Master of Science, University of Akron, 0, Applied Mathematics

The material known as graphene has been shown to exhibit highly desirable properties with respect to strength and conductivity of both heat and electricity. In this thesis, I will study the structure of a suspended sheet of graphene above a rigid substrate. A sheet of graphene will be represented as a chain of bonded atoms in 2D that is supported above a fixed line of atoms representing a substrate. My energy-based model includes bond stretching energy, van der Waals energy, as well as bending energy dependent on the angle between adjacent atomic bonds. The system is assumed to evolve via gradient-flow dynamics so that the atoms move to achieve a minimum energy configuration. Simulations show isolated wrinkles when the mismatch between the equilibrium distance of the atoms on the chain and the spacing of the atoms on the substrate is small. This wrinkling can be attributed to van der Waals interactions between atoms on the chain and atoms on the substrate.

Committee: Dmitry Golovaty Dr. (Advisor); J. Patrick Wilber Dr. (Advisor); Malena Espanol Dr. (Advisor) Subjects: Materials Science; Mathematics; Molecular Physics

Master of Science, University of Akron, 2015, Applied Mathematics

Having already shown great potential for novel engineering applications, graphene and other carbon-based nanostructures (CNSTR) are being investigated for use in nanotechnology and Nanoelectromechanical Systems. For the design of nanoscale devices, it is important to understand the geometries and behavior of CNSTR. We study an atomistic energy-based model for graphene. We model a graphene sheet as a two-dimensional sheet of atoms in ℜ³. We derive an expression for the total internal energy of a CNSTR considering only the energy of covalently bonded atoms, the energy of the local interaction between non-bonded atoms, and the energy due to the bending of adjacent atomic bonds. The configuration of a CNSTR is initialized, and we run simulations using gradient flow dynamics to minimize total energy and determine equilibrium configurations. Predictions from our model show that the structure of the final configuration depends on the relative strengths of the forces as well as the initial configuration.

Committee: Dmitry Golovaty Dr. (Advisor); Patrick Wilber Dr. (Committee Member); Malena Espanol Dr. (Committee Member) Subjects: Materials Science; Mathematics; Nanotechnology

Master of Science, University of Akron, 2014, Mechanical Engineering

In a university setting, parking service plays a critical role in complementing education. It is important to provide and manage university parking services that balance the resources of the university, market conditions, and the safety of all members of the campus community, and the convenience of the users. The complexity of the parking facility distribution, the dynamic nature of the traffic flows, and the randomness of the parking access times is indicative of both the challenge of this work as well as the urgency with which it is needed. Previous literature in parking system analytics has mainly focused on using proper parking capacity to user ratios to allocate parking resources. However, this approach doesn't offer much operational details in dealing and managing regional parking congestion issues, which are the major concerns in both the design and continuous improvement process of the parking system. This research, therefore, proposes to use a scientific based, data-driven approach to systematically model, validate, and simulate alternative parking strategies for optimal system redesign. Specifically, discrete event simulation model is used to capture the parking systems dynamics in granular details to enable deeper understanding and subsequent continuous improvement of the parking systems.

Committee: Shengyong Wang Dr. (Advisor); Jared Coleman Mr. (Committee Member); Sergio Felicelli Dr. (Committee Member) Subjects: Mechanical Engineering

Doctor of Philosophy, The Ohio State University, 2009, Family Resource Management

The main purpose of this study was to examine whether Long-Term Care Insurance (LTCI) ownership causes moral hazard in the Long-Term Care (LTC) market. By accounting for the endogeneity of LTCI ownership and LTC utilization, this study explored the unbiased effect of LTCI ownership on LTC utilization using duration analysis. In addition, this study presented the determinants of LTCI purchase and those of first LTC use of the elderly.Using the longitudinal data from 1998-2004 HRS (Health and Retirement Study), the first LTC use among the elderly who are 65 and older were analyzed. Two duration models were employed accounting for the endogeneity of LTCI purchase and LTC use: Cox model used lagged LTCI values and the discrete time model used the LTCI values predicted in the two-stage estimation. Findings from the two models were very consistent. Based on the two-period utility model, this study estimated LTCI purchase and first LTC use. As for LTCI purchase, the elderly with higher income and non-housing assets were more likely to buy LTCI. Denying the concern of adverse selection in the LTCI market, those who had poor health conditions were less likely to buy LTCI. And those who had informal caregivers were less likely to purchase LTCI, implying that informal care and formal LTC are substitutes. LTCI ownership increased the use of nursing home care, indicating some moral hazard in the nursing home care. And no moral hazard was found in the home care market. Medicaid eligibility significantly increased LTC use, while income and non-housing assets had negligible effect on LTC utilization, suggesting that financial resources are not important factors that determine LTC use. In addition, health limitations substantially increased LTC use, and availability of informal caregivers decreased the probability of using LTC. With the findings that LTCI ownership would not generate substantial moral hazard in the LTC market, this study provideed evidences to support the policy ini (open full item for complete abstract)

