Engineering Commons^™

Engineering The Properties Of Magnesium Aluminate Spinel Through Solid State Solutions, Robin Conner

All Theses

Magnesium aluminate spinel solid state solutions were prepared via the coprecipitation method and calcined in air at 900 °C for 2 h. The manipulation of magnesium aluminate spinel’s microstructure through the formation of solid state solutions with zinc and gadolinium substituting for magnesium was investigated. X-ray diffraction (XRD) and attenuated total reflectance Fourier transform infrared spectroscopy (ATR FTIR) confirmed the formation of a single cubic crystalline phase. The luminescence properties were investigated by radioluminescence (RL) under X-ray excitation and thermoluminescence (TL) measurements. In the case of zinc, all concentrations of the solid state solutions showed similar luminescence with bands at …

Genetically-Encoded Optical Barcodes For Single-Cell Analysis, Daniel Pritko

All Theses

Cell barcodes are capable of being used to answer many different biological questions. They have been used to track the lineage of cells to identifying the function of a gene. While there are multiple different methods to creating cell barcodes, they are limited in their scalability and application. In a previous publication we propose and computationally prove an optical single-cell barcoding method that bridges fast and scalable readouts with the benefits of genetic encoding. In this approach fluorescent proteins (fps) are combined to form fluorescent barcodes that can then be analyzed using a spectral flow cytometer. Here, we test the …

Exploring Healthcare Chatbot Information Presentation: Applying Hierarchical Bayesian Regression And Inductive Thematic Analysis In A Mixed Methods Study, Samuel Nelson Koscelny

All Theses

High blood pressure, also known as hypertension, significantly increases the risk of heart disease and stroke, which are leading causes of death in the United States. While contributing to over 691,000 deaths in 2021 alone in the United States (U.S.), it also imposes immense economic burden on the healthcare system, costing approximately $131 billion annually. One way to address this issue is for increased self-care behaviors and medication adherence, both of which require sufficient health literacy. Despite the importance of health literacy, 90% of U.S. adults struggle with health-related subjects. Overcoming the issues associated with health literacy requires addressing the …

Trust: The Inertia Taxonomy Of Trust And Learning Outcomes Of Trust Building Exercises, Ann B. Lyons

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This study investigates United States construction professionals’ view of trust in the workplace. In particular the focus is on building trust through trust building exercises. In order to accomplish this, a literature review was conducted focusing on trust in the worldwide construction industry. This was followed by interviews with US construction professionals who focus on team building. These interviews informed a survey sent to a wide variety of US construction professionals. The survey had two sections of content questions, 1. view of trust indicators and 2. perception of trust building exercises. Finally, experts in the field of construction team building …

A Benchtop Analysis Of Pressure Offloading Associated With Custom Socket Inlays In Transtibial Prostheses, Sarah G. Hill

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Approximately 78% of people with lower limb amputations are dissatisfied with the comfort of their prostheses (Quintero-Quiroz & Perez 2019). In the case of lower limb amputations, the residual limb tissue bears far more weight than it was before the amputation. The pressure put on the soft tissue of the residual limb causes discomfort (Brown et al. 2021). In previous work, custom inlays were created, which fit inside the prosthesis and offload pressure, with the goal of helping to increase the comfort and satisfaction of the prosthesis user (Brown et al. 2021). In this project, a benchtop prosthetic socket loading …

The Role Of Kinases Signaling In Organogenesis, Fatemeh Nasehi

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Kinases are crucial regulators of organ development and differentiation. This thesis investi- gates the roles of TAK1, TGFbeta-Activate Kinase 1 (TAK1/Map3K7), and Akt3 kinases in skeletal, cardiac muscle, and cartilage. TAK1 is pivotal for the differentiation of various organ systems, including sinoatrial node and cartilage, and is responsible for phosphorylat- ing a diverse array of downstream kinases. We identified several novel proteins, including phospho-Akts, that are upregulated in response to TAK1 activation. We discovered severe Dilated Cardiomyopathy (DCM) and cartilage defects in Akt3 mutant mice. Although this mouse mutant has been studied for over two decades, we are the first …

