Engineering Commons^™

Peroxi-Electrocoagulation For Pfas Mitigation: The Impact Of Water Quality And Dissolved Organic Matter On Removal Pathways, Donald R. Ryan, Claire K. Baldus, Shimaa M. Kteeba, Melvin Samuel, Yin Wang, Laodong Wang, Brooke K. Mayer, Patrick J. Mcnamara

Civil and Environmental Engineering Faculty Research and Publications

The recent addition of per- and polyfluoroalkyl substances (PFAS) to the National Primary Drinking Water Regulation per- has increased the need for research on PFAS treatment technologies for water and wastewater. Electrochemical treatment processes have been widely investigated for PFAS removal. Peroxi-electrocoagulation (electrocoagulation paired with hydrogen peroxide (EC:H₂O₂)) was evaluated as a novel water treatment process for PFAS mitigation due to the multimechanistic removal pathways that can proceed during treatment, including chemical degradation via oxidation, and physical separation pathways such as sorption to flocs, flotation layer accumulation, and foam fractionation. This work investigated the impacts of …

Evaluating Environmental And Economic Sustainability Of Engineered Chitosan Particles For Water Treatment, Fatima Iqbal, Astha Upadhyay, Rouzbeh Tehrani, Stetson Rowles

Civil Engineering & Construction: Faculty Publications

The global water demands have prompted the development of sustainable treatment solutions, with adsorptive chitosan composites emerging as promising alternatives to petroleum-based materials. As a cleaner material, chitosan offers significant advantages over conventional adsorbents, including biodegradability, biocompatibility, and the potential to create a circular economy in water treatment applications. This study presents a comprehensive sustainability assessment of three novel porous chitosan particles synthesized using low-toxicity solvents, focusing solely on the production of pure chitosan scaffolds without additional adsorptive materials for targeted removal. Integrating techno-economic analysis and life cycle assessment, we evaluate the economic viability and environmental impact of methylpentane, azocarboxamide, …

Household Point-Of-Use Faucet Filters For Lead Removal: Field Performance And User Experiences, Jeannie M. Purchase, Chantaly Villalona, Adrienne Katner, Kelsey Pieper, Marc Edwards

School of Public Health Faculty Publications

Lead certified point of use (POU) faucet filters were field tested in two Louisiana cities in a total of 21 occupied homes during normal use and in two unoccupied homes with very high risk of water lead (Pb) contamination. In an unoccupied home with a 28 m lead service line (LSL) with average lead of 17 μg/L in flushed water, treatment by POU filters generally produced water with < 5 μg/L Pb even when tested to 200% of rated capacity. In the unoccupied home with a disturbed LSL, the water had erratic influent particulate lead of 9-3053 μg/L, and the POUs did not consistently produce water with < 10 μg/L Pb despite very high percentage removals. When testing POUs in occupied homes known to occasionally have lead over 5 μg/L, POUs always reduced lead to < 1 μg/L. In addition, POUs were also effectively removing high levels of iron and manganese present in the water of one city, but this also caused clogging before reaching half of their rated capacity. Laboratory experiments confirmed POU susceptibility to iron clogging.

Untethered Isoperimetric Robotic Truss For Lunar Applications, Mihai Stanciu, Spencer Stowell, Isaac Weaver, Adam Rose, Chris Paul, James Wade, Ashleigh Cerven, Annie O'Bryan, Brian Bodily, Logan Yang, Nathan Usevitch

Faculty Publications

We introduce a robotic system designed to function as a lightweight, modular, and reconfigurable structure on the Moon. This robust system consists of truss-like robotic triangles, each formed by a continuous inflated fabric tube routed through two robotic roller units and a connecting unit. When deflated, these triangles can be compacted to roughly the volume of the roller units, offering an advantageous stowed-to-deployed volume ratio of 1 to 6.24. Upon inflation, the roller units pinch the tubes, creating corners by reducing the bending stiffness of the tube. Once fully deployed, electric motors move the robotic roller units along the tube, …

Nasa Design And Analysis Of Pegda Hydrogels For Microgreen Cultivation In Space, Fabiha Samiha, Luis E. Luna, Kelly Wu, Gabriel Antigua, Artur Abramyan

Publications and Research

Through multiple experiments, Polyethylene Glycol Diacrylate (PEGDA), a biocompatible polymer, has shown potential as a soilless growing medium for microgreens like arugula. However, a challenge arises when the roots run out of space within the hydrogel capsule, pushing the plant out of position and preventing it from absorbing nutrients from the PEGDA.