Committee: Gong-Soog Hong (Advisor); Catherine P. Montalto (Advisor); Kathryn Stafford (Committee Member); Robert Scharff (Committee Member) Subjects: Health Care

Doctor of Philosophy, The Ohio State University, 2004, Materials Science and Engineering

In this work, AC loss in superconducting composites was described using both an anisotropic continuum model and a discrete model. The efforts were concentrated in three main areas. First, the eddy current coupling loss of composites with rectangular cross section was calculated using an anisotropic continuum description based on a block model with different effective resistivities in each block. In this case, a numerical approach was used. This treatment, like the more typical lumped component network model, was able to describe many factors influencing the eddy current loss in the rectangular composites, such as twist pitch, aspect ratio, and core resistivity. However, the influence of core thickness and the presence of an outer sheath were also described with this model. Certain simplifying assumptions were used here to minimize computation time, while allowing the essential information to be extracted. In the second area, the eddy current loss of round composites were calculated from a discrete (network) point of view, and analytic expressions were developed which allow comparison to analytic expressions which were derived from effective medium theory. We need to measure only the contact resistance between the strands. The eddy current coupling loss of seven-strand MgB2 cables were then calculated by this model. With this model, it was possible to use a measured contact resistance between the strands to both predict the loss and compare to effective medium based resistivities. The results from the block model and from the analytical model give results in reasonable agreement. In the third part of the work, we attempt to compare the developed expressions to experiment. In some cases, data extant in the literature were used; in other cases, direct measurements were performed. For the rectangular geometry composites, existing data were sufficient. In the case of round composites, direct experiments were performed. The specific working medium chosen was round, seven- (open full item for complete abstract)

Committee: Suliman Dregia (Advisor) Subjects: Engineering, Materials Science

Doctor of Philosophy, Case Western Reserve University, 2009, Social Welfare

Purpose: This project focused on individual and neighborhood characteristics associated with child maltreatment in Cuyahoga County, Ohio. It sought to better understand risk and protective factors associated with child maltreatment, specifically the roles of race and neighborhood disadvantage. It used an ecological framework that takes into account multiple levels, and incorporated a developmental perspective that suggests that risk and protective factors vary by child age. Particular attention was paid to race and racial disproportionality in the child welfare system.Methodology: This study used a multi-level discrete time hazard model to estimate the effects of individual/household and neighborhood factors on the timing of child maltreatment reports accepted for investigation and indicated/substantiated reports of child maltreatment. Findings: This study showed that younger children are at highest risk of being the subject of a maltreatment report, yet much of this increased risk is explained by mother's age, marital status, use of alcohol and tobacco during pregnancy, and child's birth weight and receipt of TANF. Additionally, being born to an African American mother greatly increases the likelihood of being the subject of a maltreatment report. However, once other individual and neighborhood factors are taken into consideration, the increased risk for Black children drops considerably and is no longer a significant predictor of investigated reports of child neglect or substantiated/indicated reports of maltreatment. This study found the hazard of child maltreatment to be greater among children living in impoverished and instable neighborhoods. Moreover, the impact of neighborhood characteristics was found to exert its strongest effect on reports of child neglect compared to all types of reports or indicated/substantiated reports of maltreatment. Finally, findings suggest that for Black children, the relationship between neighborhood disadvantage and maltreatment (open full item for complete abstract)

Committee: Claudia Coulton PhD (Committee Chair); David Crampton PhD (Committee Member); Jill Korbin PhD (Committee Member); David Miller PhD (Committee Member) Subjects: Social Research; Social Work; Welfare

Master of Arts (MA), Bowling Green State University, 2021, Psychology/Developmental

