Theses and Dissertations

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Conceptual, Trajectory-Based Structural Sizing Method for Hypersonic Glide Vehicles

(Georgia Institute of Technology, 2024-08-20) Gulan, Anna Elizabeth

In recent years, interest in hypersonic vehicles has rapidly developed resulting in an increase in hypersonic research and funding. This push is driven by the anticipation of enhanced mission capabilities. However, hypersonic vehicles pose unique challenges due to complex flow phenomena and extreme environmental conditions. As vehicles travel at hypersonic speed they encounter shock layers, strong entropy layers, viscous interactions, and high temperature flow. Additionally, they experience an intense environment which creates high dynamic pressure, heating loads, and maneuver loads resulting in significant challenges. Among these challenges thermal and mass sensitivity stand out. The rate of heat generation increases exponentially with velocity causing vehicle skins to reach temperatures exceeding 3500 degrees Fahrenheit. This challenge requires a deep understanding of thermal protection systems and the effect of temperature on structural materials. Additionally, high speed vehicles tend to be sensitive to mass. Typically, a lower mass vehicle can have benefits of having a lower production cost, rapid development, and improved performance. The structural weight contributes a significant portion of the vehicle’s throw-weight, emphasizing the need for a better understanding of weight sensitivities. The scope of this project focuses specifically on the conceptual design phase. The conceptual design phase is an iterative process which establishes preliminary requirements, creates a conceptual sketch, performs first-order sizing to estimate the weight, arranges the internal subsystem layout, and performs early-phase mission analysis. Improving the accuracy of conceptual sizing tools can expand the design space for optimization and support the development of preliminary requirements. There are a few primary considerations when performing structural sizing. First, the structure needs to be sized to support the changing flight loads throughout the trajectory. The primary loads include buckling from both bending moment and axial stress, aerodynamic loads which derived into normal and axial forces, maneuver loads which cause a bending moment, and thermal loads. The structural material is also crucial in sizing as it dictates the strength properties, manufacturability, cost, and maximum allowable operating temperature. Due to hypersonics intense heating environment, vehicles face a challenge in the impact of the temperature on material strength properties. To conserve material integrity a thermal protection system (TPS) will be needed. Current conceptual phase practice relies on historical regressions to estimate both the vehicle launch weight and the structural weight. These regressions are based off historical missions and the volume estimation from the conceptual sketch. While these regressions provide an early phase size estimate, they lack mission specific parameters, loads assessment, and optimization opportunities. The process presented in this paper will discuss how the implementation of a trajectory-based structural sizing tool could increase early-phase accuracy and support the development of requirements. This structural sizing tool would augment preexisting modular sizing tools to interact with geometry, aerothermal, and mission analysis. The use of an analytical structural module will increase traceability and accuracy by referring to specific aerothermal and mission parameters while assisting in trade studies to compare design trades. This background leads us to the overarching research question: How can we inform requirements and implement traceability into early-phase structural sizing? This multi-faceted question will be divided into two related research questions. The first research question is: How can we identify the primary loading condition and how it relates to the trajectory? Existing sizing regressions lack background context and specificity to the desired mission. Through the introduction of a trajectory-based sizing tool we identified the impact of trajectory on the loading and quantified the effect of perturbing load distribution. This experiment required the introduction of an analytical model to identify what the primary load condition is, at what point the peak load occurs, and how the trajectory relates to the peak load. This experiment validated a process to increase confidence in early-phase weight estimates. After development of a design of experiments (DOE) and identification of existing trends, the previous claims were substantiated. It showed that the primary loading conditions were external pressure and buckling due to the bending moment of which aligned with the presence of a vertical maneuver such as a pull-up or dive. The implementation of a bank maneuver provided minimal differences to this trend. This research not only validated a trajectory-based sizing method but will also provides a unique opportunity to assess the relationship between the trajectory and the structure and develop additional design freedom to explore this optimization. The second research question is: How can we identify the impact of mission parameters on structural sizing. This research question was separated into two following questions: 1. How do initial trajectory parameters affect structural sizing? 2. What is the relationship between operating skin temperature and structural sizing? Both questions seek to explore the effect of mission parameters on structural loads thus providing support to mission constraints and subsystem co-design. These questions utilized the analytical structural sizing tool along with a DOE to identify trajectory-structural trends and quantify the effect of temperature on structural mass. After evaluation, a well-validated model was created and the effect of initial height, velocity, and flight path angle, terminal velocity and flight path angle, and horizontal range was compared to structural thickness. The results showed that the structural thickness was sensitive to all parameters but especially to initial velocity, terminal flight path angle, and range. These trends will provide additional information to the engineer early in the design phase to assist in preliminary requirement development and design. The sensitivity of structural mass to temperature was also assessed. The temperature proved to have an exponential effect on the structural mass. This work will support informed thermal constraint derivation as well as identification of optimization opportunities between TPS and structure. This research explored how we can introduce traceability into conceptual structural sizing, support requirement derivation, and explore optimization opportunities. The effect of load distribution, trajectory, and temperature on structural sizing was quantified and the primary loading conditions were identified. This process will expand engineers’ early-phase knowledge and allow for informed decisions.

