Engineering Commons^™

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

All Theses

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 …

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 …}

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

All Theses

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 …

Divergence Measures And Aggregation Operators For Single-Valued Neutrosophic Sets With Applications In Decision-Making Problems, Surender Singh, Sonam Sharma

Neutrosophic Systems with Applications

Single-valued neutrosophic sets (SVNSs) facilitate the representation of uncertain information more extensively than conventional methods. The study of divergence measures of SVNSs is important due to their applications in different areas like multi-criteria decision-making (MCDM), pattern recognition, cluster analysis, machine learning, etc., In this paper, we introduce a divergence measure for SVNSs. The suggested divergence measure is applied to cluster analysis for the classification of imprecise data. For establishing the reasonability and advantage of the suggested divergence measure in a clustering problem over the existing measures, a comparative assessment is also presented. Furthermore, we introduce, an inferior ratio method for …

Smart Zoning Control For Air Conditioning Systems, Octavio Gomes Diaz

Mechanical Engineering Theses

Nearly 45% of the energy consumed in residential buildings goes for Heating, Ventilation, and Air Conditioning (HVAC). Typical HVAC systems are mostly controlled by one thermostat that is usually located in the living room. This means that the HVAC system is running without consideration of the thermal conditions in the other rooms (zones), which might be colder (or warmer). Colder zones in the summer indicate that a lot of energy is wasted, and warmer zones mean that the HVAC system can’t produce a good comfort level. Therefore, zoning was introduced into relatively recent HVAC systems. Zoning in HVAC systems uses …

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

All Dissertations

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

All Dissertations

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

All Dissertations

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 …

Understanding And Tuning Magnetism In Van Der Waals-Type Metal Thiophosphates, Rabindra Basnet, Jin Hu

Physics Faculty Publications and Presentations

Over the past two decades, significant progress in two-dimensional (2D) materials has invigorated research in condensed matter and material physics in low dimensions. While traditionally studied in three-dimensional systems, magnetism has now been extended to the 2D realm. Recent breakthroughs in 2D magnetism have attracted substantial interest from the scientific community, owing to the stable magnetic order achievable in atomically thin layers of the van der Waals (vdW)-type layered magnetic materials. These advances offer an exciting platform for investigating related phenomena in low dimensions and hold promise for spintronic applications. Consequently, vdW magnetic materials with tunable magnetism have attracted significant …

High-Quality Single-Step Growth Of Gaas On C-Plane Sapphire By Molecular Beam, Emmanuel Wangila, Calbi Gunder, Mohammad Zamani-Alavijeh, Fernando Maia De Oliveira, Serhii Kryvyi, Aida Sheibani, Yuriy I. Mazur, Shui-Qing Yu, Gregory J. Salamo

Physics Faculty Publications and Presentations

We report on the growth of high-quality GaAs semiconductor materials on an AlAs/sapphire substrate by molecular beam epitaxy. The growth of GaAs on sapphire centers on a new single-step growth technique that produces higher-quality material than a previously reported multi-step growth method. Omega-2theta scans confirmed the GaAs (111) orientation. Samples grown at 700 °C displayed the highest crystal quality with minimal defects and strain, evidenced by narrow FWHM values of the rocking curve. By varying the As/Ga flux ratio and the growth temperature, we significantly improved the quality of the GaAs layer on sapphire, as compared to that obtained in …

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

All Dissertations

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 …

Large-Scale Hpc-Empowered Power Electronics Modeling And Simulation In Photovoltaic Applications, Liwei Wang

All Dissertations

The rising popularity of renewable energy sources requires advanced, efficient power electronic systems for energy conversion, grid integration, and system management, thereby raising expectations for power electronics in the energy industry. The complexity of modern power electronic systems requires comprehensive simulations and in-depth analysis to predict performance accurately, but this process is impeded by prolonged simulation times. The primary objective of this dissertation is to develop a high-fidelity, high-speed event-driven simulator to tackle challenges related to mass data processing, uncertainty evaluation, as well as modeling and simulation issues in assessing the reliability of power electronics in large-scale Photovoltaic (PV) systems. …

Investigating Institutional Support For A Minority Engineering Program At A Historically White Institution, Stephanie Damas

All Dissertations

Engineering programs at historically White institutions (HWIs) often perpetuate stereotypes and racism against Black students, impacting their experiences and opportunities in the field. Minority engineering programs (MEPs) provide support and resources to minority students in engineering, challenging stereotypes and fostering positive identity development. MEPs push back on cultural norms by rejecting the stereotypical narrative of what it means to be Black in engineering. Despite their significance, MEPs face challenges in garnering institutional support and recognition within engineering departments. It is imperative to understand what institutional support for MEPs looks like to mitigate barriers identified in the literature. To address these …

Data-Driven Enhanced Energy Management System Applications For Energy Control Centers, Dulip Madurasinghe

