Master of Science in Aerospace Systems Engineering (MSASE), Wright State University, 2024, Mechanical Engineering

The development of high order numerical schemes has been instrumental in advancing computational fluid dynamics (CFD), particularly for applications requiring high resolution of discontinuities and complex flow phenomena prevalent in high-speed flows. This thesis introduces the Pade-ENO scheme, a high-order method that integrates Essentially Non-Oscillatory (ENO) techniques with compact Pade stencils to achieve superior accuracy, up to 7th order, while maintaining stability in harsh environments. The scheme's performance is evaluated through benchmark tests, including the advection equation, Burgers' equation, and the Euler equations. For high Mach number flows, such as the sod shock tube the Pade-ENO method demonstrates its ability to resolve sharp gradients and discontinuities with no smoothing required. Numerical results highlight the scheme's robustness and its potential as a powerful tool for high-speed aerodynamic simulations, paving the way for future advancements in CFD modeling.

Doctor of Philosophy, The Ohio State University, 2024, Industrial and Systems Engineering

Sociotechnical systems in safety-critical domains are distributed and contain interdependencies between the different elements, including human and automated roles that need to coordinate and synchronize their activities with dynamic events in the environment. The advancement of technology and the introduction of machines capable of acting at a higher level of autonomy has increased the complexity of such Distributed Work Systems (DWSs). An envisioned DWS is described by a set of static paper-based documents and will be deployed in the next few years. The short-range low-altitude air mobility system is one very good example of an envisioned DWS. Interactions between human and automated roles and their environment are dynamic, evolve, and change over time, causing emergent effects like taskload peaks and coordination breakdowns. A well-designed DWS will be able to keep pace with the work environment dynamics (like the dynamics of aircraft governed by laws of flight in a short-range low-altitude air mobility system) and succeed in responding to the disturbance. This creates the need to understand the dynamics of envisioned DWS, such as how a DWS performs in high-paced situations like anomaly response. Assessing the feasibility and robustness of an envisioned DWS comes with challenges: the physical system does not yet exist, its design and operations are often underspecified, and multiple versions may exist within a designer community about what future operations will look like. Therefore, as a part of this dissertation, an exploratory early-stage computational modeling and simulation technique is described and demonstrated to evaluate an envisioned DWS. Using functional modeling and computational simulation capabilities, the dissertation shows a technique that can help evaluate envisioned DWS by discovering things that are not uncovered by traditional normative simulations. The primary advantage of the technique is the ability to evaluate the dynamics of work in (open full item for complete abstract)

Doctor of Philosophy, University of Akron, 2023, Biology

Vision is a crucial sense. Sight enables us to navigate and interact with our surroundings. Our environments contain an almost infinite variety of shapes, contours, and colors. Yet we only have a finite number of cells, and those cells consume a finite amount of energy. Vision enables us to effectively interact with these complex environments despite these limitations. In order for retinal development to be completed, light-evoked activity is required. Various synapses in the inner retina also must be established in order for these signals to propagate further. Only after these things occur can the visual system function at full capacity. Because of this much of the aims center around timing of electrophysiological activity in the retina. The first aim of this dissertation will be to establish a timeline for which photoreceptors (rods and cones), and bipolar cells are capable of generating and transmitting light evoked activity. Disruption of this light evoked activity can result in residual immature and can result in visual deficits. The second aim of this dissertation will be to analyze a model of X-linked retinoschisis at timepoints before eye-opening and determine how cells physiological output is reduced by this disease. The transition and increasing influence of GABA occurs around the same time we have determined bipolar cells become capable of light-evoked activity. The final aim of this dissertation is to describe a computational model of the generation and propagation of retinal waves from the SAC. Together each aim is directed at synaptogenesis at and around eye-opening. How does the presence of light evoked activity alter the physiological output of electrochemical signals at the first synapse and beyond, and how do these signals influence early synaptic refinement due to retinal waves?

Doctor of Philosophy, Case Western Reserve University, 2024, Biomedical Engineering

In the pursuit of enhancing prognostic methodologies for glomerular diseases, this dissertation introduces a comprehensive approach termed "deep phenotyping," which synergistically integrates artificial intelligence (AI) capabilities with engineered techniques to revolutionize outcome prediction. The primary objective is to harness the potential of AI to perform rigorous quality control on data, identify distinct tissue compartments, and subsequently extract features for downstream analyses that identifies the image biomarkers with strong associations to disease outcomes. The research journey commences by establishing a comprehensive machine learning prognosis pipeline rooted in deep phenotyping principles. Tailored specifically to glomerular diseases and utilizing digital kidney pathology images, this pipeline addresses the need for robust quality control in deep learning processes. It encompasses a multifaceted exploration, encompassing the impact of image compression artifacts on deep learning performance, the revelation of batch effects caused by digital pathology-related artifacts in multi-site repositories, and the introduction of a novel computer-aided quantitative quality control pipeline. Following this foundation, the dissertation advances to the creation and evaluation of intricate deep learning segmentation models. These models are developed to accommodate a range of kidney histologic primitives and stains commonly used in kidney pathology. The refined segmentation toolkit leads to the extraction of features, with a particular focus on peritubular capillaries (PTCs) due to their implications in kidney disease outcomes. This hierarchical feature extraction spans from fundamental attributes to complex aspects of PTCs. The subsequent sections delve into the investigation of the independent prognostic value of cortical PTCs and their interplay with interstitial fibrosis and tubular atrophy (IFTA). Machine learning prognostic models are built upon this PTC (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2020, Linguistics

This thesis treats a major challenge for current state-of-the-art natural language processing (NLP) pipelines: morphologically rich languages where many inflected forms or weak form--meaning correspondence lead to data sparsity and noise. For example, if the lexeme TEACHER occurs the same number of times in an English text and an Arabic text, those occurrences will be spread over just four forms in English, teacher, teacher's, teachers' and teachers, versus numerous forms in Arabic, leading to more low frequency and out-of-vocabulary forms at test time. Furthermore, while the +s suffix of teachers is highly predictable, there is significant entropy involved in predicting how pluralization will realize in Arabic, which can cause models to be noisy. That said, the particular means of realizing pluralization (among other properties) can be informative in Arabic, as the +wn in mdrswn, 'teachers' not only indicates plurality, but also that the referent is human. To address data sparsity and noise from morphological richness, I propose some practical means of inducing morphological information and/or incorporating morphological information in preprocessing steps or model components, depending on the task at hand. The goals of this intervention are twofold. First, I aim to link variant inflections of the same lexeme to reduce sparsity. Second, I aim to mitigate noise by identifying morphosyntactic properties encoded in complex inflections like mdrswn and leverage them to help models interpret low frequency or out-of-vocabulary forms. To be practical, morphological modeling should be maximally language agnostic, i.e., portable to new languages or domains with minimal human effort, and maximally cheap, i.e., in terms of the amount/cost of required manual supervision. Thus, I explore morphological modeling strategies and morphological resource creation, progressing toward more language agnostic solutions requiring less supervision over the course of this thesis. To (open full item for complete abstract)

Master of Science, Miami University, 2020, Mathematics

This thesis is to provide an overview of Topological Data Analysis (TDA) for the advanced undergraduate or early graduate student. This thesis assumes familiarity with basic graph theory, point-set topology, and introductory algebraic topology. Furthermore, this thesis will study phylogenetic relationship of NA gene in various Influenza A strains and determine if horizontal evolution has occurred with the strains under consideration. Furthermore, this thesis serves as a verification to the results published in a paper in 2013, in which, TDA was used to study influenza A HA and NA.

