dot arrays are then analyzed on a general footing with respect to quantum computation and charge qubits based on an extended Hubbard Hamiltonian model. For systems with at most two operative electrons, general restrictions apply, introducing certain constraints on what realizations of this type of charge qubit may eventually look like. Furthermore, the interaction of the macroscopic world with the quantum dot network via quantum gates is discussed. Again, general arguments allow us to rule out certain scenarios of quantum gates. For example it turns out that capacitive coupling alone is not sufficient for full single qubit operation. Alternative ways are discussed, and finally, by using an external magnetic field and its resulting Aharonov – Bohm phases on the array, full single qubit operation based on charge is demonstrated.

Committee: Sergio Ulloa (Advisor) Subjects: Physics, Condensed Matter

MS, Kent State University, 2012, College of Arts and Sciences / Department of Earth Sciences

A buried valley is an ancient river or stream valley that predates the recent glaciation and since has been filled with glacial till and/or outwash. Outwash deposits are known to store and transmit large amounts of ground water. Their productivity largely depends on their hydraulic properties, rate of recharge and their hydraulic relationship with the adjacent bedrock formations. These relationships were illustrated by using MODFLOW to simulate steady-state three-dimensional flow through a section of a buried valley in Northeastern Ohio. The flow domain was divided into five hydrostratigraphic units: low conductivity (K) till and high K outwash parts of the drift sediment within the buried valley and three bedrock units: Pottsville Formation, Cuyahoga Group and Berea Sandstone, while the pre-Berea formations served as a no-flow boundary. Model input data, e.g. spatial distribution of the hydrostratigraphic units and their hydraulic properties were estimated using the data from Well Log and Drilling Reports of residential water wells. The model was calibrated using observed hydraulic heads and flow data with mean residual head error of 0.3m (1.0'). The calibrated model was used to quantify flux between buried valley and bedrock formations. Mass balance for the entire model consists of 2.7 Mm3/yr (87%) of inflow by recharge from precipitation and 0.4 Mm3/yr (13%) of inflow across the upstream model boundary. Approximately 80% of the inflow goes out as an outflow across the downstream model boundary and the remaining ¿¿¿¿¿¿¿ 20% leaves the model as baseflow to Chagrin River. Within the model, buried valley receives 1.6 Mm3/yr (¿¿¿¿¿¿¿40% of the total inflow to the buried valley aquifer) from the adjacent bedrock aquifers. Mass balance along the buried valley/bedrock contact indicates that Pottsville Formation contributes 0.96 Mm3/yr (or 0.34 Mm3/yr/km) while the Berea Sandstone contributes 0.64 Mm3/yr (or 0.22 Mm3/yr/km). The calculated mass balance error is -2.2%. Sig (open full item for complete abstract)

Committee: Yoram Eckstein Professor (Advisor); Abdul Shakoor Professor (Committee Member); Griffith Elizabeth Dr. (Other) Subjects: Geological; Geology; Hydrology; Water Resource Management

Doctor of Philosophy, Case Western Reserve University, 2010, EECS - Computer and Information Sciences

Traditional medical education has relied on training with real patients in actual clinical setting under the supervision of an experienced surgeon. Novice surgeons can make mistakes that result in risks to patient safety. Computer simulation-based training has been proposed to complement traditional training to improve patient safety and surgeon efficiency and reduce cost and time. Surgical simulation allows surgeons to learn, practice and repeat surgical procedures to gain experience in a realistic and safe environment. This dissertation focuses on the development of computer-based surgical simulations. Physically based modeling is used to model deformable objects to mimic human organs in simulation. Such a simulation is composed of many simulation objects whose behaviors are represented by differential equations. The system of differential equations can be solved by using numerical integration algorithms. Moreover, physical intersections between the objects require the computation of collision detection and response between objects. This dissertation studies the determination of elasticity parameters in lumped element models, the trade-offs in numerical integration algorithms for finding the suitable numerical integration algorithms and time step size of simulation objects, and the collision detection and response algorithms for deformable objects. Improvements and extensions of the open source/open architecture GiPSi surgical simulation framework are also presented. An endoscopic third ventriculostomy simulator is constructed using the GiPSi framework as a test bed of the specific tools and methods developed.

Committee: M. Cenk Cavusoglu PhD (Committee Chair); Guo-Qiang Zhang PhD (Committee Member); Vira Chankong PhD (Committee Member); Shudong Jin PhD (Committee Member); Alan R. Cohen MD (Committee Member) Subjects: Computer Science

Doctor of Philosophy, Case Western Reserve University, 2004, Biomedical Engineering

Ventricular fibrillation and tachycardia are the leading causes of sudden cardiac death in the United States. Yet, despite extensive research, their nature as well as the electrophysiological mechanisms responsible for their initiation and sustenance are not fully understood. Researchers have suggested that the breakup of a spiral wave, a vortex-like electrical wave, may be one major mechanism by which tachycardia can evolve into fibrillation. We therefore apply linear perturbation theory, a mathematical technique, to gain new insights into the electrophysiological and dynamical mechanisms underlying this phenomenon. We found spiral wave perturbation dynamics to be composed of a multitude of characteristic and independent behaviors, called eigenmodes. Along with one meandering mode, not just one but several unstable alternans modes were found with differing growth rates, frequencies and spatial structures, suggesting different electrophysiological properties. We also explored a promising new approach, based on the theory, for the design of an energy efficient electrical stimulus protocol to control spiral wave breakup. We show a particular example in which the instability of an entire spiral wave can be controlled in the linear regime over several rotation periods using a single localized stimulus applied at one instant in time. Computer simulation of cardiac activity has been another popular approach used to study arrhythmia. However, due to various numerical constraints, these simulations are computationally costly when modeling large tissue size using realistic ionic cell models. We have therefore developed a new fast variable timestep method. The method is explicit, yet highly stable, permitting the use of adaptive timesteps much larger than the limit imposed by conventional explicit methods. We perform a thorough study of computational efficiency of the method, by examining how the grid spacing, tissue size and error tolerance affect runtimes obtained for the H (open full item for complete abstract)

Committee: Niels Otani (Committee Chair); Yoram Rudy (Other); Igor Efimov (Other); Daniela Calvetti (Other) Subjects: