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

There are three main research conducted in this paper, including using deep learning methods with vision-based technologies on Structural Damage Detection (SDD), Structural Health Monitoring (SHM) and progressive collapse study. During the learning and improvement process, many goals of automation in SDD and SHM have been achieved, although there will be a large room for further improvement and development on these studies. In progressive collapse study, remote sensing technologies and data fusion are applied on a field experiment of a real building at the Central Campus of the Ohio State University. The major contributions of this paper are shown as follows: A few comprehensive experimental studies for automated SDD in extreme events using deep learning methods for processing 2D images. In the first study, a 152-layer Residual Network (ResNet) is utilized to identify multiple classes in eight SDD tasks, which include identification of scene levels, damage levels, material types, etc. The proposed ResNet achieved high accuracy for each task while the positions of the damage are not identifiable. In the second study, the existing ResNet and a segmentation network (U-Net) are combined into a new pipeline, cascaded networks, for categorizing and locating structural damage. The results show that the accuracy of damage detection is significantly improved compared to only using a segmentation network. In the third and fourth studies, end-to-end networks are developed and tested as a new solution to directly detect cracks and spalling in the image collections of recent large earthquakes. One of the proposed networks can achieve an accuracy above $67.6\%$ for all tested images at various scales and resolutions, and shows its robustness for these human-free detection tasks. Studies are conducted with a pipeline to automatically track and measure displacements and vibrations of structures or structural components in laboratory and field experiments. This novel framework (open full item for complete abstract)

Doctor of Philosophy, University of Toledo, 2020, Engineering

Using prescriptive design approaches, structures are intended to provide a life-safety level of protection that has been shown by recent natural hazard events to have limited contribution to the post-disaster resilience of a community. The performance-based engineering (PBE) methodology allows the structure to be designed to achieve any pre-defined performance objective. The structures of the future will not only aim at being structurally resilient but also sustainable to natural hazard loads. To contribute to the development of these structures, PBE requires the development of state-of-the-art numerical models for the accurate structural performance assessment and the creation of a framework that can effectively account for this performance when evaluating the environmental impacts of structures. This research has two main goals: i) to create state-of-the-art high-fidelity numerical models for the PBE of structures; and ii) to create a multidisciplinary framework for the resilient-based environmental impact assessment of structures subjected to natural hazard loads. In pursuit of this research's goals, four main objectives were conducted: High-Fidelity Numerical Modeling, PBE, Life Cycle Assessment, and Combined PBE and LCA. This research has been primarily conducted on reinforced concrete (RC) and cross laminated timber (CLT) structures, as the first is a traditional and resilient while the second is a newer and seemingly more sustainable structural alternative. However, the created approach can also be applied to other structural alternatives under natural hazard loads. The high-fidelity numerical models created have demonstrated to satisfactorily capture the structural performance of the considered building structure alternatives and the multidisciplinary framework created provides a powerful means for making science-based decisions when considering newer and seemingly more sustainable building structure alternatives while accounting for their natural hazard (open full item for complete abstract)

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

It was in the 1960s that one of the first self described user friendly computer analysis programs, STRESS (STRuctural Engineering Systems Solver), was introduced to the mainstream world. (Fenves et al. 1964). It was in the same STRESS User's Manual that Fenves et al. described the use of matrices as a “recent development in structural analysis” after being developed in the 1950s, though familiarity with matrix analysis was not required knowledge for the successful use of the program. In the time since the introduction of STRESS, matrix analysis has become a standard for structural analysis methodology as computers and computer analysis programs have become a standard tool used in the industry. With the increased use of these analysis programs by structural engineers comes the increased possibility for making mistakes. This possibility increases if there is not enough understanding of the parameters from which the program solves the structure. The research herein is a meta analysis of select structural analysis software in order to fully understand the differences in parameter definition processes within several of these programs, and to determine how those parameters and software-prescribed assumptions can affect the solution of given structural systems. The research employed within comprises the development of four models that were created within the select programs. The results of these models were then validated and compared with classical solutions. The first model chosen was to allow for determination of whether shear deformation was included, whether by default or as an option, within a program. The second model was a review of second order analysis capabilities of the programs through the use of the AISC Benchmark Models for P -Δ and P -δ analysis. The third model, comprising the bulk of the research, was a bilaterally symmetrical structure that allowed for the largest insight into the chosen programs with comparison between 2D and 3D s (open full item for complete abstract)

