Engineering Commons^™

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 …

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 …

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 …

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 …

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 …

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 …

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.

Dynamic Analysis And Control Of A Quadruped Robotic System Based On Newton-Euler Formulation, Vyshak Sureshkumar

Thesis/ Dissertation Defenses

Despite advancements in legged robotics, comprehensive dynamic analyses remain limited in the literature. This research presents kinematic and dynamic modeling of a quadruped robot using the Newton-Euler approach to improve computational efficiency in high degree of freedom systems. The formulation leverages system over-constraints with assumed ground reaction forces and focuses on simulating two primary gait patterns: static walking and dynamic trotting. The research explores reaction wheel-based roll stabilization for a quadruped with 8 actuators, omitting the conventional Hip Abduction/Adduction (HAA) joints. This approach addresses roll control limitations by compensating for the reduced actuation. This research presents a brief overview of …

A Proposed Metals Recovery Assessment Protocol To Evaluate Mine Waste For Critical Minerals And Rare Earth Recovery Prior To Site Remediation, Claire Mbia

Graduate Theses & Non-Theses

The Metals Recovery Assessment (MRA) protocol involves collecting and evaluating information to assess the possibility for recovery of critical or rare earth minerals at mine sites to offset remediation or redevelopment costs associated with land reuse at Superfund or closed mine sites. This protocol provides a tool to implement metals recovery in conjunction with property reuse, and may involve a review of available records, visual inspections of the site, sample collection and discussions with local government officials and community members. The selection for metals recovery would be intended to both achieve metals reduction which may be required for the protection …

Unraveling The Impact Of Vessel Geometry In Resonant Acoustic Mixing, Jefferson Guthrie

Graduate Theses & Non-Theses

This study aimed to advance the understanding of ResonantAcoustic® Mixing (RAM) and its application in industrial powder processing. RAM, which consists of vertically oscillating boundaries operating at nominally 60 Hz with accelerations up to 100 g’s, is particularly effective for mixing fine powders and materials. RAM is able to complete mixing processes 10 to 100 times faster than traditional methods without the risk of cross contamination. Despite RAM’s growing potential, the underlying mechanisms of RAM are not fully understood, limiting its optimization and broader adoption. Research in this study sought to bridge existing gaps in understanding by investigating the influence …

How Extreme Rainfall And Failing Dams Unleashed The Derna Flood Disaster, Ayman Mokhtar Nemnem, Ahad Hasan Tanim, Audrika Nahian, Sadik Khan, Erfan Goharian, Jasim Imran

Faculty Publications

On September 11, 2023, Storm Daniel unleashed unprecedented rainfall over the Wadi Derna watershed, triggering one of the most devastating floods in modern history, striking Derna, a coastal city in Libya. This study reconstructs the disaster using an integrated modeling approach that combines satellite imagery, hydrologic, hydraulic, and geotechnical simulations, machine learning, eyewitness accounts, and digital elevation data to assess the impact of cascading dam failures. Our findings reveal that the region’s dams, even if structurally sound, would have provided minimal protection against the extreme runoff. However, their failure unleashed a destructive surge wave, amplifying the disaster’s magnitude and devastation. …

Gradient Fibro-Porous Materials For Tailored Sound Absorption, William Johnston, Janith Godakawela, Bhisham Sharma

Michigan Tech Publications

Reducing the pore size of bulk sound absorbers often increases weight and introduces manufacturing challenges, limiting their practical use. To address these issues, a class of materials is introduced that uses 3D printing to seamlessly integrate fibers within porous scaffolds, allowing improved sound absorption performance without a significant weight addition. The reliance on 3D printing enables the creation of gradient fibro-porous structures with customizable acoustic properties. This study explores the effect of through-thickness gradients in the scaffold’s relative density, fiber thickness, and fiber density on the acoustical performance with the goal of identifying the optimal strategy to obtain broader and …

Biogenic Synthesis Of Metallic And Bimetallic Oxide Nanoparticles For Water Treatment Applications, Gunarani G.I