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Design guidance towards enhanced ophthalmological and rehabilitation communication with patients

(Georgia Institute of Technology, 2025-01-10) Kim, Dahee Sophie

Vision rehabilitation is essential for helping Blind or Low Vision (BLV) individuals regain independence and navigate daily life. However, current ophthalmological care often relies on visually oriented, clinician-centered communication methods, creating significant barriers for BLV patients to access and understand health information. Accessible communication is critical for patient-centered care, yet little research has explored ophthalmologists’ expectations (predictions, desires, tolerances, and perceived rights), training, and familiarity regarding inclusive communication practices. This study investigates these gaps through a mixed-methods approach, integrating surveys, community engagement, and design probe deployment to examine how ophthalmologists perceive and implement novel communication strategies. Findings reveal that ophthalmologists often lack formal training and rely on family-mediated communication and simplified strategies, which limit BLV patients’ autonomy and effective information delivery. Although clinicians try to adapt to patients’ needs, unfamiliarity with non-visual methods and time constraints hinder consistent communication. This study proposes design criteria for curricula, training materials, and technology-enhanced products that prioritize accessibility, privacy, multilingual support, and durability. Ultimately, this thesis contributes a framework for understanding “modalities of care” that move beyond information delivery to address the complex dynamics of equitable, patient-centered doctor-patient relationships.

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Scanning Probe Studies of One and Two Dimensional Organic Polymers

(Georgia Institute of Technology, 2024-12-13) Murali, Harshavardhan

This document explores the synthesis and characterization of one and two-dimensional organic materials through a combination of surface-assisted chemical synthesis and characterization techniques. The first part of the thesis focuses on the on-surface synthesis and characterization of a two-dimensional heterotriangulene based Covalent Organic Framework (COF). We characterize the incorporation of atomic hydrogen as a tool to modulate the in-situ growth in Ultra-High Vacuum (UHV), using the dimethylmethylene-bridged triphenylamine (DTPA) COF. Scanning Tunneling Microscopy (STM) and Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) revealed insights into the structural growth properties of these materials. Semiempirical calculations were performed to complement the experimental Scanning Tunneling Spectroscopy (STS) data and computational Density Functional Theory (DFT) calculations to further elucidate the electronic structure. We then describe the synthesis and characterization of donor-acceptor polymers based on a benzobisthiadiazole (BBT) acceptor and dithophene donors on Au(111), theorized to have a freestanding open shell electronic structure, using STM and STS to uncover their properties as synthesized on the surface. We do not observe features that suggest an open shell character, but low temperature STS measurements indicate the presence of a conductance peak near zero bias that appears when picking up monomer molecules. In the final part of the thesis, we present preliminary investigations into imaging porphenes, a class of two-dimensional materials composed of repeating porphyrin units, using STM.

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Aluminumnano-Layersuperconducting Thin Films

(Georgia Institute of Technology, 2024-12-16) Dadkhah, Shohreh

The fascinating properties of superconductors have led to widespread use in applications such as quantum computing, MRI machines, and particle accelerators. However, understanding how factors like material thickness influence these properties remains a key challenge in the field. We focus on investigating the relationship between the thickness of aluminum nanolayers in superconductors and their corresponding resistivity and critical temperature. Aluminum, being a well-characterized low-temperature superconductor, provides an ideal model system for exploring these effects. By systematically varying the thickness of the aluminum films and conducting comprehensive microstructural and electrical characterization, this study aims to elucidate the fundamental mechanisms that govern superconductivity in thin films. The research presented in this thesis not only contributes to the fundamental understanding of superconductivity but also has practical implications for the design and optimization of superconducting materials for technological applications. By advancing our knowledge of how thickness and microstructure affect the superconducting properties of aluminum-based films, this work lays the groundwork for future innovations in both low and high-temperature superconducting technologies.

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Design of Materials Tolerant to Dynamic Tensile Spall Failure

(Georgia Institute of Technology, 2024-12-16) Frawley, Keara G.