Studies examining age differences in the Ultimatum Game, an economic bargaining game, have produced mixed results regarding which age group is more likely to accept unfair offers. One possible explanation for age differences in the Ultimatum Game is that emotions differentially affect young and older adults' decision to accept or reject unfair offers. Research has found that emotions play an important role in decision-making, and that discrete emotions may lead to distinct thoughts, actions, and goals. Additionally, studies have shown that older adults rely on emotions to make decisions to a greater extent than younger adults. According to the discrete emotion theory of affective aging (DEA), discrete emotions have different adaptive advantages at different ages (Kunzmann et al., 2014). Specifically, the DEA proposes that anger motivates younger adults to achieve age-normative tasks, while sadness is adaptive in older adulthood, when loss is common and time left to change unfavorable situations is limited. The present study examined discrete emotions experienced by young and older adults during the Ultimatum Game as a possible explanation for age differences in acceptance and rejection decisions in the Ultimatum Game. Young and older adult MTurk workers (n = 113) participated in a modified version of the Ultimatum Game that was designed to increase emotional salience and ecological validity. Young adults reported higher levels of discrete negative emotions, partially supporting the DEA. Interestingly, young adults were also more likely to accept unfair offers in the Ultimatum Game. Anger and disgust were significant predictors of Ultimatum Game decision; however, no significant interactions between age and discrete emotions emerged. Implications and future directions are discussed in light of these findings.

Committee: Yiwei Chen Ph.D. (Advisor); Richard Anderson Ph.D. (Committee Member); Dara Musher-Eizenman Ph.D. (Committee Member) Subjects: Psychology

Master of Science, The Ohio State University, 2016, Civil Engineering

Expanding travel choices by providing ridesharing can improve mobility and accessibility and reduce congestion and the negative externalities associated with single occupancy automobile use. To realize these benefits, sufficient demand must be generated by matching drivers and passengers with similar origins and destinations and who are willing to travel with potential strangers. Technological developments have facilitated the provision of real-time ridesharing programs, where travelers are matched to share a ride shortly before they travel. Real-time ridesharing offers additional flexibility and the possibility of occasional use that may be desirable in an increasingly complex society with varying schedules. While initial real-time travel options have been perceived as unattractive due to reliability and personal safety concerns, the growing success of real-time ride-sourcing services suggests that perceptions may be shifting. Furthermore, large employer-based ridesharing offers additional promise due to a network of co-workers with similar work locations facilitating good matches, increased familiarity with fellow travelers, and the ability to incentivize participation. A stated preference survey of The Ohio State University community was used to analyze willingness to participate in an idealized real-time employer-based ridesharing program. Individual characteristics and travel behaviors associated with unwillingness to participate in an ideal program are analyzed. Also, the characteristics and behaviors associated with interest in a passenger or driver role in such a program are identified. Many findings support results presented elsewhere and a priori expectations, for example an increased willingness of younger travelers to participate in ridesharing, an increased willingness of females to participate as passengers, and an increased willingness of those with experience driving to participate as drivers. In addition three findings provide important insights (open full item for complete abstract)

Committee: Mark McCord (Advisor); Rabi Mishalani (Advisor); Gulsah Akar (Committee Member) Subjects: Civil Engineering; Transportation

Doctor of Philosophy, The Ohio State University, 2009, Sociology

The high rates of offenders returning to prison after their release have renewed interest in explanations of recidivism. While researchers have focused on individual level crime theory and characteristics to explain recidivism, one neglected area of study is neighborhood context's role in recidivism. The few examples of research that attempts to address this gap also fail to incorporate the fact that recently released offenders are likely a highly mobile population, something that could cause error in contextual analysis.Using a unique dataset of released offenders in Ohio that contains serial residence and violation information, this project tests a social disorganization model of recidivism, while also analyzing mobility patterns. A third analysis uses a unique property of the dataset: the fact that it includes prisoners sentenced under indeterminate and determinate sentencing guidelines. This offers the chance to assess the deterrent aspects of the switch in sentencing as well as how deterrence interacts within neighborhood context. The first analysis of residential mobility patterns answers four questions: do recently released offenders move, where do recently released offenders move, who lives where initially, and who moves? The results indicate that offenders do move and move at a higher rate than the general public, with most offenders in the study experiencing at least one move in the first year after release. These movements are mostly lateral, or to neighborhoods that are similar to the neighborhoods offenders reside in immediately after release. Neighborhood of initial residence is related most notably to race and whether an offender is released into a halfway house. Finally, movement is related to employment, race, and living in a halfway house. The second analysis of contextual effects on recidivism, using discrete time multilevel logistic regression models to predict likelihood of a parole violation and arrest, reveals support for social disorganizatio (open full item for complete abstract)

