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Reciprocity-Based Transfer Function Techniques For Acoustic Source Reconstruction, Spring Isolator Characterization And Structural Damping Assessment, David Pum Thian Lal Paite Neihguk

Theses and Dissertations--Mechanical and Aerospace Engineering

Reciprocity implies that a system responds identically when the source and receiver positions are interchanged. This dissertation applies this principle to address three practical challenges in noise and vibration characterization, where conventional approaches are limited by inaccessible interfaces, constrained excitation conditions, or metrics that do not fully capture vibroacoustic behavior.

The first study develops and validates an inverse method to characterize ducted acoustic sources using acoustic free velocity. Acoustic reciprocity is applied to simplify transfer function measurements. The method is extended to large cross-section ducts, where the source is reconstructed as a collection of point sources along a plane. Validation …

Process-Guided Learning Via Data-Driven Modeling And Controller Synthesis, Benton Clark

Theses and Dissertations--Mechanical and Aerospace Engineering

This work introduces process-guided learning, a framework in which process characteristics and learning algorithms are combined in the modeling process of engineering applications with the aim of uniting traditional and data-driven modeling and control techniques. Traditional engineering methods using simplified analytic models fail to capture the increasing complexities of engineering problems with sufficient accuracy to achieve modern requirements. More advanced modeling and control techniques using high-fidelity models often produce a computational burden that is infeasible for real-time solutions. Data-driven modeling offers a simple and flexible algorithm for producing real-time capable, high-fidelity models, but naive implementations lack the physical constraints of …

Shock The System: Pouring Water On The Cpuc’S Income-Graduated Flat Rates In Favor Of More Effective Rate Structures, Benjamin Hill

Dickinson Law Review (2017-Present)

The volume of rate cases in the United States continues to increase, resulting in constant price hikes for utility customers. The battle between corporate profit and consumer financial satisfaction will likely continue. Considering these diametrically opposed interests, the California Public Utility Commission, at the behest of the California legislature, decreased the rate consumers pay for usage and added fixed fees based on income to utility bills. The broader goals of the Commission’s model are to maintain utility profitability, alleviate the financial burden consumers face, promote energy conservation, and develop energy efficient technology to combat greenhouse gas emissions. This Comment will …

Machine Learning For Predicting Prosthetic Limb Movements, Jessica Alexandra Cegarra Arraiz

Theses and Dissertations

This thesis develops and evaluates a deep learning-based prediction model capable of identifying intended limb movement from surfaced electromyography (sEMG) signals using sequence learning techniques. sEMG signals change over time due to multiple factors such as muscle fatigue or user variability. Traditional prosthetics control methods rely on static feature extraction, ignoring how signals change over time, thereby limiting their ability to capture the temporal changes of muscle activity. As a result, these approaches often lead to poor accuracy, robustness, and generalization. Limited experimental validation has been conducted on sequence-based machine learning approaches using temporal sEMG data from publicly available datasets …

Edge Guided Channel Attention In Fsrcnn: A Novel Approach For Depth Super Resolution, Yagneshkumar Jayantilal Parmar, Paresh M. Dholakia

Mansoura Engineering Journal

Depth images from low-cost sensors often suffer from blurred edges and structural distortions when processed with standard super-resolution models. While FSRCNN is efficient for RGB images, it struggles to handle the unique geometric requirements of depth maps. To solve this, we propose the Edge Guided Channel Attention FSRCNN (EGCA FSRCNN). This method incorporates an edge-guided modulation mechanism to preserve object boundaries and a Squeeze and Excitation (SE) block to focus on critical structural features. A major benefit of this framework is the use of frozen, pretrained FSRCNN weights, which bypasses the requirement for retraining. Our evaluation on the UTKinect, Middlebury, …

Solving High-Dimensional Differential Equations Using Recurrent And Residual Neural Network Architectures, Hind Khaled Kolaib