Materials tolerant to dynamic tensile or “spall” failure are of interest for applications involving high-velocity impact and blast loading. Metals and polymers generally have favorable responses to such extreme conditions and are therefore useful materials in shock- absorbing applications, such as the automotive industry, body armor, or other protection and shielding devices. The complex stress states and high strain rates involved in events leading to spall failure are typically different from the conditions under which most material testing is conducted to determine mechanical properties. Hence, it has been difficult to predict how spall strength, i.e., resistance to dynamic tensile failure, relates with typical mechanical properties such as hardness, toughness, strength, and moduli. This work focuses on utilizing machine learning (ML) to determine the relationship between these key properties and spall strength, with the goal of developing predictive models and a better understanding of the spall response behavior of metals, alloys, and polymers. Various methods were utilized to generate databases of spall strengths and key properties of metals and polymers through literature surveys and experiments. Sources included peer-reviewed journal articles and gas gun plate-on-plate impact experiments. Data analytic methods, such as the Pearson correlation and the coefficient of determination, were used to correlate the properties to spall strength. The first main result of this work is a model that predicts the spall strength of metals and alloys. The study provides design guidelines for efficiently screening metals based on commonly available mechanical properties that most influence the spall strength values, minimizing reliance on intensive experimental procedures. Furthermore, the model has been extended to predict the spall strength values of a class of complex alloys for which there is limited data available: high entropy alloys (HEAs). The second main result is a database of the spall strengths of 23 unique polymers, either experimentally determined in this work or available in the literature. This database also includes the available mechanical and physical properties of the various polymers, and correlates those to predict the spall strength based on a physically-based energy balance model available in the literature. Additionally, an initial exploration using Molecular Dynamics (MD) calculations was conducted on a simple polymer, polyethylene, to evaluate how this computational approach might perform across a broader range of polymers. By learning more about the influence of material properties on the spall strengths of different classes of materials, we can better understand and predict the spall response of untested materials.

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Data and Computation-efficient Deep Learning for Multi-agent Systems

(Georgia Institute of Technology, 2024-12-10) Kang, Beomseok

The primary goal of this research is to build data and computation-efficient deep learning methods for multi-agent systems. Multi-agent systems are present in a wide range of domains, from physical systems (e.g., molecules, planets) and biological systems (e.g., host-pathogen interactions, neurons) to social systems (e.g., covid-19 spread, games with human players). Although these systems have significant real-world applications, mathematical modeling of their often unknown dynamics is challenging. Deep learning offers a data-driven approach to modeling these systems without requiring extensive domain knowledge. However, collecting sufficient training data is difficult, as these systems evolve over time, and we may not even detect when the underlying dynamics change. Moreover, multi-agent systems are often driven by a large number of agents, making learning and prediction computationally expensive and inefficient. This thesis explores these challenges by developing innovative algorithms and neural network designs that can efficiently learn representations of the spatial arrangement of agents, forecast their trajectories and state transitions, and uncover hidden interaction graphs in unstructured and structured multi-agent systems, considering data and computation constraints.

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Effects of Pd-Addition on the Reaction Pathways of the Aqueous Phase Reforming of Ethanol over Pt/γ-Al2O3

(Georgia Institute of Technology, 2024-12-09) Rettstatt, Michael Jeffrey

Aqueous phase reforming (APR) is a sustainable liquid-phase process that converts biomass into clean hydrogen energy. APR is generally limited to pure feedstocks containing fully oxygenated hydrocarbons of the form CxH2x+2Ox, while functional groups like alkanes are underutilized and require further investigation. This study utilizes Fourier-transform infrared spectroscopy to elucidate the reaction paths of ethanol APR over monometallic and Pd-doped Pt/γ-Al2O3 catalysts. Two reaction paths are identified; both the monometallic and bimetallic catalysts follow both paths to differing degrees. Path 1 is the decarbonylation of ethanol into surface carbon monoxide and a surface methyl species, while Path 2 involves C-C coupling of the acetaldehyde intermediate to form C4 carbonaceous species, resulting in a lower theoretical hydrogen yield and increased catalyst deactivation. Path 1 dominates over Pt/γ-Al2O catalysts, while bimetallic PtPd/γ-Al2O3 catalysts follow Path 2. It was found that co-adsorption of water reduces the formation of C-C coupling products on PtPd/Al2O3, likely due to blockage of Pd sites and geometric effects that prevent adjacent acetaldehyde molecules from coupling. Due to the increased oxophilicity of Pd compared to Pt, water will bind more strongly to Pd and block potential active sites for the undesirable C-C coupling reaction, evidenced by the decrease in intensity of bands around 1575cm-1.