This study aims to address this challenge by analyzing different 3D-printed mold designs for the creation of the hydrogel capsules. The most promising designs include coil and tree-branch models, which encourage roots to grow in a way that relieves pressure on the leaf side of the plant, helping …

The Crystal Mountain Fluorite Deposit: Scandium-Rich Mineralization And Geochronology, Natalie Kilanowski-Doroh

Graduate Theses & Non-Theses

The Crystal Mountain fluorite mine is located in the Sapphire Mountains of the Bitterroot National Forest, near Darby, Montana. Crystal Mountain was a significant US producer of high-purity fluorspar between 1952 and 1972. As well, the deposit is rich in yttrium (Y) and scandium (Sc), and could possibly be a domestic source of these critical metals. The ore occurred as lodes of massive fluorite up to 10 m thick and 100 m long (now mined out), with few other associated minerals. Recent studies have speculated that Crystal Mountain may be a rare example of a magmatic fluorspar deposit. The main …

Development Of Predictive Maintenance For Centrifugal Pumps, Elliot B. Lange

Honors Capstones

Over prolonged periods of time, mechanical machinery requires regular maintenance to ensure optimal performance. Conventionally this maintenance is done on a regular schedule with predefined procedures to repair all aspects of the machine. As machine learning models become more applicable in everyday life, these algorithms can be leveraged to predict failures in mechanical devices. This project worked toward creating a predictive maintenance machine learning model for centrifugal pumps that can identify and predict discrete failure modes. As a result of the project, a pump loop setup was constructed. The purpose of this report is to provide a guide for how …

Design And Development Of A Stethoscope Attachment For Instant Heart Murmur Detection, Caitlin K. Cherwin, Dillon Desai

Honors Theses

Heart murmurs are critical indicators of potential cardiovascular conditions yet their detection can often go unnoticed due limitations in equipment and is dependent on clinician experience. Cardiovascular disease remains a leading cause of death worldwide, therefore, early detection of heart murmurs play a crucial role in improving patient outcomes. Many established methods of detection are expensive and often unreliable allowing there to be room for a device which is more cost and result effective. This paper presents the development of a device that attaches onto a regular stethoscope and analyzes auscultatory sounds to diagnose the possibility of a present murmur. …

Benefits And Applications Of Learning With Virtual Reality, Michael W. Timm

Honors Program: Senior Projects (Public)

Education is a fundamental pillar of society. It equips students for employment and interpersonal relations. Virtual reality (VR) has emerged as a transformative technology in the field of education. The aim of this paper is to synthesize existing research in order to determine the benefits of utilizing virtual reality in a variety of education settings, such as K-12 classrooms, universities, and workplace training. This paper observes significant benefits of virtual reality in constructivist and experiential learning, gamified learning, and tailored practice. This analysis also finds that virtual reality is advantageous for educational accessibility, particularly for absentee students and impoverished students. …

Computational Fluid Dynamics Analysis Of A Turbine Blade, Luis Luna, Fabiha Samiha

Publications and Research

In Aerospace engineering, the use of computer-aided design (CAD) software, such as SolidWorks, is crucial when designing and validating high-performance parts. SolidWorks provides a valuable tool for simulating computational fluid dynamics (CFD), allowing engineers to analyze and visualize how parts behave under real-world aerodynamic conditions.

One such part is a turbine blade, an airfoil-shaped component inside a jet engine that compresses and redirects airflow to generate thrust. This study aims to perform aerodynamic testing of a single turbine blade design while evaluating SolidWorks' ability to simulate external flow conditions. By visualizing velocity profiles, pressure distribution, and vortex formation, the simulation …

Ecodrone: Autonomous Environmental Monitoring, Belsen Lee

Student Scholar Symposium Abstracts and Posters

This project presents EcoDrone, an autonomous aerial drone designed for continuous and automated environmental monitoring. Current environmental monitoring methods rely on stationary sensors or manual data collection, limiting real-time response capabilities. This reliance leads to delayed, incomplete, and spatially limited data and restricts the ability to capture real-time changes. Another challenge includes the difficulty of environmental monitoring in challenging terrain, whether it be wildfire areas, dense forestry, or mountainous terrain. EcoDrone overcomes these challenges by autonomously navigating difficult terrain to collect real-time data, offering more flexible and timely monitoring than stationary or manual methods. The central research question investigates integrating …