Committee: Christopher Browning PhD (Committee Chair); Ruth Peterson PhD (Committee Member); Paul Bellair PhD (Committee Member) Subjects: Criminology; Sociology

Doctor of Philosophy (PhD), Ohio University, 2009, Electrical Engineering (Engineering and Technology)

The dissertation presents a novel hierarchical block-diagram modeling framework for manufacturing systems. A block can be a single manufacturing operation, a single machine, a single part or a factory. Each block has three inputs and three outputs and is represented by a set of linear max-plus algebraic equations. A complex manufacturing system can be modeled as a network of basic manufacturing blocks. Routing of parts and resources through the block diagram graphically corresponds to machine-flow and resource-flow interconnection of blocks and is mathematically modeled by part-flow and machine-flow interconnection matrices, respectively. A formula for composing a network of manufacturing blocks into a single manufacturing block is derived. The model can be used for: (a) performance evaluation, (b) deadlock detection, (c) structural analysis, (d) scheduling, (e) design, and (f) control of manufacturing systems.The dissertation develops an elegant analysis tool called a matrix signal flow graph (MSFG) over max-plus algebra (also called a synchronous MSFG) for these models. New topological methods for evaluating gains of synchronous MSFGs are presented. Synchronous MSFG provide a straightforward way to covert the graphical block-diagram representation of the system to the max-plus algebraic view. The dissertation also shows that in the case of a permutation flow shop, an inverse Monge matrix represents the resulting algebraic equations for the system. The dissertation proves that the class of inverse Monge matrices is closed under max-plus algebraic multiplication, and provides an efficient algorithm for computing an eigenvector of an inverse Monge matrix. These properties allow for efficient computation of performance characteristics of permutation flow shops.

Committee: Robert P. Judd PhD (Advisor); Kenneth Cutright PhD (Committee Member); William Kaufman PhD (Committee Member); Douglas Lawrence PhD (Committee Member); Dušan N. Šormaz PhD (Committee Member); Constantinos Vassiliadis PhD (Committee Member) Subjects: Computer Science; Electrical Engineering; Engineering; Industrial Engineering; Mathematics; Operations Research

Master of Science (MS), Ohio University, 1991, Industrial and Manufacturing Systems Engineering (Engineering)

The research constituting this thesis originates from a Federal Highway Administration's Graduate Research Fellow- ship entitled "Calibration of RFLO Traffic Simulation Program." The RFLO Simulation Program provides a macroscopic description of vehicular traffic flow. The majority of the research was performed at the FHWA's Turner-Fairbank Highway Research Center (McLean, Va.) during the time from June 15 to September 15, 1989. The actual calibration procedure centered around RFLO's Relaxation Constant parameter, a partial differential equation - containing the parameter - representing the acceleration/deceleration of macroscopic traffic, and the microscopic traffic data sets that were available at the research facility. Initially, the microscopic traffic data needed trans- formed into a macroscopic traffic description in order to facilitate a legitimate comparison to RFLO. While becoming acquainted with the data sets several types of errors and misconceptions were identified and subsequently streamlined from the recorded traffic descriptions. The transformation process would create quantities of Volume (Q), Density (k), and Speed (v) describing a facility's traffic behavior de- pendent upon a distance region (DX) and time interval (DT). In order to justify these averaging regions a DX-DT Aggrega- tion Analysis resulted. This analysis used carefully selected DX-DT combinations and the Rational Subgroupping Concept (Montgomery, 1985) to arrive at the conclusion, for the Roscoe Boulevard data set, of using a DX of 200 feet and a DT equal to 3 seconds. By performing the transformation to this aggregation level an "optimal" overall macroscopic description of the Roscoe Boulevard's traffic behavior was attained. The calibration of RFLO's Relaxation Constant was expected to provide additional agreement with Prigogine and Herman (1971) whom suggest that the (RFLO) "forcing func- tion" is a disastrous simplification of the manner and abil- ity for which macroscopic traffic (open full item for complete abstract)