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Empowering Guardians of the Digital Realm: An Analysis of the Current State of Trust & Safety and Opportunities for Advancing the Industry

(Georgia Institute of Technology, 2024-12-11) Swenson, Michael Ray

This work analyzes the challenges faced by Trust & Safety professionals in managing online content moderation and transparency practices. Through 16 semi-structured interviews and participant observation, the authors examined how these professionals navigate complex policy areas, such as harassment, hate speech, misinformation, and legal requests. The study reveals that Trust & Safety workers encounter significant obstacles in moderating non-English content, addressing the needs of children and teens, and adapting to increasing governmental regulations worldwide. Participants emphasized the need for stronger knowledge-sharing programs, open-source tools, and cross-platform collaborations to better tackle online harm. Additionally, participants advocate for enhanced transparency reporting and algorithmic accountability to increase public trust. The study concludes by suggesting that Trust & Safety professionals should play a more active role in shaping regulations that govern online platforms. This work offers both theoretical insights into industry challenges and practical recommendations for advancing the Trust & Safety field through collaboration and knowledge sharing.

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CFD Analysis and Molecular Kinetics in a Supercritical CO2 Circuit Breaker

(Georgia Institute of Technology, 2024-12-08) Metzler, Joy

In this work, the behavior of supercritical carbon dioxide (scCO2) at high pressures is investigated in regards to its arc quenching capabilities to suppress reignition in high-voltage circuit breakers. scCO2 is a favorable replacement for the current SF6 gas, which produces toxic byproducts. SF6 contributes heavily to the global warming crisis, and it is paramount to find a more environmentally conscious alternative. One possibility is scCO2, which has a comparable dielectric strength to SF6 and shows promise in arc quenching applications; however, the behavior of scCO2 is not as well researched as that of SF6, leading to a critical gap in knowledge needed to implement this change. To bridge this gap, a preliminary investigation of scCO2 was done using a novel Particle-In-Cell (PIC) solver approach as opposed to a more classic, continuum flow approach. This work presents the initial results from the simulation program Charge Plus[1], developed by Electro-Magnetic Applications Inc. (EMA3D®). Charge Plus is a Particle-In-Cell (PIC) solver that, rather than using fluid properties, instead utilizes reaction probabilities to track macroparticles representing the flow of species in the simulation. While a continuum flow solver is a suitable approach to handle the initial quenching of the arc, the PIC method is particularly suited to answering this work’s overarching question of whether restrike (or reignition) will occur due to its leverage of molecular kinetics, as restrike is largly a molecular kinetics problem rather than a thermodynamics problem. Through a series of parametric studies, it was determined that scCO2 shows promise preventing arc restrike, but some numerical instabilities and a lack of validation data prevents this work from reaching a conclusive answer to the objective. However, significant progress has been made in building and testing a working model not only for scCO2 but also for a nozzle configuration.

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Uncertainty Analysis in ICRP 66 Human Respiratory Tract Model for Consequence Management Data Products

(Georgia Institute of Technology, 2024-12-08) Margot, Dmitri Edward

Inhaled radioactive is a unique hazard. Once inhaled the radioactive material is translocated within the body via incorporation into the metabolism and immune response. While metabolizing, the radioactive material is irradiating nearby tissue. Since the distribution of radioactive material changes over time, biokinetic modelling tracks the movement of the radioactive material within organs and tissues. To determine the impact of the input parameters into biokinetic modelling, a software called REDCAL (Radiation Exposure Dose Calculator) was developed in Python to handle statistically sampled parameters to compute the radiation dose from radionuclides of concern for emergency response planners. REDCAL handles the inhalation of radioactive particles and subsequent deposition within the airways. Following the deposition computations, REDCAL tracks the movement of radioactive material within the body and computes the effective dose to the individual over a lifetime. With statistically sampled input parameters, REDCAL was used to generate 3,410,000 effective dose coefficients to analyze the influence of the input parameters on the resulting dose. As sets of dose coefficients were made for each radionuclide and its associated lung clearance type(s), a defined distribution of its effective dose coefficient as a function of inhaled particle size, in AMAD, were generated to inform the sampling needing for computing derived response levels (DRLs) by in Turbo FRMAC by the Federal Radiological Monitoring and Assessment Center (FRMAC). This dissertation covers the methods, mathematics, and concepts required to compute particle deposition in the airways, solve biokinetic models, and compute effective dose from radiation sources with time-dependent concentrations.

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