New Signal Identification Algorithms For Enhanced Gamma-Ray Burst Detection In The Advanced Particle-Astrophysics Telescope, Longhao Huang

McKelvey School of Engineering Graduate Student Theses & Dissertations

This work presents a series of algorithmic advancements aimed at improving photon signal identification and gamma-ray burst (GRB) source localization for the Advanced Particle-astrophysics Telescope (APT) and its Antarctic Demonstrator (ADAPT). These advancements are aimed at identifying valid signals in noisy environments. Previous methods failed to effectively distinguish real photon signals from noise, prompting us to develop a new photon detection algorithm with peak counting. Instead of integrating all waveform data in the observation window, we use multiple thresholds to accurately identify single-photon and two-photon arrival events, minimizing false counts due to amplifier noise. The new peak count algorithm also …

The Role Of Piezo1 In Mediating Chondrocyte Cell Signaling And Senescence, Sophie Gretler Paradi

McKelvey School of Engineering Graduate Student Theses & Dissertations

Osteoarthritis (OA), the leading cause of disability, is driven by articular cartilage degeneration and inflammation. Mechanosensitive ion channels PIEZO1 and PIEZO2 have been implicated in OA progression via calcium signaling in chondrocytes. This study investigates the role of conditional Piezo channel knockout (cKO) in modulating calcium signaling and senescence in OA, particularly under the supra-physiologic inflammatory condition of a high-fat diet (HFD). Using calcium imaging, we found that Piezo1 cKO and dual Piezo1/2 cKO significantly reduced Yoda1-induced calcium signaling, while Piezo2 cKO alone had no effect. Under HFD conditions, Piezo1 cKO showed a non-significant trend toward reduced calcium influx, potentially …

Structural Controllability For Switched Linear Ensemble Systems, Yi Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

No abstract provided.

Towards The Performance Characterization Of A Robotic Multimodal Diagnostic Imaging System, George Papaioannou, Christos Mitrogiannis, Mark Schweitzer, Nikolaos Michailidis, Maria Pappa, Pegah Khosravi, Apostolos Karantanas, Sean Starling, Christian Ruberg

Publications and Research

Characterizing imaging performance requires a multidisciplinary approach that evaluates various interconnected parameters, including dosage optimization and dynamic accuracy. Radiation dose and dynamic accuracy are challenged by patient motion that results in poor image quality. These challenges are more prevalent in the brain/cardiac pediatric patient imaging, as they relate to excess radiation dose that may be associated with various complications. Scanning vulnerable pediatric patients ought to eliminate anesthesia due to critical risks associated in some cases with intracranial hemorrhages, brain strokes, and congenital heart disease. Some pediatric imaging, however, requires prolonged scanning under anesthesia. It can often be a laborious, suboptimal …

Review Of Tethered Unmanned Aerial Vehicles: Building Versatile And Robust Tethered Multirotor Uav System, Dario Handrick, Mattie Eckenrode, Junsoo Lee

Faculty Publications

This paper presents a comprehensive review of tethered unmanned aerial vehicles (UAVs), focusing on their challenges and potential applications across various domains. We analyze the dynamic characteristics of tethered UAV systems and address the unique challenges they present, including complex tether dynamics, impulsive forces, and entanglement risks. Additionally, we explore application-specific challenges in areas such as payload transportation and ground-connected systems. The review also examines existing tethered UAV testbed designs, highlighting their strengths and limitations in both simulation and experimental settings. We discuss advancements in multi-UAV cooperation, ground–air collaboration through tethers, and the integration of retractable tether systems. Moreover, we …

Learning-Based Mri Reconstruction Method With Coil Sensitivity Estimation And Prior Adaptation, Haoyu Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Magnetic Resonance Imaging (MRI) reconstruction from undersampled multi-coil k-space data is a challenging inverse problem, typically relying on fixed priors such as precom puted coil sensitivity maps. To improve adaptability, we propose a novel framework named Learning-based Coil sensitivity Estimation and Prior Adaptation (LCEPA). LCEPA formu lates reconstruction as a bilevel optimization, using a Joint Deep Equilibrium (Joint DEQ) model in the inner loop to simultaneously estimate images and coil sensitivity maps, while the outer loop adaptively fine-tunes image and coil priors using supervised data. Experiments demonstrate that LCEPA surpasses state-of-the-art methods in terms of PSNR and SSIM, showcasing robust …

