Engineering Commons^™

Physics-Guided Scan Paths Optimization For Controlled Microstructure In Laser Powder Bed Fusion, Augustine Twumasi

Open Access Theses & Dissertations

Laser Powder Bed Fusion (L-PBF) is a renowned additive manufacturing technique, celebrated for its capability to construct intricate metal components with remarkable precision. However, one of the main challenges with L-PBF is the formation of complex microstructures, which can significantly impact the final material properties. To address this issue, our study proposes a physics-guided and machine-learning-aided approach to optimize scan paths for achieving desired microstructure outcomes, such as the generation of equiaxed grains that enhance material properties. By using phase-field modeling, a physics-based computational method, we gain insights into microstructure evolution. To reduce computational costs, we train a surrogate machine-learning …

Selective Transfection Of A Transferrin Receptor-Expressing Cell Line With Dna-Lipid Nanoparticles And Synthesis Of Parasite-Derived Glycans As Biomarkers For Leishmaniasis, Irodiel Vinales Lozano

Open Access Theses & Dissertations

Despite notable progress in lipid nanoparticle (LNP)-mediated gene delivery, achieving selective transfection of specific cell types, such as cancer cells, remains a significant hurdle, hindering the advancement of innovative gene therapies. In this study, we engineered an LNP formulation encapsulating plasmid DNA (pDNA) encoding the monomeric Green Lantern (mGL) fluorescent reporter protein. The DT7 peptide ligand targeting human transferrin receptor 1 (hTfR1) was also conjugated to the LNP surface for targeted delivery to hTfR1-expressing cells. Optimization of LNP composition yielded favorable particle diameter, ζ-potential, yield, and pDNA encapsulation efficiency. Evaluation of transfection selectivity using a panel of two engineered cell …

Smart Public Transportation And Mobility Hub Design In El Paso, Jiri Vojtisek

Open Access Theses & Dissertations

This thesis explores the potential of a Smart Public Transportation concept and mobility hub design as tools to mitigate the growing trend of transportation issues, such as traffic congestion, reliance on privately owned vehicles, or unattractive public transportation. Consequently, residentsâ?? lives are negatively affected by excessive noise, air pollution, and travel delays, leading to increased safety risks, lost productivity, and a lower quality of life. Considering these challenges, the study begins by analyzing the current state of public transportation in El Paso. Next, it introduces a toolkit from the Smart City concept, followed by case studies of best practices of …

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.

Gamification Of Speech Therapy With Pronunciation Pal, Parker Zbylut

Theses/Capstones/Creative Projects

This capstone report examines the theory and implementation behind applying game design principles to educational applications, and explores their implementation in an educational game through the Pronunciation Pal application. The gamification of learning tools aims to increase learners' engagement and attentiveness with a subject by restructuring content using game design principles of challenges, rewards and feedback. Feedback can be delivered via visuals and/or sounds, as well as regular indicators of player progress and accomplishment. In addition, a successful game implementation establishes challenges to facilitate a player's intrinsic desire to continue playing and improving at the skills presented by the game. …

The Role Of Voluntary Descending Control In Enhancing Motor Function Via Transcutaneous Spinal Cord Stimulation, Yoon Kim

McKelvey School of Engineering Theses & Dissertations

Spinal cord injury (SCI) is a life-changing event that causes lasting motor impairments. Transcutaneous spinal cord stimulation (tSCS), a non-invasive form of neuromodulation in which electrodes are placed on the skin and used to stimulate the spinal circuits via an electrical current, has demonstrated positive effects on motor function recovery in individuals who have had SCIs. However, the precise mechanism of how tSCS interacts with voluntary descending drive remains poorly understood. This study aims to investigate the role of voluntary descending control in influencing reflex responses triggered by tSCS.

Electromyography (EMG) recordings were performed in ten unimpaired individuals while they …

Development Of A Wearable Short-Wave Infrared Photoplethysmography Device For Detection And Monitoring Of Hemodilution During Postpartum Hemorrhage, Hannah Gruensfelder

McKelvey School of Engineering Theses & Dissertations

ABSTRACT OF THE THESIS

A Thesis on the Development of a Wearable Short-Wave Infrared Photoplethysmography Device for Detection and Monitoring of Hemodilution During Postpartum Hemorrhage

by

Hannah Gruensfelder

Master of Science in Biomedical Engineering

Washington University in St. Louis, 2024

Professor Christine O’Brien, Chair

Postpartum hemorrhage (PPH), the leading cause of maternal death and morbidity, affects nearly 14 million people worldwide each year, disproportionally impacting racial minorities and people in low resource settings. A timely diagnosis of PPH is key in providing optimal patient care, as an estimated 90% of deaths due to PPH are preventable with early diagnosis and …

Environment And Response Of 3d-Encapsulated Mesenchymal Stem Cells To Mechanical Loading, Augustus Greenwood