Master of Science, The Ohio State University, 2020, Public Health

Legionella pneumophila (L. pneumophila) has become a significant public health issue due to its growth in water distribution systems. In natural water systems L. pneumophila is often found in relatively low concentrations. However, in distribution systems it is able to thrive through the use of biofilms and invasion of larger host organisms such as protozoa. Additionally, the altered microbial ecology of water distribution systems seems to play a role in facilitating its ability to proliferate and persist. L. pneumophila can cause respiratory infections when contaminated water is aerosolized as it exits from distribution or premise plumbing systems and is then inhaled. Research has shown that some tap water organisms can exhibit inhibitory or commensal effects on L. pneumophila. Understanding more about these relationships will allow us to better estimate L. pneumophila concentrations in premise plumbing. A systematic literature review was conducted to gather relevant information regarding the interactions of L. pneumophila with tap water biofilm microbial ecology. From the resulting information a stochastic model has been produced to simulate (1) these interactions within a tap water biofilm and (2) the inhibitory or commensal effects on L. pneumophila concentrations. The model simulates the interactions of L. pneumophila within a tap water biofilm. These interactions are used to calculate the resulting L. pneumophila concentrations in the biofilm and bulk tap water. Theses concentrations are then used in a quantitative microbial risk analysis (QMRA) of a 15-minute showering event and used to determine the exposure hazard to humans and associated risk of L. pneumophila infection based off this novel ecological modeling method. The models that my method develops are a means of improving the precision of estimates for exposure of bacteria after its growth in premise plumbing. From this, we can better understand how communities of microorganisms in biofilms affect (open full item for complete abstract)

Master of Arts, The Ohio State University, 2019, Psychology

Attention-deficit and hyperactivity disorder (ADHD) is one of the most frequently diagnosed disorders. Nevertheless, phenotypes of ADHD are heterogenous, and remain vaguely defined. For instance, current cognitive test procedures are often inconclusive on the characteristics of ADHD and frequent comorbidities are mostly neglected. This thesis is composed of three parts: The first part describes existing approaches (e.g., theories, ADHD subtypes, comorbidities), as well as empirical findings from current test procedures (e.g., neurocognitive tasks) for ADHD across eight cognitive domains. It will be shown that the findings from these reviews point towards a spectrum of ADHD and comorbidities that often seem beyond the scope of existing studies, because of the nature of the administered test procedure, the type of applied analysis, as well as the pre-categorization of participants. The third part therefore introduces a proposal for measuring a spectrum of not only ADHD, but also comorbidities in a set of test procedures susceptible to identified clinical characteristics. To support these proposals, the second part describes the results from the application of the Ratcliff Diffusion Model to the neurocognitive test performances of an existent clinical dataset (e.g., the MTA study). It will be illustrated that significant differences between controls and ADHD children become apparent, when accounting for gender and medical treatment. Specifically, unmedicated ADHD children seem to take less time for cue retrieval and motor output (smaller Ter), accumulate information at a slower rate (smaller v), and show higher variability in response times. ADHD boys are characterized by a small Ter when interstimulus interval is short, whereas ADHD girls are characterized by an overly conservative decision criterion (large a). Moreover, stimulants not only increase drift rates as suggested by previous studies, but also reduce the gender-specific ADHD characteristics (e.g., small (open full item for complete abstract)

Master of Science, The Ohio State University, 2019, Aero/Astro Engineering

This thesis details aeroelastic response prediction of hoods on automobiles in the wake of a leading vehicle. Such conditions can lead to significant hood vibration due to the unsteady loads caused by vortex shedding. A primary focus is the sensitivity of the aeroelastic response to the aerodynamic modeling fidelity. This is assessed by considering both Reynolds-Averaged Navier-Stokes (RANS) and Detached Eddy Simulation (DES) flow models. The aeroelastic analysis is carried out by coupling a commercial computational Fluid dynamics (CFD) solver (StarCCM+) to a commercial computational structural dynamics (CSD) solver (Abaqus). Two different configurations are considered: 1) sedan-sedan and 2) sedan-SUV. This enables the consideration of both varied geometry and structural stiffness on the aeroelastic response. Comparisons between RANS and DES emphasize the importance of turbulence modeling fidelity in order to capture the unsteadiness of the flow and the vibration response of the hood. These comparisons include analysis of the lift forces, pressure loads on the hood, and Power Spectral Density Analysis (PSD) of the flow in the region between the two vehicles. As expected, DES predicts higher frequency content and significantly higher turbulence levels than RANS. Both the sedan and SUV hoods are sensitive to the turbulent fluctuations predicted by DES. The increased levels of turbulence result in up to 40 - 60% higher maximum peak to peak deformation and the excitation of a torsional mode of the hood for the sedan-sedan case. For the more flexible hood configuration (sedan - SUV), these differences are even higher, with maximum peak to peak deformations of up to 17 – 71% higher than the RANS solution.