Novel Meta-Materials Application For Pressure-Offloading Of Diabetic Foot Ulcers, Kyle Walker

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Diabetes and its associated complications have seen their prevalence sharply rise in the United States over the past few decades. In fact, the prevalence of diagnosed diabetes has nearly doubled from 5.1% of the US population in 1988, to 9% in the most recent CDC report, which does not include the large percentage of the population with undiagnosed or prediabetes. Of this diabetic population, it is estimated that up to 34% will experience at least one foot ulcer during their lifetime. In worst case scenarios, these ulcers can become infected and eventually require amputation of a portion of, or the …

Identification And Validation Of A Measurement Of Emergency Physician Workload During End Of Shift Patient Handoffs, Steven Foster

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Recent increases in emergency physician (EP) workload have been identified as contributors to increased EP burnout, increased staff attrition, decreased patient safety, and increased patient admission rates. Patient handoffs have been extensively researched as critical points in patient care, with existing research primarily focusing on communication errors and interventions designed to standardize handoff communication protocols.

While end of shift handoffs in hospital emergency departments (EDs) intuitively represent a transfer of patient caseload from an outgoing EP to an incoming EP, there is a fundamental lack of literature examining how such handoffs contribute to EP workload, and a similar lack of …

Vision-Based Autonomy Stacks For Farm Tractors And Intelligent Spraying Systems In Orchards, Shengli Xu

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Autonomous tractors equipped with intelligent sprayers have become a pivotal aspect of smart farming (SF), marking a transformative shift in traditional agricultural practices and holding the potential to revolutionize the farming industry. With 2,453,620 fruit-bearing acres in the United States as of 2022, there is a pressing need for the implementation of autonomous systems for farm tractors and intelligent spraying systems in orchards. These advancements can significantly reduce labor costs, address labor shortages, and minimize spray loss. Furthermore, to enhance profitability and productivity, it is essential to develop low-cost yet effective vision-based autonomy systems that can operate efficiently across various …

Convex Approach To Data-Driven Optimal Control With Safety Constraints Using Linear Transfer Operator, Joseph Raphel Moyalan

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This thesis is concerned with the data-driven solution to the optimal control problem with safety constraints for a class of control-affine nonlinear systems. Designing optimal control satisfying safety constraints is a problem of interest in various applications, including robotics, power systems, transportation networks, and manufacturing. This problem is known to be non-convex. One of this thesis's main contributions is providing a convex formulation to this non-convex problem. The second main contribution is providing a data-driven framework for solving the control problem with safety constraints. The linear operator theoretic framework involving Perron-Frobenius and Koopman operators provides the convex formulation and associated …

Fabrication And Characterization Of Lignin–Pva Hydrogels With Tunable Network Structures, Keturah Bethel

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The ability to directly tune the crosslinked network structure of hydrogels is crucial for their functional applications in various fields, such as water filtration, protein separation, and tissue engineering. By controlling the crosslink density of the hydrogel, one can directly alter the mesh size – i.e., the end-to-end distance between crosslink junctions – and, subsequently, directly alter the hydrogel performance. This work discusses the fabrication and characterization of soft composites containing the biopolymer, lignin, are discussed. Precisely, physically-crosslinked composite lignin–Poly(vinyl alcohol) (PVA) hydrogels were fabricated via the freeze-thaw (F/T) pathway, whereby solutions containing specified amounts of PVA and lignin were …

Understanding The Microstructure And Tribological Performance Of Cocrfeni-Based High Entropy Alloys, Ali Azarmi

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Due to their higher wear resistance compared to conventional alloys, high entropy alloys (HEAs) are now being considered as candidates for parts undergoing sliding contact during their lifetimes. While the engineering field has built some knowledge related to the performance of selected high entropy alloys, such as the CoCrFeNi alloy, more research is needed to determine if (how) expansions from four to five principal alloying elements alter the performance compared to the initial alloy. In this study, we started this research effort by investigating the relative performance of CoCrFeNiMn and CoCrFeNiTi with respect to CoCrFeNi. The two primary alloying elements …

Understanding The Challenges To Robotic-Assisted Surgery Adoption From The Perspectives Of The Human-Robot Interaction, Built Environment, And Training, Patrick A. Fuller