Doctor of Philosophy, University of Toledo, 2023, Foundations of Education

The proliferation of educational technology currently marketed by textbook publishers reflects the neoliberal influence in higher education that emphasizes automated, standardized delivery and skills-based curriculum. Inclusive access programs are publisher developed digital packages that include access to digital course materials at a lower cost to the student, claiming to provide equitable access despite evidence that a digital divide still exists. This embedded single-case study is a critical analysis of the decision-making power of faculty and administrators as it relates to the adoption of inclusive access programs at a community college. The purpose is to explore if the adoption of inclusive access contributes to inequality in the form of digital structural violence. Hegemony is used as the theoretical framework. Data collection methods include student and faculty focus groups, faculty and administrator interviews, and faculty and student surveys. Findings indicate that while faculty members do hold some hegemonic power, the greater hegemonic force belongs to publishers and bookstores. Student data shows an appreciation for the lower cost and immediate access, but they prefer printed textbooks for academic reading. The data also suggests the possibility that inclusive access contributes to digital structural violence, but further research is needed.

Doctor of Philosophy, The Ohio State University, 2019, Psychology

Multilevel structural equation modeling (MSEM) is an emerging statistical framework for the analysis of hierarchically structured data, such as data corresponding to students nested within classrooms or repeated measurements nested within individuals. The MSEM framework provides several advantages over the traditional multilevel modeling (MLM) and structural equation modeling (SEM) frameworks, including the ability to model multivariate responses, level-2 response variables, measurement error via factor models, and structural relations (e.g., regressions) among the random effects/latent variables. Although several formulations of the MSEM have been presented (see, e.g., Liang & Bentler, 2004; Rabe-Hesketh, Skrondal, & Pickles, 2004; Mehta & Neale, 2005), the framework of B. Muthen and Asparouhov (2008) as implemented in Mplus (L. K. Muthen & Muthen, 2017) has the advantage that the relationship between lower-level (i.e., level-1) latent variables can be modeled as randomly varying across upper-level (i.e., level-2) units. Unfortunately, maximum likelihood (ML) estimation of the parameters for such models, as implemented in Mplus, is computationally demanding due to the likelihood function having to be approximated, as the function cannot be computed in closed-form. Mplus numerically integrates over all of the random effects/latent variables using quadrature-based methods. This approach is not feasible for high-dimensional latent variable models, which reduces the potential models that can practically be fit. In this dissertation, I develop a more computationally efficient and accurate ML estimation routine for MSEMs with random slopes for latent variables. The method relies on a reformulation of the likelihood function so that some of the integrals can be computed analytically, reducing the dimension of numerical integration required. Specifically, only the random slopes for latent variables need to be numerically integrated, as the integrals corresponding to the ot (open full item for complete abstract)

Master of Sciences (Engineering), Case Western Reserve University, 2016, Civil Engineering

Seismic design of multi-story buildings requires capacity design principles that allow for distributed damage (plastic member deformations) to occur over the building height while preventing soft-story failure mechanisms that may lead to collapse. Seismic evaluation of steel concentrically braced frame (CBF) buildings has revealed that they exhibit soft-story behavior due to non-uniform brace degradation and non-ductile failure modes. This research proposes a rehabilitative design procedure for existing buildings that uses a stiff rocking core to redistribute plastic deformations along the structure's height. Additionally, an improved design procedure for braced frame columns is proposed for new frame design. Several representative frames were designed and evaluated using nonlinear transient seismic finite element analysis and large-scale hybrid experimental testing. Predicted, analytical, and experimental response results show reasonable agreement, and the proposed techniques are believed to be reliable for achieving desirable seismic performance in low- to mid-rise steel braced frame structures.