MS, University of Cincinnati, 2016, Engineering and Applied Science: Aerospace Engineering

This thesis details a computational investigation of tone noise generated from a booster(low-pressure compressor) in a fan test rig. The computational study consisted of sets of time-linearized Navier-Stokes simulations in the booster region to investigate the blade-wake interactions that act as the primary noise-generating mechanism for the booster blade-passing frequency and harmonics. An acoustic test database existed with data at several operating points for the fan test rig that was used to compare against the predicted noise data from the computational study. It is shown that the computational methodology is able to capture trends in sound power for the 1st and 2nd booster tones along the operating line for the rig. It is also shown that the computational study underpredicts one of the tones at low power and is not able to capture a peak in the data at the Cutback condition. Further investigation of this type is warranted to quantify the source of discrepancies between the computational and experimental data as the reflected transmisison of sound off the fan through the bypass duct was not accounted for in this study.

Doctor of Philosophy, University of Toledo, 2015, Mechanical Engineering

External Verification Analysis (EVA), a new approach to verifying unsteady partial differential equation codes, is presented. After a review of the relevant code verification literature, the mathematical foundation and solution method of the EVA tool is discussed in detail. The implementation of the EVA tool itself is verified through an independent Python program. A procedure for code verification with the EVA tool is described and then applied to the three-dimensional form of a high-order non-linear computational aeroacoustics code.

Master of Science (M.S.), University of Dayton, 2015, Materials Engineering

Modern computational tools are permitting realistic complex 2-dimensional(2D) and 3-dimensional(3D) geometry structures, material state properties, and multi-physics realism to be included into Computational Nondestructive Evaluation Models (CNDE), which allows a direct comparison of local material property statistics with sensing model results. The goal of this research was to develop and demonstrate ultrasound model-assisted nondestructive evaluation (NDE) methods for characterizing and mapping 2D/3D microstructures. A framework was created using the concept of Integrated Computational Materials Engineering (ICME) that allows for the incorporation of real material data sets to be described explicitly within computational NDE models. The Framework was tested using real and synthetically generated 2D/3D material data sets, where material state properties were characterized and correlated with NDE model sensing results. The implications of research are that the development of the framework is now allowing for studies to observe and understand complex elastic wave scattering due to polycrystalline microstructures.

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

Helicopters and other Vertical Take-Off or Landing (VTOL) vehicles exhibit an interesting combination of structural dynamic and aerodynamic phenomena which together drive the rotor performance. The combination of factors involved make simulating the rotor a challenging and multidisciplinary effort, and one which is still an active area of interest in the industry because of the money and time it could save during design. Modern tools allow the prediction of rotorcraft physics from first principles. Analysis of the rotor system with this level of accuracy provides the understanding necessary to improve its performance. There has historically been a divide between the comprehensive codes which perform aeroelastic rotor simulations using simplified aerodynamic models, and the very computationally intensive Navier-Stokes Computational Fluid Dynamics (CFD) solvers. As computer resources become more available, efforts have been made to replace the simplified aerodynamics of the comprehensive codes with the more accurate results from a CFD code. The objective of this work is to perform aeroelastic rotorcraft analysis using first-principles simulations for both fluids and structural predictions using tools available at the University of Toledo. Two separate codes are coupled together in both loose coupling (data exchange on a periodic interval) and tight coupling (data exchange each time step) schemes. To allow the coupling to be carried out in a reliable and efficient way, a Fluid-Structure Interaction code was developed which automatically performs primary functions of loose and tight coupling procedures. Flow phenomena such as transonics, dynamic stall, locally reversed flow on a blade, and Blade-Vortex Interaction (BVI) were simulated in this work. Results of the analysis show aerodynamic load improvement due to the inclusion of the CFD-based airloads in the structural dynamics analysis of the Computational Structural Dynamics (CSD) code. Improvements came (open full item for complete abstract)