All Theses

Introduction: Robotic-assisted surgery (RAS) is a form of minimally invasive surgery that is increasing in both its adoption and development due to many perceived advantages such as tremor reduction and motion scaling. However, RAS is still relatively new and there are a variety of novel barriers and challenges to the adoption of these platforms. Objectives: This study aims to understand how the integration of RAS platforms impacts the interactions and outcomes of interactions between surgical team members to explore the barriers from three aspects critical to facilitating Robotic-assisted-surgery (RAS) adoption: the human-robotic interaction, built environment, and RAS training. Future …

Local Charge Distortion Due To Cr In Ni-Based Concentrated Alloys, Jacob Fischer

All Theses

Due to the presence of multiple elements consisting of a range of atomic radii, local lattice distortion (LLD) is commonly observed in concentrated (and high entropy) alloys. However, since these elements also have diverse electronegativities, recent works show that atoms can have a range of atomic charges. In this work, using density functional theory (DFT), we investigate electronic charge distribution in face centered cubic (FCC) Ni-based alloys and find significant charge-density distortion in HEAs. Specifically, Cr atoms have large charge density distortion that results in a wide range of bond lengths, atomic charges, and electronic density of states in Cr-containing …

Degradation Products And Microbial Communities Associated With The Conversion Of Five Long-Chain Fatty Acids Relevant For Anaerobic Co-Digestion Of Fog With Sludge, Claire Funk

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Anaerobic digestion is a technology that allows wastewater treatment plants to convert sludge to energy by recovering the biogas produced during the breakdown of proteins, carbohydrates, and lipids. Furthermore, adding fats, oils, and greases (FOG) through co-digestion with wastewater sludge can increase energy production as lipids have a higher methane yield than proteins and carbohydrates. However, adding FOG can also lead to operational problems in the digester due to the potential accumulation of certain long-chain fatty acids (LCFAs). Current research is limiting in the degradation pathways of prominent LCFAs in FOG and the microbial communities responsible for their degradation

The …

Hyperspectral Image Classification Of Bacteria Using A Deep Convolutional Neural Network, Bruce S. Vogelsberg Jr

All Theses

Hyperspectral imaging is a non-invasive imaging method capable of collecting both spatial and spectral information. However, because of the large volume of data collected, much of it is redundant or not useful for classification. Deep learning is a subset of machine learning that uses artificial neurons in a multilayered structure to learn representations from data. One of the main advantages of deep learning is the powerful feature extraction capabilities, which allow the model to learn both high- and low-level features. Convolutional neural networks are a type of deep learning model that have alternating convolutional and pooling layers capable of extracting …

Predicting The Ductility Of Tungsten Based Bcc Refractory High Entropy Alloys: A Computational Science Driven Study, Akshay Korpe

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Bcc refractory high entropy alloys (HEAs) are a relatively new category of metallic alloys that promise excellent irradiation resistance and strength retention at high temperatures but exhibit brittle behavior at room temperatures limiting their formability. Understanding the deformation mechanisms and predicting their ductility at room temperature is a topic of interest in contemporary research.

In this work, multiple independent ductility criteria for quantifying the ductility of these HEAs were studied, calculated and compared using Density Functional Theory (DFT) calculations and continuum mechanics frameworks. These ductility parameters were calculated for various W-Ta-Cr-V alloys and the trends were analyzed for each criteria …

Developing An Assessment Tool For Ideation Effectiveness: A Survey-Based Approach For The Shah’S Method Of Design Space Exploration, Venkat Jaya Deep Jakka

All Theses

The research is focused on creativity in engineering design. The goal is to understand if creativity in engineering design can be assessed using a less resource-intensive approach, specifically a survey, compared to design exercises. The survey builds on the metrics established by Shah and colleagues. The four metrics are Novelty, Quality, Variety and Quantity. The metrics are measured with the help of a design activity that is deployed to the participants. These metrics have been used in comparative analysis to assess treatments such as new design methods and personality types. However, the downside of the metrics is that they require …

Expandable Tissue-Engineered Living Surgical Pulmonary Heart Valve For Pediatric Patients, Jacob M. Lautenschlager