Automated Beam Stitching And Segmentation Procedure For Space Division Multiplexing Optical Coherence Tomography Angiography, Andrew J. Song

McKelvey School of Engineering Graduate Student Theses & Dissertations

Optical Coherence Tomography Angiography (OCTA) has revolutionized ophthalmic imaging and its capability to produce high-resolution 3D maps of the retinal microvasculature is instrumental in diagnosing retinovascular diseases such as diabetic retinopathy and age-related macular degeneration; However, the existing OCTA devices often suffer from slow acquisition speed limiting the field-of-view (FOV) in the clinic. Space Division Multiplexing OCTA (SDM-OCTA) address these limitations by acquiring multiple beams simultaneously, achieving manyfold faster acquisition speeds than single beam OCTA systems. But as each beam contains only part of the image, SDM-OCTA requires additional processing steps to produce coherent wide-field images. Though manual stitching and …

Comparative Analysis Of Intrinsic Reward-Based Reinforcement Learning Algorithms, Chengyu Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

Reinforcement learning agents often struggle in tasks with sparse or delayed rewards, since they receive little guidance about which actions to pursue. This thesis investigates how adding intrinsic rewards can help address that issue. We focus on three main methods: Count-Based bonuses, where states are hashed and infrequent states receive higher rewards; Random Network Distillation (RND), where a predictor network learns to match the output of a fixed random target; and the Intrinsic Curiosity Module (ICM), which uses an inverse and a forward model to highlight transitions the agent cannot yet predict.

We implement these approaches under a single Proximal …

Functional Devices Based On Freestanding 2d Materials, Shijue Xu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Two-dimensional (2D) materials have attracted extensive attention in the field of nanoelectronics due to their atomic-scale thickness, high surface-to-volume ratio, tunable electronic properties, and compatibility with low-temperature processing. These characteristics make them highly suitable for the construction of emerging device architectures, particularly in both ionic and electronic devices.

In this work, we investigate the application of 2D materials in two distinct classes of devices: ionically-driven memristors and electronically-dominated metal–semiconductor contacts. For the memristor study, we fabricate heterostructure-based resistive switching devices using h-BN and WSe₂ as active layers. These 2D material-based memristors exhibit stable power consumption loops and high linearity …

Soft, Adhesive Dry Electrodes For Improved Electrophysiological Signal Acquisition With Motion Tolerance And Long-Term-Recoverability, Ryan Andersen

McKelvey School of Engineering Graduate Student Theses & Dissertations

Soft electronic devices and sensors have seen substantial interest devoted to them for the purpose of recording and analyzing various electrophysiological signals including for the use of electrocardiography (ECG), electromyography (EMG), and electroencephalography (EEG). Dry electrodes specifically have enormous potential compared to traditional commercial electrodes for long-term, real-time monitoring of biopotential activity. Gel-based commercial electrodes have notable drawbacks such as limited flexibility, skin irritation that decreases comfort, inconsistent signal quality due to poor conformal contact, and degraded signal quality over long-term monitoring due to drying out.

Herein, we report a soft, adhesive dry electrode that utilizes chemical additives to promote …

Adaptive Noise Estimation And Denoising With Deep Learning For Nmr Spectroscopy, Naveen Asokan

McKelvey School of Engineering Graduate Student Theses & Dissertations

Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful analytical technique widely used for molecular structure elucidation in chemistry, biology, and medicine. However, spectral accuracy is often degraded by noise—particularly in low acquisition time settings—resulting in reduced resolution and obscured chemical features. While traditional noise reduction techniques such as signal averaging can improve spectral quality, they require longer acquisition times, limiting their utility in real-time and high-throughput applications.

This thesis presents a deep learning-based denoising framework designed to enhance the quality of complex-valued NMR spectra. The proposed model, built upon a U-Net architecture, incorporates both real and imaginary components of the …

Generic Fpga Preprocessing For Astrophysics Instruments In Hls, Qinzhou Song

McKelvey School of Engineering Graduate Student Theses & Dissertations

FPGAs are widely deployed on high-energy astroparticle physics instruments to preprocess large volumes of streaming data from various sensors. Increasingly, these deployments are finding their way to space-borne instruments, where constraints on size, weight, and power (SWaP) require careful balancing of speed and resource utilization. Although telescope designs vary widely, they often share common preprocessing elements, including channel-level readout, pedestal subtraction, waveform integration, and zero suppression from front-end ADCs, as well as identification and centroiding of signal islands across groups of multiple channels. High-Level Synthesis (HLS) tools allow these designs to be expressed at a conceptual level, which automates a …