Master of Science, Miami University, 2015, Geology and Environmental Earth Science

This study focuses on the kinematics of extensional deformation and horst-graben formation in the Gediz Graben (GG), includes Caldag High which is a horst structure in the western GG. Graben formed under control of E-W trending, high angle normal faults and NNE-SSW oriented oblique slip faults. The geometry and internal structure of the GG were strongly controlled by this fault systems. Structural data, sedimentological records and seismic cross sections show that evolution of the western and eastern parts of the GG are quite different. Differential vertical axis rotations in the Menderes Massif during Miocene-Pliocene effected the opening style of the GG. We suggest that the development of the Izmir Balikesir Fault Zone, which occurs at western termination of the GG, was coeval with rotational opening of the GG, and coincided with an oblique-slip accommodation zone around a pole of rotation located right beyond the eastern apex of the GG.

Master of Science, The Ohio State University, 2014, Civil Engineering

When discussing the infrastructure in America, and more specifically, the problems facing America's infrastructure, bridge failures have been one of the leading problems facing America's infrastructure. Bridge failures often are costly in the commerce foregone, lives lost, and replacement funds required to rebuild the failed bridge. More than 8,000 bridges are categorized as structurally deficient, and almost 25% of all bridges are categorized as functionally obsolete, resulting in a bridge rating of a C+ given by the American Society of Civil Engineers (ASCE) in 2013. Ongoing studies of following trends and patterns in bridge failures has been an important undertaking, which can greatly enhance the ability for engineers to predict and avoid the great costs associated with a bridge failure. Previous studies to compile and analyze bridge failure data were conducted over the timeframe of 1977 to 1981, 1981 to 1989, and 1989 to 2000. The aim of this study was to continue these studies by compiling a comprehensive database to display the findings of this study, both graphically and in tabular form. Finally, a model was needed in order to help the end user visualize and interpret the data in light of preventing future bridge failures; to that end, fuzzy logic was applied to the data in order to create a user-friendly and intuitive model for preventing future bridge failures. In all, it was also found that the most vulnerable sections in a bridge with regard to bridge failure were scouring and the bridge's age, resulting in unmaintained and crippling bridges.

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

Protein structural alignment is important for studying similarities between proteins. Various protein structural alignment tools have been developed for this task. These alignment tools have different characteristics and strategies on which they are based. In order to find out which structural alignment tool is the best for the application in hand and to develop better tools it is very important to classify the tools into groups based on these strategies and characteristics. In this research we have studied several protein structural alignment tools and categorized them based on several properties. This provides a basis and background work for the development of future structural alignment tools. Typically the developers of a given structural alignment program test the program on a few pairs of proteins and comment on its comparison with other previously developed tools. Although there are a large number of alignment tools available, the tools have never been subjected to a comprehensive and critical comparative analysis on the basis of a common data set or test bench. The absence of such a common data set is the major reason for the lack of this analysis. In this research, we propose a benchmark data set to test any protein structural alignment program. This data set is composed of 221 protein pairs and is divided into 11 categories. We have tested all the online available structural alignment tools on this data set and analyzed their performance. On the basis of the alignment results we have computed overall rankings of these alignment tools using three different rating methods.