All Theses

Cardiovascular disease is the most common cause of mortality in developed countries, with 607.74 million cases globally in 2020.^1,2 Advances in medicine have changed the current demographic suffering from heart valve disease into an aging population suffering from degenerative heart valve disease, creating a growing population treated by surgical or transcatheter intervention.^3-6 Current treatments of valvular heart disease are therefore directed toward valve replacements for the adult population, leaving a treatment gap for pediatric patients suffering from heart valve disease.^7-10

Congenital heart defects are defined as structural abnormalities of the heart or intrathoracic great vessels and are …

Training Uav Teams With Multi-Agent Reinforcement Learning Towards Fully 3d Autonomous Wildfire Response, Bryce Hopkins

All Theses

As climate-exacerbated wildfires increasingly threaten landscapes and communities, there is an urgent and pressing need for sophisticated fire management technologies. Coordinated teams of Unmanned Aerial Vehicles (UAVs) present a promising solution for detection, assessment, and even incipient-stage suppression – especially when integrated into a multi-layered approach with other recent wildfire management technologies such as geostationary/polar-orbiting satellites and CCTV detection networks. However, there remains significant challenges in developing the necessary sensing, navigation, coordination, and communication subsystems that enable intelligent UAV teams. Further, federal regulations governing UAV deployment and autonomy pose constraints on real-world aerial testing, creating a disconnect between theoretical research …

Proportioning And Performance Of Ultra-High Performance Concrete (Uhpc) For High Friction Surface Treatment (Hfst) On Pavement And Bridge Decks, Adam R. Biehl

All Theses

High Friction Surface Treatment (HFST) is a roadway remediation technique used to improve pavement’s coefficient of friction, to enhance roadway safety. The application of HFSTs has repeatedly demonstrated the ability to significantly reduce crashes in both wet and dry conditions. Typically, epoxy-resins and calcined bauxite aggregate are used in HFST treatment. However, the high material costs and scarcity of calcined bauxite render this form of HFST an expensive and limited option for roadway rehabilitation. Therefore, the identification of alternative binders and HFST aggregates is needed for broad scale implementation. One potential alternative binder is Ultra-High-Performance Concrete (UHPC), a specialty cementitious …

Impact Of Nitrogen Species On Algal Carbon Capture, Lauren J. Todd

All Theses

Increasing global carbon emissions from fossil fuel combustion and the resulting detrimental effects of climate change have created a need for atmospheric carbon drawdown. Biological-based carbon capture not only sequesters carbon dioxide (CO₂) but also provides a sustainable source of biomass for biofuels and biomaterials. Thus, the aim of this research was to examine freshwater green algal growth with total ammoniacal nitrogen (TAN) and nitrate nitrogen (NO₃-N) sources at high pH for improving carbon capture potential. The following objectives were accomplished: nitrogen uptake was identified as simultaneous or sequential, the effect of TAN and NO_{3 …}

Extraction Of Neutron-Gamma Irradiated Diffusion Pump Oils, Cooper L. Tillman

All Theses

This work successfully demonstrates solvent extraction methods for separation of oil from the by-products when two commercially available vacuum pump oils were exposed to an intense neutron and gamma-ray radiation environment. Nuclear fusion power at a commercial scale has accelerated the need for radiation resistant vacuum technology, such as oil-based diffusion pumps. Polyphenyl ether and aromatic silicone oils were irradiated at the Rhode Island Nuclear Science Center (RINSC) up to MGy absorbed doses with neutron and gamma-ray radiation. Solvent extractions were performed using hexane and isopropanol to characterize the oil extraction as a function of total absorbed dose. The by-products …

Hydrogen Isotope Exchange On Diffusion Pump Oils, Carson G. Allen

All Theses

The extent of isotopic exchange of deuterium and tritium with protium atoms in hydrocarbon pump oil was investigated as a means to quantify the chemical stability of a mineral oil, a silicone oil, and a polyphenyl ether oil as candidates for implementation in a diffusion pump. In its target application at a fusion power plant, a chemically stable and radiation hard oil offers substantial reductions in tritium inventory, electrical consumption, and operational pump expenses over alternate solutions for vacuum induction. Select oils were introduced to deuterium and tritium isotopes in a high temperature environment, analogous to an operating vacuum pump. …