Partially Supervised Reinforcement Learning For Gps-Denied Navigation, Ethan Weilheimer

McKelvey School of Engineering Graduate Student Theses & Dissertations

Navigating dynamic environments is a key challenge for autonomous agents, yet most existing research focuses on 3D settings or settings where the agent has full access to relevant semantics. In this work, we propose a learning framework for aerial navigation in the presence of changing dynamics and limited positional information. Specifically, we consider a drone navigation task where a drone at one time has access to GPS location information, which it has now lost and needs to navigate in the same area but at a future time with no GPS signal and differing transition dynamics. To address this, we introduce …

Development Of Interactive Games On An Affordable Braille Display, Daniel Tsivkovski, Dylan Ravel, Maryam Etezad

Student Scholar Symposium Abstracts and Posters

Developing an affordable and STEM learning-focused Braille display addresses a significant disparity in the market for Braille displays, where most fail to provide a cost-effective, accessible, and education-oriented solution. This research aims to bridge this gap through innovative hardware and software development, offering a comprehensive learning experience to elementary school children (K-6) who are blind/visually impaired. The hardware features a piezo-electric tactile display that displays up to six Braille characters at once or a shape in an 8x8 pin array configuration. The educational software includes a user-friendly website packed with engaging STEM activities specifically designed for blind/visually impaired children. The …

Facilitating Design Of Effective, Scalable Digital Mental Health Care, Himanshu Mahesh Patil

Dartmouth College Master’s Theses

This thesis tackles the challenges of designing effective, scalable digital mental health care solutions by integrating psychological research with human-computer interaction (HCI) principles. An exploration of self-care technologies (SCTs) for mental health is conducted to highlight challenges to comparative analysis, like fragmented research outcomes. Two research questions are posed to investigate how mental health interventions can be designed to be effective and overcome practical challenges to implementation. A theoretical framework in clinical psychology is adapted to bridge the gap between psychology and HCI. A methodology for conducting standardized, structured comparative analysis of mental health interventions is identified. The identified method …

Training Safety Control Filters Using High-Dimensional And Un-Labeled Data, Yuxuan Yang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Synthesizing control policies that preserve the safety of autonomous systems is a challenge that remains to be solved. Towards that goal, control barrier functions (CBFs) have been developed as mathematical constructs that can be used in real-time to correct safety-violating nominal actions to ones which preserve the safety of control systems. However, synthesizing CBFs using correct-by-construction methods has not been scalable. Instead, recent research has proposed data-driven approaches for learning CBFs in the form of neural networks. Two main challenges face such approaches: (1) labeling states as unsafe or safe ones requires the knowledge of the states in the backward …

Strategic Reactor Allocation For Deadlock-Free Execution, Jeevan Sivamohan

McKelvey School of Engineering Graduate Student Theses & Dissertations

As it becomes harder to increase the computation power of a single machine, we are turning towards parallel and distributed systems to extract additional performance by breaking down the problem into pieces and solving it simultaneously. While this provides a great opportunity for increased performance,e it comes with additional problems not present in the sequential approach. One such problem is deadlock. Deadlock is defined as the state in which program execution stalls because the system has run out of resources to manage and execute the program properly, or there exists some circular dependency in the data between parallel or distributed …

Preliminary Study: Minimizing The Gap Between Pre-And Post-Spaceflight, Caleb E. Scheideger, Louis A. Diberardino

Aurora

Long-duration space missions pose significant challenges to astronaut health, primarily due to the detrimental effects of microgravity on musculoskeletal and cardiovascular systems. This research proposal aims to address the critical gap between pre- and post-spaceflight physiological conditions, focusing on the marked decline in muscle mass, bone density, and cardiovascular function. Existing countermeasures, such as resistive exercise, are insufficient to prevent muscle atrophy and bone demineralization, highlighting the need for novel solutions. Neuromuscular Electrical Stimulation (NMES) emerges as a promising intervention, capable of eliciting muscle contractions to maintain function and mitigate atrophy. By integrating NMES into existing exercise regimens, we hypothesize …

Praxly: An Online Ide For The Praxis Cs Test Pseudocode, Benjamin Saupp

James Madison Undergraduate Research Journal (JMURJ)

No abstract provided.