Committee: Helmut Zwahlen (Advisor) Subjects: Engineering, Industrial

Doctor of Philosophy (Ph.D.), University of Dayton, 2011, Mechanical Engineering

As the use of composite materials in aerospace structures continues to increase, the need to properly characterize these materials, especially in terms of damage tolerance, takes on additional importance. The world wide failure exercises (WWFE) are an example of the international interest in this issue. But though there has been a great deal of progress in understanding the initiation of damage and modeling damage propagation along known interfaces, methods that can capture the effects of interactions among various failure modes accurately remain elusive. A method of modeling coupled matrix cracks and delamination in laminated composite materials based on the finite element method has been developed and experimentally validated. Damage initiation is determined using the LARC03 failure criterion. Delamination along ply interfaces is modeled using cohesive zones. Matrix cracks are incorporated into the discretization of the problem domain through a robust Mesh-Independent Cracking (MIC) technique. The matrix cracking technique, termed the Regularized Extended Finite Element Method (Rx-FEM), uses regularized forms of the Heaviside and Dirac Delta generalized functions to transform the crack surface into a volumetric crack zone. The Regularized Extended Finite Element method is compared to benchmark cases. The sensitivity of the solution to mesh size and parameters within the cohesive zone model is studied. Finally, the full method with delamination is employed to study a set of experimental tests performed on open-hole quasi-isotropic laminates. The trends of hole-size and ply thickness are well predicted for the laminates. Rx-FEM is also able to simulate the pattern of damage, as demonstrated by comparisons to x-ray images. From the results of this series of analyses it can be concluded that failures occur when delamination originating at the hole links up with delamination originating at the edge along the path of matrix cracks.

Committee: Robert A. Brockman PhD (Committee Chair); Steven L. Donaldson PhD (Committee Member); Endel V. Iarve PhD (Committee Member); James M. Whitney PhD (Committee Member) Subjects: Mechanical Engineering; Mechanics

Master of Sciences, Case Western Reserve University, 2009, Chemical Engineering

In this study, a discrete in silico model of cell island migration based on random walkMonte-Carlo was constructed to elucidate cell island size effects as observed in previous work. Also, this study improves theoretical understanding of cell island size effects on invasiveness. Results show the model successfully reproduces trends observed in previous work. Trials using interaction energies ranging from -10 to +100 KBT were conducted. The model is capable of differentiating attractive interaction energies but lacks differentiability for repulsive interaction energies which is due to model saturation. Exclusion of cell proliferation is overcome by a novel procedure, the cell island contour graph method. Theoretical analysis yields several important findings regarding model construction and cell island size effects on invasiveness such as model selection frequency and expansion layer effect. It is concluded that the model in this study is valid and changes in cell island size affect cell island dynamics.

Committee: Harihara Baskaran PhD (Advisor); Heidi Martin PhD (Committee Member); Daniel Lacks PhD (Committee Member) Subjects: Chemical Engineering

Master of Science, University of Akron, 2012, Applied Mathematics

A biofilm is a community of microorganisms embedded in a matrix of polymers. The focus of this project is on biofilms that grow in the lungs of cystic fibrosis (CF) patients. A biofilm structure protects bacteria and makes it harder for natural enzymes and drugs to fight the bacteria within the biofilm. Biofilms also secrete compounds that stimulate pro-inflammatory cytokines, which further damage the underlying lung tissue. The goal of this work is to improve the understanding of how drugs disperse through a biofilm. To accomplish this goal, a discrete model was adopted. The model describes the nutrient and biomass as discrete particles. Diffusion of the nutrient, consumption of the nutrient by microbial particles, and growth and decay of microbial particles are simulated using stochastic processes, which are directly related to physical and biological parameters of the system. These processes have been modeled previously by other authors. Our model extends the complexity of the biofilm system by including the conversion and reversion of living bacteria into a hibernated state, known as persister bacteria. Another new contribution is the inclusion of antimicrobial in two forms: an aqueous solution and encapsulated in biodegradable nanoparticles. Finally, we model bacteria movement using Monte Carlo (MC) techniques, which is unique from other discrete models. The bacteria population growth and spatial variation of drugs and their effectiveness are included in the project. Due to the stochastic nature of the model, different initial conditions affect the quantitative results of the biofilm growth. However, qualitatively the results are similar. The minimum inhibitory concentration (MIC) of the antimicrobial is 6 μg/mL, which is consistent with continuum models and experiments. However, this may take a long time to clear the biofilm. For example, it took 8 μg/mL of antimicrobial over four days of exposure to kill all the living bacteria. The distribution of nanoparti (open full item for complete abstract)

Committee: Alper Buldum Dr. (Advisor); Curtis Clemons Dr. (Committee Member); Gerald Young Dr. (Committee Member) Subjects: Applied Mathematics; Biophysics; Physics