Using Efficient Vision Transformers To Improve Perception Systems In Autonomous Off-Road Vehicles, Adam S. Pickeral

All Theses

The development of autonomous vehicles has become one of the greatest research endeavors in recent years. These vehicles rely on many complex systems working in tandem to make decisions. For practical use and safety reasons, these systems must not only be accurate, but also be quick to make decisions. In Autonomous Vehicle research, the environment perception system is one of the key com- ponents of development. The environment perception system allows the vehicle to understand its surroundings using cameras, light detection and ranging (LiDAR), and other sensor systems or modalities. Deep learning computer vision algorithms have shown to be the …

Advancing Unmanned Ground Vehicle Path Planning With Quantified Map Uncertainty, Israel Afriyie

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This thesis addresses the complex challenge of path planning for Unmanned Ground Vehicles (UGVs) in areas where traditional navigation systems are inadequate, such as unstructured or off-road military zones. Recognizing the limitations of current path planning algorithms, which primarily focus on optimizing for the shortest path and often fail to account for variability and risks, this research proposes an enhanced Hyperstar algorithm. This approach not only considers the fastest route but also integrates maximum delays and visibility risks into its computation, ensuring a balance between swift mission completion and concealment from adversaries.

Utilizing terrain maps and incorporating uncertainties in map …

Exploiting Physical Side-Channel Information For Offensive And Defensive Ends, Sisheng Liang

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Side-channel information consists of side effects of computation that range from microarchitectural to physical phenomena. Empirical studies have demonstrated the practical exploitability of these side effects in real-world systems for malicious attacks and effective defenses. In this dissertation, we discover, analyze, and exploit certain physical side-channel information for end-to-end attacks and defense across three studies.

In the first study, we demonstrate a new DNN model extraction attack named Clairvoyance that exploits certain far-field electromagnetic signals emitted from a GPU to steal DNN models several meters away from the victim machine, even with some physical obstacles in between. Using Clairvoyance, an …

Hardware-Oriented Protection And Acceleration For Machine Learning Application, Antian Wang

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The security of Machine Learning (ML) grows along with the development of high-performance models and expanding application scenarios. Numerous users are benefiting from the convenience brought by transformative ML applications. In the meantime, various attackers are trying to find vulnerabilities within ML deployment service models, thereby undermining the performance of ML and jeopardizing stakeholders’ interests. The dissertation focuses on the two aspects of secure ML applications: acceleration and protection. Homomorphic Encryption (HE) emerges as a widely recognized security primitive suitable for the cloud computing service model, where the computation can be performed over ciphertext without decryption. However, evaluations in the …

Frameworks For The Techno-Economic Assessment Of Membrane-Based Bioprocessing Platforms, Juan Jose Romero Conde

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This dissertation describes developing and implementing computational frameworks for simulating and optimizing purification processes in the biopharmaceutical industry. The framework performs techno-economic analyses to establish value propositions for new process alternatives, especially membrane technologies. Initially, the focus is developing a framework capable of simulating monoclonal antibody (mAb) capture using membrane and resin media in multi-column chromatography (MCC) platforms for continuous manufacturing. Subsequently, the impact of capture MCC is compared against other intensification strategies in established mAb manufacturing facilities. Finally, the framework application expands to simulate the purification of adeno-associated virus (AAV) vectors for gene therapy.

Chapter 2 details the framework …

Physics-Informed Machine Learning Methods For Inverse Design Of Multi-Phase Materials With Targeted Mechanical Properties, Yunpeng Wu

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Advances in machine learning algorithms and applications have significantly enhanced engineering inverse design capabilities. This work focuses on the machine learning-based inverse design of material microstructures with targeted linear and nonlinear mechanical properties. It involves developing and applying predictive and generative physics-informed neural networks for both 2D and 3D multiphase materials.

The first investigation aims to develop a machine learning method for the inverse design of 2D multiphase materials, particularly porous materials. We first develop machine learning methods to understand the implicit relationship between a material's microstructure and its mechanical behavior. Specifically, we use ResNet-based models to predict the elastic …