Theses and Dissertations

Access to clean water is a quality-of-life indicator. The availability of clean water apart from water scarcity is marred due to contamination by heavy metals and synthetic dyes, posing a grave environmental and public health challenge. This necessitates the implementation of advanced and sustainable treatment solutions towards water remediation. This research work focusses on the fabrication and application of biogenic and chemically synthesized metallic and bimetallic nanoparticles for the efficient removal of uranium, chromium, and toxic dyes from aqueous environments. The study particularly focuses on zero-valent (C-Fe and B-Fe) and bimetallic (C-NiFe and B-NiFe) nanoparticles, evaluating their adsorption capabilities and …

How Extreme Rainfall And Failing Dams Unleashed The Derna Flood Disaster, Ayman Mokhtar Nemnem, Ahad Hasan Tanim, Audrika Nahian, Sadik Khan, Erfan Goharian, Jasim Imran

Faculty Publications

On September 11, 2023, Storm Daniel unleashed unprecedented rainfall over the Wadi Derna watershed, triggering one of the most devastating floods in modern history, striking Derna, a coastal city in Libya. This study reconstructs the disaster using an integrated modeling approach that combines satellite imagery, hydrologic, hydraulic, and geotechnical simulations, machine learning, eyewitness accounts, and digital elevation data to assess the impact of cascading dam failures. Our findings reveal that the region’s dams, even if structurally sound, would have provided minimal protection against the extreme runoff. However, their failure unleashed a destructive surge wave, amplifying the disaster’s magnitude and devastation. …

Rare Earth Mineral Flotation – A Comparison Of Silicates To Oxides, Carbonates And Phosphates, Abdul Mamudu

Graduate Theses & Non-Theses

Flotation is a processing method used to separate valuable minerals from gangue minerals based on differences in hydrophobicity. When applied to ores bearing rare earth minerals (REMs) variations in rare earth element (REE) concentrations within the REMs can lead to inconsistent flotation results. Prior work at Montana Technological University examined the adsorption of collectors on the surfaces of synthetic REMs to assess recovery via flotation. Previous studies showed that the results obtained for Salicyl Hydroxamic Acid (SHA) on rare earth oxides REO), rare earth carbonates (REC), and rare earth phosphates (REP) vary depending on the coordination number (CN) and the …

Characterization Of A Magnetically Contained Hot Filament Plasma Source With A Wide-Sweeping Langmuir Probe, Jonas Rowan

Doctoral Dissertations and Master's Theses

Ionospheric plasma research in the Space and Atmospheric Instrumentation Laboratory’s Space Plasma Chamber has been hindered by the lack of a suitable plasma diagnostic instrument and understanding of its hot-filament plasma source. This thesis describes efforts made to remedy both problems. A wide-range Sweeping Langmuir Probe was developed with a ±35 V sweeping range to fully analyze ion and electron saturation regions in the entire IV curve. A method was derived to estimate the chamber source’s filament temperatures. The new Langmuir probe was integrated into a refurbished automated system designed in Python to measure plasma parameters for various chamber conditions, …

Solar Sailing Adaptive Control Around The Earth-Moon Lagrange Point L4 For Stellar Observations, Luis Mendoza Zambrano

Doctoral Dissertations and Master's Theses

To expand our knowledge about the influence of the Sun in the cislunar region, as well as our understanding of shocks due to Coronal Mass Ejections and large coronal magnetic reconnection, a solar sailing approach is proposed to separately capture lunar occultations and observe the solar corona from L₄ of the Earth-Moon system. Single and multiple shooting techniques are described along with a pseudo arc-length continuation method for preliminary orbit design. Periodic orbits in the vicinity of L₄ are obtained in the context of the Earth-Moon circular restricted three-body problem (CR3BP) and the Sun-Earth-Moon bi-circular restricted four-body problem …

Satellite Reorientation Using Reinforcement Learning Under Unknown Attitude Failure, Matthew Willoughby