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

A method for structural health monitoring of large structures based on detecting acoustic emissions produced by damage was developed for this dissertation. The advantage of sensing acoustic emissions is that small damage can be detected in structures built with complex geometry and anisotropic materials. A longstanding limitation of the acoustic emission method is that a large number of bulky sensors are required to monitor cracks that can form at any location on a complex structure. The sensors and data acquisition system are also required to work at a high sampling rate because the frequencies of acoustic waves propagating in the structure due to damage are on the order of hundreds of kHz. To overcome the difficulties with using the acoustic emission method, a very elegant and powerful technique that many researchers have either missed or avoided is presented in this dissertation. The new sensing technique is called a structural neural system. The technique was difficult to develop, and required using electronic circuits to mimic the architecture of the biological neural system. In developing the technique, it was also necessary to recognize the strong linkage between fracture mechanics and fatigue damage detection. The structural neural system developed uses continuous (multi-node) sensors to mimic dendrites, receptors, and the axon which perform sensing in the biological neural system. Analog electronics were then developed to mimic the thresholding and firing functions of the soma (cell body) in the neural system. The end result is a structural neural system that tremendously reduces the complexity and number of data acquisition channels needed to monitor acoustic emissions and detect damage in structures that have high feature density. Simulation and laboratory testing of a prototype of the structural neural system showed that the structural neural system is sensitive to small damage and practical to use on large structures. A field test was also performed in (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2005, Civil Engineering

A multi-paradigm nonparametric model, dynamic fuzzy wavelet neural network (WNN) model, is developed for structural system identification of three dimensional highrise buildings. The model integrates chaos theory (nonlinear dynamics theory), a signal processing method (wavelets), and two complementary soft computing methods (fuzzy logic and neural network). An adaptive Levenberg-Marquardt-least-squares learning algorithm is developed for adjusting parameters of the dynamic fuzzy WNN model. The methodology is applied to one five-story test frame and two highrise moment-resisting building structures. Results demonstrate that the methodology incorporates the imprecision existing in the sensor data effectively and balances the global and local influences of the training data. It therefore provides more accurate system identifications and nonlinear approximation with a fast training convergence. A nonparametric system identification-based model is developed for damage detection of highrise building structures subjected to seismic excitations using the dynamic fuzzy WNN model. The model does not require complete measurements of the dynamic responses of the whole structure. A damage evaluation method is proposed based on a power density spectrum method. The multiple signal classification method is employed to compute the pseudospectrum from the structural response time series. The methodology is validated using experimental data obtained for a 38-story concrete test model. It is demonstrated that the WNN model together with the pseudospectrum method is effective for damage detection of highrise buildings based on a small amount of sensed data. A nonlinear control model is developed for active control of highrise three dimensional building structures including geometrical and material nonlinearities, coupling action between lateral and torsional motions, and actuator dynamics. A dynamic fuzzy wavelet neuroemulator is developed for predicting the structural response in futur (open full item for complete abstract)

Doctor of Philosophy (PhD), Ohio University, 2009, Physics and Astronomy (Arts and Sciences)

This dissertation focuses on the study of the dynamics of structural glasses. The presence of dynamical heterogeneity has been invoked to explain the non-exponential nature of relaxation in glassy systems and the presence of anomalies in transport properties near the glass transition. Although recent experiments have provided direct evidence for its presence, the origin of this phenomenon is currently poorly understood. One of its possible theoretical explanations involves the presence of local fluctuations in the time variable. In this work, we test predictions coming from this theoretical explanation. We study fluctuations in the relaxation of structural glasses by means of molecular dynamics simulations of various structural glass models. The focus is mostly on the aging regime, but we also study the equilibrium supercooled regime. For a simple aging Lennard-Jones binary glass former, we find that the probability distributions of local fluctuations collapse for a fixed value of the global correlation C(t, tw). We also find that both the generalized dynamic usceptibility associated with particle density fluctuations and the corresponding correlation length increase as a power of the waiting time. We observe that the generalized susceptibilities and the dynamic correlation length can be scaled and fall onto master curves as functions of C(t, tw). We also analyze data from a structural glass where the interactions between the particles are via the purely repulsive Weeks-Chandler-Anderson potential. We compare the behavior of fluctuations in the aging and equilibrium regimes. We find that the dynamic susceptibility grows and saturates as the system reaches equilibrium and that the distributions of local fluctuations related to the aging and equilibrium regimes collapse with each other and show scaling. The results put a condition on theoretical explanations for dynamical heterogeneity: they should predict that the behavior of the fluctuations is similar in the agi (open full item for complete abstract)

