Engineering Commons^™

Lower Limits Of Performance Of An Electrospray Thruster Using A Direct Measurement Method, Caitlin M. Bunce

Masters Theses

Nanosatellites are a growing technology that offer a more accessible way for scientific missions to be conducted in space. The number of nanosatellites launched annually continues to grow, increasing the need for a propulsion system onboard to assist in collision avoidance, station keeping, rendezvous, and other attitude adjustments. More importantly though, new rulings have dictated that all orbiting spacecraft must deorbit within five years of mission completion to help mitigate the evergrowing problem of space debris. Electrospray thrusters, a subset of electric propulsion, is a well-researched method of propulsion for nanosatellites, including the novel µSTAMPS thruster currently in development at …

Validating The Design Tensile Strength Of Grade 5 And Metric Class 8.8 Bolts, Paxton Charles Lifsey

Masters Theses

Bolted connections offer many benefits including ease of installation and maintenance and replaceable components, but must have sufficient strength in order to take advantage of these benefits. One of the major ways a bolted connection is loaded is under tension. In this loading condition, bolted connections can fail via tension in the threaded area, shear in the bolt threads, or shear in the nut threads. Standards such as FED-STD-H28/2B and ISO TR/16224 include equations for the stress area and strength of these limit states as well as for the required length of engagement such that tensile failure controls. These equations …

Electromagnetic Penetration Of Structures Considering High-Altitude Electromagnetic Pulse, David P. Mignardot

Masters Theses

The electric power system is undergoing transformation in the 21^st century. Generation is becoming more distributed, more electronic equipment is utilized for operation and control, and load demand is increasing with society’s electrification. As this transformation occurs, both new and old threats to the system’s resilience are of concern. Of the old threats, and a critical component when studying resilience, is high-altitude electromagnetic pulse (HEMP). In this thesis, weaponized electromagnetic pulse and its interaction with the power system is revisited with an emphasis on structure shielding effectiveness against both radiated and conducted energy. Computational electromagnetic plane wave simulations are …

An Audio-Based Emotion Monitoring System For Enhancing Construction Worker Safety, Mengjun Wang

Masters Theses

The high suicide rate among construction workers in the U.S. is a concerning issue. For every 100,000 workers in this field, 53.3 are reported to commit suicide, compared to the national average of 12.93. This statistic highlights the importance of addressing the mental well-being of construction workers, which directly impacts their performance and safety on the job. In this research, an audio-based system is proposed to monitor the emotions of construction workers in real-time, aiming to enhance their safety and address potential concerns proactively. The system involves a novel stimulus mechanism that encourages workers to interact with an AI, which …

A Framework For Estimating Hybrid Manufacturing Costs, Nathan Joel Wilson

Masters Theses

Based on its potential to reduce lead times, hybrid manufacturing, which often includes both additive manufacturing and machining processes, is receiving more attention from manufacturers as they seek to increase their supply chain resilience and efficiency. A new solid-state additive manufacturing method, referred to as additive friction stir deposition (AFSD), has shown the potential to become an important process for hybrid manufacturing. To justify the selection of a hybrid manufacturing approach, the cost needs to be estimated for comparison to conventional approaches. This thesis proposes a suite of cost models that include AFSD, powder bed fusion (PBF), wire arc additive …

Milling Stability Map Identification And Machining Parameter Optimization Using Bayesian Inference, Aaron William Cornelius

Doctoral Dissertations

This dissertation describes a physics-guided Bayesian learning approach for statistically modelling and optimizing machining processes under a state of uncertainty. This approach uses a series of automatically-selected cutting tests to refine uncertainties about the machining system's dynamics and cutting force and identify higher productivity cutting parameters. The algorithm is evaluated experimentally and compared to the cutting tool manufacturer’s recommendations, both in laboratory conditions and in an industrial setting to optimize the machining process for a large aluminum component. These results show that the proposed Bayesian model can quickly identify both highly-productive machining parameters and accurate information about the underlying system …

State Of Health Estimation For Second-Use Electric Vehicle Batteries In Grid Applications, Yousef Hassan A Alamri

Masters Theses

Escalating demand for sustainable energy solutions necessitates the efficient utilization of energy storage systems (ESSs). This thesis explores the critical need for efficient energy storage systems in the face of increasing demand and intermittent renewable energy sources and addresses the need for advanced energy storage technologies, focusing on second life batteries as a potential solution. A literature review highlights the significance of second life batteries in addressing the challenges of energy storage, emphasizing their potential for cost-effective and eco-friendly alternatives by repurposing retired electric vehicle batteries. These batteries, with decreased capacity for automotive use, still retain energy storage capabilities, making …

Predictive Models For Mechanistic Cutting Force Coefficients And Surface Roughness In Carbon Fiber Reinforced Polymers Milling With Tool Wear, Junbeom Son

Masters Theses

Machining carbon fiber composite materials poses significant challenges including rapid tool wear and decreased productivity. This research aims to address these challenges by developing a predictive model for surface roughness in carbon fiber composite milling operations using a cutting force-based approach.