Doctoral Dissertations and Master's Theses

This study presents a reinforcement learning (RL) approach for reestablishing communication with deep-space satellites under unknown attitude determination and control system (ADCS) failures. When traditional fault-tolerant control methods cannot restore signal, the proposed RL controller acts as a last-resort measure by autonomously reorienting the satellite’s antenna toward Earth while charging the battery via solar panels. A generic reward function, designed for the RL-based method, enables the controller to adapt to diverse failure scenarios, including severe actuator noise, misalignment, and complete actuator failure. Simulations are conducted in the Basilisk environment and trained with the tonic framework and demonstrate ranging capabilities of …

Soft Modular Robots: From Modular Tensegrity Structures To Bioinspired Sea Robots, Luyang Zhao

Dartmouth College Ph.D Dissertations

The rapid advancement of robotics necessitates systems capable of adapting to complex, unstructured environments. Soft robots, with their flexibility and compliance, excel in delicate interactions, making them ideal for medical applications and search-and-rescue missions. Modular robots, on the other hand, offer reconfigurability, enabling diverse task-specific adaptations in dynamic settings. Despite their individual advantages, the integration of soft and modular robotics remains underexplored. This proposal aims to develop soft modular robots that combine the adaptability of soft robotics with the versatility of modularity. These systems will be capable of autonomously transitioning between locomotion, manipulation, and infrastructure assembly across land, water, and …

Unified Evaluation Of Real-World Iot-Based Federated Learning, Yi Gu

Master's Theses

Federated learning (FL) is a novel paradigm that enables the training of a global machine learning (ML) model across distributed devices by exchanging model parameters instead of raw data in the training process. Internet of Things (IoT) devices typically operate with limited resources, have weaker security protections, and are more vulnerable to potential thermal stress (TS). Current evaluations of FL are mostly conducted through simulations of multiple clients on a single device. However, there remains a gap in understanding how FL performs under TS in real-world, low-power IoT environments. Conformal prediction (CP) is an effective method for quantifying uncertainty in …

Estimating Pedestrian Crossing Times At Scramble Crossings Via Machine Learning And Agent-Based Modeling, Sho Takami

Honors Capstones

Scramble crosswalks differ from conventional crosswalks in their ability for pedestrians to cross diagonally. This research compares the average crossing times and investigates the walking behaviors that pedestrians adopt to produce the speediest times in the two crosswalk configurations. Identification of the most efficient set of walking behaviors is done through an agent-based model, whereas producing polynomials relating crossing times to the most prominent walking behaviors is done through regression algorithms in machine learning. With the combination of these two approaches, it is revealed that pedestrians must adopt a relaxed walking style to make each crosswalk configuration efficient. Additionally, between …

Frequency Up-Conversion Electromagnetic Energy Harvester For Generating Electrical Power From Vibration Of Beams Under Moving Load, Md Ismail Monsury, Adamaris Sanchez, Mohsen Amjadian, Constantine Tarawneh

Civil Engineering Faculty Publications

This paper studies a single-resonator electromagnetic energy harvester that employs an impact-driven frequency up-conversion mechanism to convert low-frequency vibrations of a multi-span beam, subjected to successive moving loads, into electrical power. The harvester consists of a cantilever beam made of plastic, serving as the resonator, with a thick square copper coil attached to its free end. This coil moves relative to two stationary cubic neodymium permanent magnets, each positioned on one side of the coil. To expand the harvester’s operational bandwidth, a stopper is positioned beneath the resonator, inducing controlled mechanical impacts as the cantilever beam vibrates. These impacts effectively …

Numerical Study Of A Locally Resonant Frictional Metamaterial For Seismic Vibration Control Of Liquid Storage Tanks, Shayan Khosravi, Mohsen Amjadian

Civil Engineering Faculty Publications

Liquid storage tanks (LSTs) are critical infrastructure components, storing essential fluids in facilities such as oil refineries and nuclear power plants. However, their vulnerability to seismic damage, including tank wall buckling and anchor uplift due to fluid-structure interaction and sloshing dynamics, necessitates advanced protective measures. This study introduces the Locally Resonant Frictional Metamaterial (LRFM) system as an innovative seismic base-isolation (SBI) technology to mitigate earthquake-induced effects on LSTs. The LRFM system consists of a periodic lattice framework with friction-based resonators designed to attenuate seismic waves by generating low-frequency bandgaps (0–20 Hz), which is a critical range for mitigating impulsive seismic …