Master of Science (MS), Bowling Green State University, 2012, Geology

Quartz cement formed during diagenesis is the principle cause of porosity and permeability reduction in sandstones and therefore greatly affects reservoir quality. Predictive quartz cement models have provided a basic ability to estimate reservoir quality for quartz-rich rocks under ideal diagenetic conditions. However, examination of more complex, specific diagenetic environments is required to improve the accuracy of predictive models applied to unconventional hydrocarbon reservoirs. Our experimental and numerical approach to this problem has examined quartz cementation processes by: 1) assessing the feasibility of relatively low temperature hydrothermal flow-through experiments for investigating silica dissolution, transport, and precipitation processes during diagenesis in active fluid flow environments, and 2) to assessing the effect of grain size and sorting on the rate of quartz cementation and corresponding pore space evolution in sandstones under static hydrothermal conditions. Hydrothermal flow-through results indicate that small amounts of new quartz cement can be generated in less than 10 days at relatively low temperatures when compared to previous experimental work. Results obtained from static hydrothermal experiments indicate that grain size and sorting effect both the rate of quartz cementation in our experiments and corresponding pore space evolution. The surface area normalized rate is observed to decrease more rapidly in fine grain size experiments when compared to coarse grain size experiments. Additionally, pore space analysis of both experimental and modeled results indicates that while all grain size fractions rapidly converge on similar total porosity values the 2D connectivity of porosity varies markedly as a function of grain size and sorting.

Doctor of Philosophy, Case Western Reserve University, 2013, EECS - Computer and Information Sciences

It has been shown that large scale genomic structural variants (SV) are closely associated with disease onset. In particular, the presence of these abnormalities may contribute to the onset and susceptibility of cancer through various mechanisms. Knowing the location and type of these variants can assist medical researchers in making insights into methods for diagnosis and treatment. It is also important to develop efficient methods to locate these variants. This thesis presents several algorithms for identifying and characterizing structural variants using array comparative genomic hybridization (aCGH) and high throughput next-generation sequencing (NGS) platforms. The aCGH-based algorithm (CGH-Triangulator) is considerably faster than a state-of-the-art method for identifying change points in aCGH data, and it has greater prediction power on datasets with low-to-moderate levels of noise. The NGS-based algorithms include methods to identify basic SV types, including deletions, inversions, translocations, and tandem repeats. They also include methods to identify double minute chromosomes, which are more complex structural variants. These methods use a hybrid strategy to identify variants at base-pair resolution. Using two primary prostate cancer datasets and simulated datasets, we compared our methods to previously published NGS algorithms. Overall, our methods had favorable performance with respect to breakpoint prediction accuracy, sensitivity, and specificity. In particular, this thesis presents one of the first attempts to algorithmically detect double minute chromosomes, which are complex rearrangements that are present in many cancers.