MS, University of Cincinnati, 2004, Engineering : Computer Science

With advancing developments of artificial intelligence, humor researchers have begun to look at approaches for computational humor. Although there appears to be no complete computational model for recognizing verbally expressed humor, it may be possible to recognize jokes based on statistical language recognition techniques. This is an investigation into computational humor recognition. It considers a restricted set of all possible jokes that have wordplay as a component and examines the limited domain of “Knock Knock” jokes. The method uses Raskin's Theory of Humor for its theoretical foundation. The original phrase and the complimentary wordplay have two different scripts that overlap in the setup of the joke. The algorithm deployed learns statistical patterns of text in N-grams and provides a heuristic focus for a location of where wordplay may or may not occur. It uses a wordplay generator to produce an utterance that is similar in pronunciation to a given word, and the wordplay recognizer determines if the utterance is valid by using N-gram. Once a possible wordplay is discovered, a joke recognizer determines if a found wordplay transforms the text into a joke.

Master of Science in Mechanical Engineering, University of Toledo, 2010, College of Engineering

As Computational Aeroacoustics (CAA) codes become more complex andwidely used, robust Verification of such codes becomes more and more important. Recently, Hixon et al. proposed a variation of the Method of Manufactured Solutions of Roache especially suited for Verifying unsteady CFD and CAA codes that does not require the generation of source terms or any modification of the code being Verified. This work will present the development of the External Verification Analysis (EVA) method and the results of its application to some popular model equations of CFD/CAA and a high-order nonlinear CAA code.

Doctor of Philosophy, The Ohio State University, 2012, Computer Science and Engineering

Scalar functions are virtually ubiquitous in scientific research. A vast amount of research has been conducted in visualization and exploration of low-dimensional data during the last few decades, but adapting these techniques to high-dimensional, topologically-complex data remains challenging. Traditional metric-preserving dimensionality reduction techniques suffer when the intrinsic dimension of data is high, as the metric cannot generally survive projection into low dimensions. The metric distortion can be arbitrarily large, and preservation of topological structure is not guaranteed, resulting in a misleading view of the data. When preservation of geometry is not possible, topological analysis provides a promising alternative. As an example, simplicial homology characterizes the structure of a topological space (i.e. a simplicial complex) via its intrinsic topological features of various dimensions. Unfortunately, this information can be abstract and difficult to comprehend. The ranks of these homology groups (the Betti numbers) offer a simpler, albeit coarse, interpretation as the number of voids of each dimension. In high dimensions, these approaches suffer from exponential time complexity, which can render them impractical for use with real data. In light of these difficulties, we turn to an alternative type of topological characterization. We investigate the Reeb graph as a visualization and analysis tool for such complex data. The Reeb graph captures the topology of the set of level sets of a scalar function, providing a simple, intuitive, and informative topological representation. We present the first sub-quadratic expected time algorithm for computing the Reeb graph of an arbitrary simplicial complex, opening up the possibility of using the Reeb graph as a tool for understanding high-dimensional data. While the Reeb graph effectively captures some topological structure, it is still somewhat terse. The Morse-Smale complex summarizes a scalar function by b (open full item for complete abstract)

Master of Science, The Ohio State University, 2011, Mechanical Engineering

This thesis reports the results of my M.S. research work about applying the space-time Conservation Element and Solution Element (CESE) method to computational aero- and hydro- acoustics. I am concerned with numerical solutions of nonlinear fluid equations for wave propagation in low-speed flows in air and in water. The case simulated is flow over cylinder. For air flows, three different Reynolds numbers are considered: 89000, 46000, and 22000. Results compared favorably with previously published numerical and experimental results. For water flow over a cylinder at Re = 89000 is carried out and the generated noises are predicted.