All Dissertations

This dissertation explores the pressing needs of modern bulk power system operation and control and delves into enhancements to EMS applications with minimal infrastructure development. The dissertation investigates three main EMS application enhancements. The transmission network topology processing (TNTP) is a foundational application of the EMS. A physics-based hierarchical transmission network topology processing (H-TNTP), including substation configuration identification, to improve efficiency and reliability is proposed. Secondly, a multi-level distributed linear state estimation (D-LSE) approach solely based on PMUs is proposed utilizing H-TNTP as the network modeling tool. The D-LSE can conduct linear state estimation (LSE) at either substation, area or …

Ultra High-Performance Concrete As A High Friction Surface Treatment For Pavements And Bridges, Kyle Maeger

All Dissertations

High Friction Surface Treatment (HFST) is a proven technology to reduce crashes on roadways by increasing the coefficient of friction between vehicle tires and the pavement. However, it is an expensive solution due to the high cost of the two commonly used constituent materials, calcined bauxite aggregate and epoxy resin binders.

This study evaluated the abrasion resistance performance of four alternative HFST aggregates to calcined bauxite using Los Angeles Abrasion and Micro-Deval Abrasion tests, and studied the surface texture utilizing a high-resolution laser scanner and friction utilizing the British Pendulum Test.

This study also assessed the performance of non-proprietary Ultra …

Integrating Artificial Intelligence And Augmented Reality For Enhanced Task Performance In The Construction Industry, Aasish Chandrika Bhanu

All Dissertations

The Architecture, Engineering, and Construction (AEC) sector, characterized by its complex tasks, often faces challenges in adopting cutting-edge technologies, a trend that can significantly hinder productivity improvements compared to other industries. This dissertation explores the emerging integration of Artificial Intelligence (AI) and Augmented Reality (AR) within the AEC domain, investigating how effectively this can be implemented to potentially revolutionize industry practices. AI could be used in the AEC domain for advanced analytical and decision-making processes, while AR could be used for training, visualization, and remote collaboration.

In scenarios where construction site workers require expert guidance, these technologies could be helpful. …

Opioid Overdose Epidemic Modeling, Chelsea Spence

All Dissertations

The opioid overdose crisis in the United States has led to thousands of lost lives and thousands more people struggling with opioid dependence. Disease modeling allows researchers to examine the course that the disease may take and to investigate policies to determine the effects they may have. Disease models can be used to model non-communicable diseases and have been used to study opioid use disorder. Many types of disease models exist with their own inherent benefits and drawbacks.

In this dissertation, we provide a scoping review of the disease models that have been used to study the opioid overdose epidemic. …

Time-Domain Line Protection In Presence Of Renewables, Prabin Adhikari

All Dissertations

Inverter based resources (IBRs) are crucial in integrating renewable energy sources into the power grid. However, their unique fault characteristics, significantly different from synchronous generators (SGs), present several challenges for existing line protection schemes at both transmission and distribution levels. These schemes, reliant on distance and directional relays designed in phasor domain, are not well-suited for IBRs. Most published literature addressing this problem concentrates on altering the control design of inverters. However, this approach faces practical limitations. Inverter controls, often proprietary, are not readily accessible to utilities, rendering the control-based solutions impractical for widespread implementation.

To address this challenge, this …

Fluid-Solid Coupled Analysis Of Biological Samples In A Flow Chamber Using Optical Coherence Tomography, Reece W. Fratus

All Dissertations

Forces from fluid flow on a tissue or cellular boundary can drive remodeling processes through mechanotransduction pathways. In most cases, the exact mechanisms are not understood, such as in marine biofilm development or vascular remodeling. To gain a better understanding of these interactions, the flow profile at a solid boundary and the mechanical changes of that solid can be coupled together to determine the impact of fluid flow on mechanical remodeling. To achieve this, optical coherence tomography (OCT) is used to image the fluid and solid simultaneously. Fluid seeded with particles can be imaged and run through a particle image …

Fundamental Study Of Nonlinear Electrophoresis, Joseph Armakan Bentor

All Dissertations

Classical electrophoretic theory describes the linear response of particles suspended in Newtonian fluids under weak electric fields. When the electric field exceeds this weak limit, a nonlinear response arises due to non-uniform surface conduction over the curved particles. This nonlinear behavior introduces dependencies on fluid and particle properties not considered in the classical theory, offering potential advantages for microfluidic particle manipulation. While this phenomenon has been extensively studied theoretically and numerically in Newtonian fluids, experimental investigations have been relatively limited.