This research applies a mechanistic cutting force model to force prediction in carbon fiber composite milling. Because tool wear can be significant in this application, the force model coefficients are defined as a function of the volume of material removed. This enables the cutting force growth with tool wear to be embedded within the model. Examples are provided for …

Finding Short Range Order In High Entropy Alloys, Mariah Wakefield

Masters Theses

In this project, chemical short-range order in four samples of the high entropy alloy FeMnAlC was investigated. X-ray diffraction measurements were performed at the Advanced Photon Source of Argonne National Laboratory in Chicago, IL. The data were then analyzed by curve fitting with mathematical Gaussian and Lorentzian functions. Conditional fitting was applied to the first and fourth samples to confirm the original curve fit. Conditional fitting was then used to adjust the determined indices of the Gaussian peaks in these samples so that they better reflected what was occurring in nature. From these indices, an increased unit cell was predicted …

Power System Electromagnetic Transient Simulation Using A Semi-Analytical Approach, Min Xiong

Doctoral Dissertations

This dissertation investigates efficient power system electromagnetic transient (EMT) simulations using a semi-analytical approach.

First, based on state-space equations of system EMT models, a semi-analytical solution (SAS) is acquired using the Differential Transformation Method (DTM). The DTM can efficiently derive the SAS of any linear or nonlinear system as a power series in time in a recursive manner using well-developed transformation rules. A high-order SAS allows a large time step to speed up the simulation while maintaining the same level of accuracy. Also, a variable time step approach is proposed to further improve its efficiency. Case studies on multiple systems …

Automated Intake Valve Control Systems For Rural Community Water System, Isabelle Hamby, Jackson Reeves, Ashlyn Celichowski, Elizabeth Morgan

Chancellor’s Honors Program Projects

No abstract provided.

Radiological Assay Of Burrowing Animals, James F. Pierce Mr, Jolyne Worthy Ms, Kip Wheeler Mrs, Evan Godbehere Mr

Chancellor’s Honors Program Projects

No abstract provided.

Principles Of Tomographic Measurements And Reconstruction, Bernadette Evelyn Brezinski

Masters Theses

X-ray computed tomography (CT) plays a crucial role in enhancing national security through its use in active interrogation of any miscellaneous object across various environments. The use of x-ray active interrogation can give insight on the structure of an object and its material density to provide an effective means of detecting potential threats in a wide range of objects. A small and lightweight portable CT device that can address highly sensitive inputs is constructed to perform active interrogation. Preprocessing analysis is performed to calibrate for irregularities in pixel values, detector current, tilt corrections, and more. Full image acquisitions are obtained …

Post-Layout Evaluation Of Adiabatic Logic For Energy Efficiency And Cpa Resistance, Jun-Cheng Chin

Masters Theses

The Internet of Things (IoT) has become commonplace in society, but it has been demonstrated that many IoT systems are vulnerable to significant security exploits. This necessitates the need for a closer examination of IoT security. IoT design prerequisites are low power consumption and an emphasis on smaller die areas for increased production yield. Security on the software level typically provides adequate protection but there are hardware-level exploits that are difficult or impossible to counteract. Booting attacks, eavesdropping and interference, and Side-Channel Attacks (SCA) are exploits deployed against IoT devices on the hardware level. To combat these vulnerabilities, several lightweight …

Genetic Algorithm Optimization Of Experiment Design For Targeted Uncertainty Reduction, Alexander Amedeo Depillis

Masters Theses

Nuclear cross sections are a set of parameters that capture probability information about various nuclear reactions. Nuclear cross section data must be experimentally measured, and this results in simulations with nuclear data-induced uncertainties on simulation outputs. This nuclear data-induced uncertainty on most parameters of interest can be reduced by adjusting the nuclear data based on the results from an experiment. Integral nuclear experiments are experiments where the results are related to many different cross sections. Nuclear data may be adjusted to have less uncertainty by adjusting them to match the results obtained from integral experiments. Different integral experiments will adjust …

Mapping Arbitrary Spiking Neural Networks To The Ravens Neuroprocessor, Jongheon Park

Masters Theses

In neuromorphic computing, a hardware implementation of a spiking neural network is used to provide improved speed and power efficiency over simulations of the networks on a traditional Von Neumann architecture. These hardware implementations employ bio-inspired architecture usually consisting of artificial neurons and synapses implemented in either analog, digital, or mixed-signal circuits. Since these hardware spiking neural networks are designed to support arbitrary networks under the constraints imposed by the available hardware resource, they have to be programmed by off-chip software with awareness of those constraints. The TENNLab research group at the University of Tennessee, Knoxville has recently developed the …

Utendo Sleeve- A Tendon To Muscle Fixation Device, Sarah Miller

Chancellor’s Honors Program Projects

No abstract provided.