Doctor of Philosophy, Miami University, 2025, Chemistry and Biochemistry

The purpose of this dissertation is to observe physical properties of molecules in solution. Structural dynamics information is provided for three systems: a cobalt-centered complex converting between three coordination states at low temperature, a lanthanide complex adopting two NMR-active enantiomers according to identity of the metal center, and a chaperone protein interaction determining binding symmetry. These systems are investigated using a variety of analytical methods – including crystallography, NMR spectroscopy, Density Functional Theory calculations, and Molecular Dynamics simulations. Chapter 2 examines the dynamics of TpPh,Me Cobalt (II) NO3 (TpPh,MeCoNO3) [TpPh,Me = tris-3-phenyl-5-methylpyrazolylborate]. Solid-state XRD structure of TpPh,MeCoNO3 is presented for the first time, showing a five-coordinate Co (II) complex with TpPh,Me with NO3 bound as a bidentate ligand. Variable temperature NMR spectra are complicated at low temperature, with signals coalescing as temperature is increased. The high temperature NMR spectra indicate a four-coordinate structure above room temperature. Spectral analysis demonstrates the TpPh,MeCoNO3 complex occupies three concurrent structures at low temperatures. These three structures are analyzed using Density Functional Theory (DFT) calculations of four- and five-coordinate structures generated in silica from the crystal structure. In Chapter 3, the conformational interconversion of two NMR-active LnDOTAM structures (Ln=La-Lu; DOTAM=1,4,7,10-tetrakis(acetamido)-1,4,7,10-tetraaza-cyclododecane) are examined using a series of 13 lanthanide ions. Variable-temperature 1H NMR spectra demonstrate the concentration of the two identifiable conformations in solution depends on the identity of the metal ion. At low temperature, early LnDOTAM (Ce-Nd) have a high concentration of the twisted square antiprismatic geometry (TSAP), and later LnDOTAM (Sm, Eu, Tb-Yb) have a higher concentration of the square antiprismatic geomet (open full item for complete abstract)

PhD, University of Cincinnati, 2024, Education, Criminal Justice, and Human Services: Counselor Education

This dissertation reviewed the literature on alcohol use disorder (AUD) recovery definitions, prevalence, pathways, and psychometrics, identifying gaps, including a lack of clarity about the dimensionality of recovery and whether its domains have the same meaning between those experiencing who have and have not experienced AUD as well as between those using and not using services (e.g., formal treatment or 12 steps). The predictive validity of AUD recovery domains over more extended periods and across development is also largely unknown. Here, I used public data from the National Longitudinal Study of Adolescent to Adult Health (n = 4,512) to (a) determine the structure of biopsychosocial domains included in definitions and measures of AUD recovery during young adulthood, (b) test this structure for measurement invariance across service utilization and non-service utilization as well as alcohol abuse and non-abuse subgroups, and (c) test whether AUD recovery domains exhibit predictive validity over 6 years. Exploratory structural equation modeling (ESEM) showed an eight-factor solution fit the data well (CFI = .968, RMSEA = .023). Bifactor ESEM showed evidence against a global recovery factor (e.g., common variance [ECVG = .146] and omega hierarchical [?h = .027]). Scalar invariance for the eight-factor model held across alcohol abuse and non-abuse (CFI = .973; RMSEA = .023) as well as service utilization and non-service utilization (CFI = .972; RMSEA = .021) subgroups, suggesting AUD recovery domains have the same meaning across them and scores may be compared. Longitudinal structural equation modeling showed that Wave III daily activities and physical health (βs = -.068 to -.134), parental support and connection (βs = -.059 to -.100), and religiosity and spirituality (βs = -.053 to -.100) significantly forecasted decreases in many AUD indicators over 6 years; whereas risky behavior and violence, psychological illness, self-esteem, and economic deprivation did not. (open full item for complete abstract)

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

A major concern in the oil and gas industry is erosion corrosion which can cause catastrophic failure in pipelines. To monitor and prevent this failure, networks of acoustic emission sensors have been installed on pipelines to detect the presence of abrasive particles in the fluid flow. These abrasive particles damage the inside walls of the pipes through high-velocity impact. It would be advantageous to utilize the ultrasonic transducers in these existing monitoring systems to measure wall thickness. Two main roadblocks exist in utilizing these transducers for wall thickness measurements. First, these systems do not have a way of providing the typical excitation needed for ultrasonic measurements. To combat this issue, this thesis explores two different passive approaches: one that requires no purposeful excitation and another that utilizes acoustic emission from particle impact and fluid flow within the pipe. The second challenge in measuring wall thickness using existing transducers is the frequency range of these transducers which is much lower than what is typically used for ultrasonic time-of-flight thickness measurements. To address this problem, this thesis explores the sensitivity of transducers to the upper limits of their frequency range using a time-of-flight method. Additionally, for thinner-walled components which would require even higher frequencies, a resonant ultrasound spectroscopy method is explored. Experimental measurements using the different measurement modalities and passive excitation approaches are shown using multiple transducers. Several of the experimental combinations tested show good agreement with active measurements and show promise in determining wall thickness.