Fluid rheology can significantly alter particle dynamics under applied electric fields. Rheological properties like shear-thinning and elasticity which are not …

On The Structure, Energy, And Segregation Behavior Of Grain Boundaries In Metallic Systems, Yasir Mahmood

All Dissertations

Nearly all structural metallic systems are multi-component polycrystalline aggregates; their microstructures are composed of crystalline grains that are internally joined at grain boundaries (GBs). This thesis focuses on GB structure, energy, and chemistry, as these greatly influence many material properties and processes, including boundary dynamics during processing treatments or under operating conditions.

Using atomistic simulations, we examine the impact of metastable GB structures on solute segregation. A wide range of GB geometries and metastable structures are used in our study. The Al-Mg alloy is used because it is of interest for light weighting. The atomistic simulation results are used to …

Computer Vision Algorithms For Assessment Of Surgical Suturing Skill Using Hand And Needle Motion, Jianxin Gao

All Dissertations

Surgical suturing skill assessment is a crucial part of surgical education. Vascular surgery educators have developed a simulation-based examination called Fundamentals of Vascular Surgery, which includes a clock-face model for assessing open surgical suturing skills. The clock-face model, however, requires the valuable time of expert surgeons to determine examinees' skills. Moreover, expert surgeons have different judgments for appropriate sutures, which leads to inconsistent grading. These limitations motivate us to use sensors to measure examinees' needle motions and hand motions during the clock-face suturing exercises, and then use the measurements for objective suturing skill assessment.

To assess suturing skills based on …

Contribution Of Collagen Type I To The Mechanical Properties Of Myocardial Tissues At The Micron Level, Adam Baker

All Dissertations

Collagen is a critical component of the organization and one of the key factors contributing to the mechanical stability of the myocardium. Where cardiomyocytes actuate to contract the heart and deliver blood to the lungs and the entire body, the local collagen network must be able to support the mechanical needs of the heart by enhancing rigidity, reducing the mechanical responsibility of cells, and increasing compliance to add loading capacity during diastole. At an organ-wide level, this has been measured and modeled in many ways. At the tissue level, the mechanical properties have been evaluated using techniques such as bi-axial …

Lab To Leadership: How Do Women College Stem Students’ Classroom Experiences Inform Their Leader Identity Development?, Meredith Mcdevitt

All Dissertations

This dissertation is an exploration of leader identity development and women in science, technology, engineering, and mathematics (STEM) college academic classrooms. While there continues to be research promoting diversity in STEM professions, women remain underrepresented in STEM disciplines, leadership positions, and for this specific study, the college academic classroom. This dissertation represents an opportunity for women in STEM college students to reflect on their experiences in STEM academic spaces and communities, while self-exploring factors that shape their leader identity development. The research utilized a basic qualitative research design to understand the participant’s authentic experiences within the academic environment. Conducting semi-structured …

Base Case Shear-Wave Velocity Profiles And Non-Linear Material Property Models Of Local Site Conditions In South Carolina For Seismic Site Response Analyses, Ali Sedaghat Shirehjini

All Dissertations

This dissertation presents the development of base case small-strain shear-wave velocity ( ) profiles and non-linear materials property models of local site conditions in South Carolina for seismic site response analyses. The need to address South Carolina's seismic hazards is partly motivated by the 1886 Charleston earthquake (moment magnitude, M_w= 6.7 to 7.5). Required inputs for seismic site response analysis include profile down to a specified reference outcrop condition and non-linear material properties for each layer in the profile. Although firm rock (i.e., ≥ 2,500 ft/s) or hard rock (i.e., ≥ 9,850 ft/s) is commonly assumed for the …

Exploring The Synthesis Of Biobased And Chemically Recyclable Polysulfone Using Imine Chemistry, Vitasta Jain

All Dissertations

Plastic waste poses a major problem because of the chemical stability of these materials, leading to their accumulation in the environment and the leaching of toxic chemicals during their slow decomposition. Additionally, the use of depleting petroleum reserves for synthesis has made for an unsustainable production and risks due to use of chemicals hazardous to the environment and the individuals exposed to it.

To address these concerns, researchers have explored biobased feedstock and incorporating chemical recycling capabilities for a closed loop, sustainable process. One promising feedstock is lignin with its abundant functional groups that can be modified and utilized to …

The Development Of A Novel Cartilage Analog Scaffold For Chondral Regeneration, Vishal Thomas

All Dissertations

Focal Chondral Defects (FCDs) are cartilage injuries that affect about 900,000 Americans every year. Left untreated, these may lead to osteoarthritis and eventually necessitate painful knee replacements. Current treatment options are limited in terms of durability, cost, and availability of grafts. Tissue engineering, using natural scaffolds, are a highly attractive alternative promising cost efficiency, abundance, and long-term benefits. However, their low mechanical strength and dense matrices are impediments that could lead to sub-optimal repair.

In this work, a natural biomaterial, the bovine nucleus pulposus (bNP), derived from intervertebral disc tissue, was identified as a candidate scaffold for cartilage regeneration. Mechanical …