Doctor of Philosophy, The Ohio State University, 2002, Linguistics

Lexicalized noun phrases are noun phrases that function as words. In English, lexicalized noun phrases are often realized as noun-noun compounds such as theater ticket and garbage man, or as adjective-noun phrases such as black market and high school. In specialized or technical subjects, phrases such as urban planning , air traffic control , highway engineering and combinatorial mathematics are conventional names for concepts that are just as important as single-word terms such as adsorbents , hydrology , or aerodynamics . But despite the fact that lexicalized noun phrases represent useful vocabulary and are cited in dictionaries, thesauri and book indexes, the traditional linguistic literature has failed to identify consistent and categorical formal criteria for identifying them. This study develops and evaluates a linguistically natural computational method for recognizing lexicalized noun phrases in a large corpus of English-language engineering text by synthesizing the insights of studies in traditional linguistics and computational linguists. From the scholarship in theoretical linguistics, the analysis adopts the perspective that lexicalized noun phrases represent the names of concepts that are important to a community of speakers and have survived a single context of use. Theoretical linguists have also proposed diagnostic tests for identifying lexicalized noun phrases, many of which can be formalized in a computational study. From the scholarship in computational linguistics, the analysis incorporates the view that a linguistic investigation can be extended and verified by processing relevant evidence from a corpus of text, which can be evaluated using mathematical models that do not require categorical input. In a engineering text, a small set of linguistic contexts, including professor of , department of or studies in , yields long lists of lexicalized noun phrases, including public safety , abstract state machines , complex systems , computer graphics , (open full item for complete abstract)

Master of Science in Chemistry, Youngstown State University, 2012, Department of Chemistry

Computational studies on thermodynamics of dismutation of superoxide anion radicals (O2-) to hydrogen peroxide and molecular oxygen was conducted with various theoretical models using a variety of basis sets. The computational models include semi-empirical, Hartree-Fock and density functional contained in the Spartan 2004* program suite. The catalytic role of Cu2+ in the superoxide dismutase enzyme was reflected by observing its effect on reducing the activation energies. Activation energies were computed for various transition states complex involved in concerted, two step and three step mechanisms catalyzed by [Cu(NH3)4(H2O)2]2+. Based on this analysis, mechanisms which include the peroxy radical (.OOH) are less favored than those which include neutral O2 in a transition state complex, or involve both H+ donors and a superoxide (O2-) in a single step.

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

In industries such as mining and powder handling, workers are at risk of exposure to inhaling particulates as the powder can get aerosolized in their work environments. It is critical to characterize the dustiness or propensity of powders to get aerosolized to quantify workers' health risks. The Venturi Dustiness Tester (VDT) is widely used for this purpose. The aerosolization process in this device starts at the powder holding tube, where a dome or hill of powder is exposed to very high flow rate and the aerosol gets sucked into the measurement chamber where it is sampled for dustiness characterization. The process of powder hill aerosolization occurring in VDT is very complex as the obstruction caused by the dome leads to vortex shedding and the shape of the hill changes with aerosolization. To keep the problem tractable, a simplified model problem of flow over a solid hemisphere attached to a horizontal substrate in a rectangular duct is analyzed in this thesis. While this model does not account for changing shape of the hill during the aerosolization process, flow features like vortex shedding and their effect of shear and lift forces acting on the dome surface are captured. This information will be useful in understanding how particulate in a powder hill are likely to be affected by the flow. The flow dynamics in the simplified configuration were explored for different flow speeds, including creeping flow (Re<<1), laminar flow, and turbulent flow using computational fluid dynamics techniques. To obtain the inlet velocity profile to provide the inlet boundary condition for the unsteady simulations of flow over the solid dome, a set of steady-state empty duct simulations were performed first. A grid convergence study was carried out at Re = 1000 to establish grid-independent results for the unsteady simulations. The optimized grid was then used for all Reynolds numbers. In the creeping flow regime, the flow was found to be symmetric around the hemisphere as t (open full item for complete abstract)