Doctor of Philosophy, Case Western Reserve University, 2025, Management

This dissertation explores the persistent gender gap in partnerships at Big Four public accounting firms, employing a mixed-methods approach to examine both individual experiences and career trajectories. Despite women entering the profession at equal rates to men, only about 23% of partners are women. This study aims to understand why this disparity persists and how career paths influence partnership attainment. Study 1 utilized qualitative interviews with 11 female advisory partners to investigate their lived experiences in reaching partnership. Findings revealed a common internal mental model for evaluating the partnership career path, consisting of three iterative phases: partner inquiry, developing partner behaviors, and solidifying a partner identity. This process highlights the importance of personal reflection and identity development in pursuing partnership. Study 2 employed Optimal Matching Analysis to quantitatively examine the career trajectories of 312 partners (159 women, 153 men) across audit, tax, and consulting functions. Results showed no significant gender differences in time to partnership or career transitions. However, distinct patterns emerged among business units, with audit and tax partners typically achieving partnership faster than consulting partners. Notably, only about 40% of partners followed traditional linear career paths within their initial function. The integrated analysis of these findings revealed a complex interplay between individual mindsets and organizational structures in shaping the path to partnership. Key elements include early career goals, professional socialization, self-managed career progression moderated by sponsorship, and making a strong business case for partnership. This analysis highlighted that while women and men who make partner do so in similar timeframes, the journey to partnership involves navigating psychological transitions, organizational changes, and social dynamics that (open full item for complete abstract)

Doctor of Education , University of Dayton, 2024, Educational Administration

This study examined the current sick leave policies in a K-12 education organization. The access to sick leave and the allotted days available have resulted in high absenteeism among elementary teachers. This study's qualitative-focused approach included participants who provided their perspectives on the current policies. The findings showed that the current policies are unfavorable, impacting student learning. As an employee of a school board that oversees the medical absences of elementary teachers, my action plan consists of presenting these findings to my organization and further researching and investing in accessible resources for teachers in hopes of creating better attendance throughout the organization. I desire the board of directors to recognize the financial impact of the sick leave policies on the organization and look at the absence trends from when the current sick leave plan was implemented, compared to the previous one. My action plan aims to promote an idea regarding resources for teachers as they tend to take on other tasks that go beyond their teaching roles, which, respectfully, they do not have sufficient background to deal with.

Master of Science (M.S.), University of Dayton, 2024, Mechanical Engineering

This thesis presents a method for estimating the weight of a novel concept aircraft designed with a bio-inspired rotating empennage (BIRE). The selected platform for the BIRE concept is a single-engine, supersonic, tactical aircraft similar to the F-16 Fighting Falcon. The agile, tailless aircraft is able to tilt its horizontal stabilizers to provide yaw stability. To provide the unusual motion, unique mechanisms and structures are required. Sizing models of the mechanical system for the BIRE were generated using first-order principles and component vendor information. The weight estimator uses aerodynamic and inertial loads and physics-based component reliability constraints. An optimization was implemented to select component alternatives and dimensions that minimize the weight. A MATLAB script was written as part of this research to efficiently perform the optimization. Traditional weight estimation methods use empirical estimates that are not accurate when applied to novel concepts. Numerical methods, such as finite element analysis, are too complex to include in trade studies. This mid-fidelity weight estimation has been developed specifically for the BIRE platform but consists of sub-models that can be applied to other mechanical components such as shafts, bearings, gears, and actuators.