05.05.2025 Ored Connect, Liz Williamson

ORED Newsletter

Research Showcase Photos

Showcase Raffle Winners

Chancellor's Award for Research and Creative Scholarship

Video of the ORED website

Recent U.S. Government Policy Literature On Critical And Strategic Minerals, Bert Chapman

Libraries Faculty and Staff Scholarship and Research

Critical and strategic minerals have become increasingly important in U.S. government civilian and military policymaking in recent years. This is demonstrated by the heavy use of such minerals in many critical civilian and military infrastructures. This work will discuss how this subject has been addressed in laws, presidential documents, and works by government agencies along with congressional oversight committees and support agencies. It will stress how the United States is heavily dependent on strategic minerals from adversarial foreign countries such as China and will examine U.S. efforts to increase its ability to produce such materials in the United States by …

First-Principles Studies Of Electrical Polarization Effects In Ferroelectrics, Antiferroelectrics And Defects, Louis Alaerts

Dartmouth College Ph.D Dissertations

Over the last few decades, density functional theory (DFT) has emerged as a formidable tool in the field of computational material science. Not only has it become a complementary method approach to experiments by rationalizing the many complex properties of materials but its formidable predictive power can also be used to identify the most promising candidates for specific applications. Point defects in semiconductors have become an important platform for the development of quantum networks due to their ability to act as spin-photon interfaces. Spectral diffusion, the broadening of the optical emission line, can significantly impact the performance of these defect-based …

Data-Driven Dynamic Decision-Making Using Discrete Optimization And Supervised Machine Learning, Navid Rashedi

Dartmouth College Ph.D Dissertations

In recent years, the operations research community has developed data-driven optimization techniques to solve complex combinatorial problems with the aid of machine learning. This thesis contributes to these efforts by combining machine learning with optimization to expedite online decision-making, with applications in transportation and healthcare.

In the domain of airline operations recovery, the focus is on the aircraft recovery process—repairing disrupted schedules by minimizing overall disruption costs. Traditional exact methods are too time-consuming, while heuristic approaches often yield poor solution quality and lack generalizability across varying formulations. To address these challenges, this research employs supervised machine learning to identify near-optimal …

Predicting Sorption Of Diverse Organic Compounds In Soil-Water Systems: Meta-Analysis, Machine Learning Modeling, And Global Soil Mapping, Jiachun Sun, Kai Zhang, Huichun Zhang

Faculty Scholarship

In recent decades, the environmental detection of various organic compounds (OCs) has highlighted the limitations of conventional soil-water sorption models, which simplify complex experimental conditions and often overlook OCs with polyfunctional and ionizable structures. To address these shortcomings, we compiled a comprehensive soil-water sorption dataset encompassing 20,945 data points for 419 OCs with various functional groups and 1037 different soils. Meta-analysis of the dataset revealed the trends of soil sorption associated with OC substructures, soil properties, and solution conditions. Machine learning models employing the XGBoost algorithm, in conjunction with MACCS fingerprints and experimental conditions, were developed to cover the entire …

Breaking New Ground: Division Directly In Memory, M. Hassan Najafi, Mehran Shoushtari Moghadam

Faculty Scholarship

In-memory computing (IMC) has emerged as a promising paradigm for overcoming the limitations of traditional von Neumann architectures by reducing data movement and enhancing computational efficiency. Despite significant advancements in this area, implementing complex arithmetic operations, such as division, directly within memory has remained an elusive challenge. This paper introduces a pioneering technique for performing division operations directly in memory, representing the first successful integration of such functionality into the IMC framework. Our approach leverages an innovative circuit based on an unconventional model of computing–stochastic computing (SC). Our technique extends the computational capabilities of IMC systems and paves the way …