Characterization Of Ceramic Powders Through Powder Rheology, Samuel Weimer

Doctoral Dissertations

Frequently in the literature, it has been shown that any single characterization technique is incapable of sufficiently describing the overall rheology properties of a powder. Consequently, much work has gone into exploring multivariate relationships between common rheological tests. However, such efforts have been primarily focused on powders used in pharmaceutical and food industries. Much less rheology work has been conducted for powders of other industries, such as ceramic powders used in making grinding media and crucibles. Yet, it has been shown that supplementing particle size distribution and chemical composition measurements of ceramic powders with powder rheology techniques can greatly increase …

Design And Develop Lignin Based Recyclable Copolymers For Hydrophobic Coatings, Di Xie

Doctoral Dissertations

Due to the abundance, renewability, biodegradability, overall hydrophobicity, good compatibility with cellulose, and anti-UV/oxidant abilities, lignin has great application potentials in hydrophobic coatings on cellulose-based substrates. However, lignin's structural heterogeneity and rigidity challenge its value-added utilization. Herein, Kraft lignin (KL), from paper mills, is fractionated into more homogeneous fractions (FL), nanosized into lignin micro-nanospheres (LMNS), chemically modified and copolymerized with other constituents to fabricate hydrophobic coating materials with improved coating performances.

To investigate structure-property relationships of lignin-based copolymers, solvent fractionation is conducted to obtain FLs with different molecular weight (MW) and hydroxyl (OH) contents to prepare copolymers by integrating with …

Development And Feasibility Studies Of Ai-Powered Socially Assistive Robotics To Promote Wellbeing Of Persons With Alzheimer’S Disease And Related Dementias, Fengpei Yuan

Doctoral Dissertations

The number of persons living with Alzheimer's Disease and Related Dementias (PLWDs) has been keeping growing. In 2024, it is estimated that there will be approximately 6.7 million individuals living with Alzheimer's Dementia. This number will increase to about 14 million in 2060. Due to the damage in neurons, the capabilities of memory, thinking, and language will decline as the disease progress. As a result, persons with dementia will gradually withdraw from their social activities and become more dependent on others during their activities of daily living. Making it worse, our society is not ready for the increasing requirements of …

Feature Interaction Selection For High-Dimensional Experimental Data, Di Bo

Doctoral Dissertations

In a material development process, discerning the effect of material properties and their interactions on material behaviors is critical to achieving the desired functionality of a material. This causal analysis often involves a small experimental dataset arranged in a high dimension and is challenged by the curse of dimensionality. Feature selection can alleviate such a challenge by producing a short list of features that are significant, but identifying significant feature interactions is very challenging. In this proposal, we propose a couple of approaches that can evaluate and determine important interactions, including a randomized subspace-based model (RSM), feature subspace selection (FSS), …

Cmos-Memristive Neuromorphic Architecture For Nonlinear Signal Processing, Manu Rathore

Doctoral Dissertations

Neuromorphic computing mimics the functional components and structure of the human brain to achieve highly efficient computing with minimal resources and power consumption. Creating neuromorphic systems in Complementary Metal-Oxide-Semiconductor (CMOS) technology offers an alternative computing paradigm to Von neumann computing. However, implementing these systems on an CMOS Integrated Circuit (IC) poses major challenges. These challenges include implementing synaptic weight multiplication and weight tuning operation that conserves energy and occupies minimal area. Additionally, designing a network-on-chip architecture that is reconfigurable and offers a full-connectivity design space is crucial. Furthermore, implementing a complete architecture for nonlinear data processing and, specifically, online learning …

Multi-Objective Radiological Analysis In Real Environments, David Raji

Doctoral Dissertations

Designing systems to solve problems arising in real-world radiological scenarios is a highly challenging task due to the contextual complexities that arise. Among these are emergency response, environmental exploration, and radiological threat detection. An approach to handling problems for these applications with explicitly multi-objective formulations is advanced. This is brought into focus with investigation of a number of case studies in both natural and urban environments. These include node placement in and path planning through radioactivity-contaminated areas, radiation detection sensor network measurement update sensitivity, control schemes for multi-robot radioactive exploration in unknown environments, and adversarial analysis for an urban nuclear …

Exploration Of Event-Based Camera Data With Spiking Neural Networks, Charles Peter Rizzo