McKelvey School of Engineering Theses & Dissertations

This thesis explores the micromechanical environment induced when cyclically compressing hydrogels via finite element modeling and experimentally on the impact of loading on mesenchymal stem cells (MSCs) when encapsulated withing 3D hydrogel matrices. Degenerative joint diseases, characterized by cartilage degradation, present significant challenges due to cartilage's limited self-repair capacity. Innovative approaches, including stem cell-based therapies and engineered biomaterials, have emerged as promising strategies for cartilage repair and regeneration. This work specifically investigates the calibration of a bioreactor, the uniformity of load response across the hydrogel constructs via finite element modeling (FEM), and the stress response of MSCs subjected to various …

Modeling Of Nk Cells In Pediatric Patients With Unusually Severe Or Recurrent Hsv Using High-Dimensional Flow Cytometry, Yunran Feng

McKelvey School of Engineering Theses & Dissertations

HSV infection is broadly spread all over the world with some patients having severe and/or recurrent HSV infections. Our lab studies human Natural Killer (NK) cells, which are important in innate immune responses to viral infections and tumors. A publication in 2013 by Ornstein et al from our lab studied HSV+ pediatric patients and found some associations between severe infection and defects in NK cytolytic function. PLCG2 haploinsufficient variants found in 2 HSV patients causing PLCγ2 hypophosphorylation, and loss of cytolytic function in NK cells is a novel finding recently published by Alinger et al from our lab in 2023. …

Ai-Powered Information Retrieval In Meeting Records And Transcripts Enhancing Efficiency And User Experience, Srushti Nitin Ghadge

Theses and Dissertations

This study compares the traditional search methods, which is to search from video recordings of the meetings by moving the slider back and forth or by keyword search in transcripts versus integrated AI video plus transcript search. Based on the previous test results, we introduced some human-centric design features to the AI and built a new enhanced AI search tool for information retrieval. For search technique efficiency testing, the method had two set of experiments. The first results of the experiment showed that AI-based search algorithms were more accurate and faster than conventional search approaches. Participants were also happier with …

Computational Fluid Dynamics Study Of Perforated Monopiles, Mary Kathryn Walker

Theses and Dissertations

Monopiles are used in the construction of offshore wind turbines and typically have a design life of 25 to 50 years. Over their lifecycle, monopiles are exposed to a corrosive saltwater environment, facilitating a galvanic oxidation process that quickly degrades the structure. This process can be mitigated by coating the monopile in a protective barrier and implementing cathodic protection techniques. Historically, monopile designers assumed the interior of the pile would be completely sealed and the galvanic corrosion process would eventually consume all the available oxygen, halting the reaction. However, penetrations made in the pile wall for conduit often leaked and …

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 …

Geomagnetic Substorms Prediction Model Using Combined Physics-Based And Deep Learning Modeling Techniques, Ruthba Yasmin

<strong> Theses and Dissertations </strong>

This thesis aims to develop a hybrid physics-incorporated neural network model (PINN) for classifying geomangnetic substorms in Earth's Magnetosphere. The model is trained using a comprehensive list of substorm onsets, ground magentometer data from a global network, and solar wind parameters from the Advanced Composition Explorer (ACE) satellite. Two different neural network architectures are used, and the physics model used for training is called WINDMI. The magnetic field components on the ground, which are a function of the ionospheric currents, are captured by the SML index. The methodology involves using 60-minute data segments preceding an event to train the hybrid …

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

Chancellor’s Honors Program Projects

No abstract provided.

Understanding Peer Interactions In Undergraduate Engineering Education, Jack C. Elliott

All Graduate Theses and Dissertations, Fall 2023 to Present

Whether they occur inside or outside the classroom, social interactions between undergraduate students play a key role in student success. As a result, engineering education researchers have sought to understand why students interact with certain peers, and which types of interactions relate to positive student outcomes. While existing studies show promising results for formal group assignments, most have been conducted in a single undergraduate course. Because important student interactions occur outside and inside courses, more research is needed to fully understand (a) why students choose to, or not to, interact with other students, and (b) how these interactions relate to …

Development, Modeling, Identification, And Control Of Tilt-Rotor Evtol Aircraft, Clayton T. Spencer

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis includes the development, modeling, identification, and control of an electric-Vertical-Take-Off-and-Landing (eVTOL) aircraft with tiltable rotors. The front two rotors have tilting capability for transition flight from vertical-take-off to forward-level flight. This work details the development of an eVTOL aircraft and the selection of sub components such as electric motors, batteries, and controllers. After the aircraft build, mathematical model is derived to describe the motion of the aircraft. Unknown parameters in the mathematical model are identified using a Least-Squares-regression (LSR) method that can handle parameter constraints. This is done using real flight data collected from the aircraft. Lastly, this …

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 …