Doctoral Dissertations

Neuromorphic computing is a novel, non-von Neumann computing architecture that employs power efficient spiking neural networks on specialized hardware. Taking inspiration from the human brain, spiking neural networks are temporal computation units that propagate information throughout the network via binary spikes. Compared to conventional artificial neural networks, these networks can be more sparse, smaller in size, and more efficient power-wise when realized on neuromorphic hardware. Event-based cameras are novel vision sensors that capture visual information through a temporal stream of events instead of as a conventional RGB frame. These cameras are low-power collections of pixels that asynchronously emit events over …

Development Of Novel Cesium Chloride-Based Ultrafast Inorganic Scintillators For Fast Timing Radiation Detection Applications, Daniel Rutstrom

Doctoral Dissertations

Cs₂ZnCl₄ [dicesium zinc tetrachloride] and Cs₃ZnCl₅ [tricesium zinc pentachloride] are relatively new scintillator materials that appear to be promising for use in fast-timing radiation detection applications owing to their 1 to 2 nanosecond decay times. Moreover, they offer several advantages over the state-of-the-art ultrafast inorganic scintillator BaF₂ [barium fluoride]. To fully realize the potential of these novel materials, growth of crystals having improved optical quality must be demonstrated. The mechanism responsible for the ultrafast decay times, core valence luminescence (CVL), in cesium zinc chloride crystals can also be observed in other compounds containing …

A Pattern Matching Algorithm For Self-Adjusting Basal Rates In Insulin Pump Systems, Lauren Smith

Doctoral Dissertations

In a Type 1 Diabetic, Insulin can be administered in a pump system. There are two types of insulin that must be given: basal and bolus. Basal insulin is a long-acting form of insulin that works in the background while fasting, while Bolus insulin is rapid/short acting given in response to food to immediately begin working to lower blood sugar.

Modeling in Diabetes can be represented by algorithmic approaches ranging from simple autoregressive models of the Continuous Glucose Monitor time series to multivariate nonlinear regression techniques of machine learning. Other examples of modeling in Diabetes include prediction models of hypoglycemia …

The Role Of Grain Morphology And Individual Grain Fracture On Granular Material Behavior, Anne Katherine Turner

Doctoral Dissertations

Granular materials, such as sand, are multi-scale materials combining an immense number of crushable particles to create an assembly. Numerical approaches to modeling sand’s mechanical behavior often use simplifications, such as treating the volume as a continuum or representing the particles with rigid, idealized spheres using the discrete element method. These approaches overlook crucial nonlinear phenomena, such as individual grain morphology and fracture, which have been shown to influence sand’s strength and plasticity behavior. This research investigated methods to incorporate such phenomena , focusing on simulating single grain crushing tests and 1D confined compression of Ottawa sand using finite element …

Discrete Time State-Space Modeling Framework For Switched-Mode Power Supplies, Jared Baxter

Doctoral Dissertations

Electrical power consumption has become ever prominent in modern society. Switch mode power supplies, now more than ever, have become a foundation for residential, commercial, and industrial electrical needs. These demands require numerous advanced power converters, and modeling plays a vital role in the design of these converters. Commonly, modeling is completed using either dedicated hand analysis, which must be completed individually for each topology, or time-stepping circuit simulations, which are insufficiently rapid for broad analysis considering a wide range of potential designs or operating points. Discrete time state-space modeling of switching converters has shown merits in rapid analysis and …

The Development And Enhancement Of A Forward Mathematical Model Of The Human Knee Joint, Seth Coomer

Doctoral Dissertations

Degenerative joint disease, or osteoarthritis, is a common occurrence in the knee joint. This can often result in joint pain, decrease in range of motion, and ultimately disability. One way to counteract osteoarthritis is the incorporation of a total knee arthroplasty (TKA). TKAs replace the damaged bone and soft tissue surrounding the knee with metal and polyethylene components. Ideally this will improve the joint’s performance and reduce pain. However, there is still a number of TKA patients who remain dissatisfied. In order to investigate this, in depth research must be done on the design and performance of TKAs.

One such …

Development Of Supg And Stabilized Finite Element Method Solvers For The Two Fluid Plasma Model, Kenneth A. Croft

Doctoral Dissertations

This dissertation describes efforts to employ stabilized finite element method approaches to simulate ideal two fluid plasma dynamics. First, the streamline-upwind/Petrov-Galerkin (SUPG) finite element method, which is well developed and known to be applicable to models containing terms like those in the ideal two fluid plasma model, is employed. Then, in an attempt to address some shortcomings found in that approach, another stabilized finite element method is developed along similar lines, starting from a steady state advection-reaction equation rather than a steady state advection-diffusion equation as was done in the development of the SUPG method. The performance of the SUPG …