Knowledge Engineering and Data Science

High-dimensional Partial Differential Equations (PDEs) form the foundation of complex process modeling in various scientific and engineering applications, including finance, physics, and optimal control. However, classical numerical methods are adversely affected by the curse of dimensionality, making them inapplicable for large-scale problems. Recently, however, deep learning-based approaches have provided a new toolbox for these high-dimensional PDEs, including methods such as the Deep Backward Stochastic Differential Equation (Deep BSDE) method. Our approach draws on a more sophisticated deep learning backbone, using neural networks (in our case, a Residual Neural Network and a Long Short-Term Memory network (LSTM) integrated into the Deep …

A Full Polymer Piezoelectric Flextensional Energy Harvester, Nadia Ahbab, Sidra Naz, Bingqi Zhao, Tian-Bing Xu

Mechanical & Aerospace Engineering Faculty Publications

This study presents a full polymer piezoelectric flextensional energy harvester (FPPFEH) comprising a single-layer poly(vinylidene fluoride) (PVDF) film bonded to a 3D-printed polylactic acid (PLA) flextensional frame. For an arm inclination angle of θ=10°, the free-body model gives a theoretical geometric force-amplification factor of M_F=cot θ ≈ 5.67; this value represents an ideal upper bound and was not independently validated by local force or strain measurements. During assembly, the film was tensioned only to remove visible slack and maintain a flat configuration. No intentional pretension was applied, and any residual tension was not measured. Off-resonance force-controlled tests showed …

Advancing Cns Tumor Management: Novel Modalities In Surgery, Radiation, And Chemotherapy, Armin David Tavakkoli

Dartmouth College Ph.D Dissertations

Most tumors affecting the brain and spine are managed through a combination of surgical resection, radiation, and chemotherapy; however, operative morbidity from invasive surgery, the narrow therapeutic window of conventional radiotherapy, and poor blood-brain barrier penetration of systemic agents are critical barriers that hinder long term tumor control. This thesis presents three complementary strategies to advance brain and spine tumor therapy. First, we investigate laser interstitial thermal therapy (LITT) in the treatment of spinal tumors with metastatic epidural spinal cord compression, replacing “separation surgery” with a minimally invasive, image-guided approach that maximizes tumor ablation while preserving neurologic function. Second, we …

Extending Low-Frequency Traveling-Wave Propagation In A Water-Filled Cylindrical Waveguide Using Active Impedance Control, William Slater

Open Access Dissertations

This dissertation investigates extending the frequency range over which a one-dimensional, plane traveling wave can be generated in a water-filled, steel-walled waveguide under ocean temperature and hydrostatic pressure conditions. The wave guide considered is a thick-walled, steel cylinder filled with a water/glycol mixture with a transducer at each end and a hydrophone array along the length. One transducer excites a plane wave while the other cancels reflections, resulting in a traveling wave in the waveguide. The current (open-loop) measurement system is advertised to generate traveling waves for low frequencies where only 3.4% of a wavelength can be measured (kL …

Development Of Stronger, More Extrudable 6xxx Series Alloys For Automotive Applications, Eli A. Harma

Dissertations, Master's Theses and Master's Reports

6xxx alloys are widely used in automotive extrusion structures for their high specific strength and formability. Advanced designs require greater formability and strength, creating an opportunity for high-strength, formable alloys. The 6xxx series forms β”-Mg₅Si₆ precipitates during age hardening and develops a fibrous microstructure during extrusion, both strengthening the alloy. Increasing Mg and Si to form more β” decreases formability. Thus, modifying texture can increase strength without reducing formability. Current alloys like 6005A add Mn and Cr to form dispersoids that inhibit recrystallization and promote strengthening textures; however, high Mn and Cr concentrations reduce formability. Replacing Mn …

Aqueous Iron Electrowinning: From Electrolyte Engineering To The Unexplored Potential Of Acetate Systems, Chodwell N. Verenga

Dissertations, Master's Theses and Master's Reports

Iron electrowinning and electrodeposition sit at the intersection of classical metallurgy and developing sustainable manufacturing. With the iron and steel industry responsible for 7 - 9% of global CO₂ emissions, low-temperature electrochemical pathways for iron production have garnered significant research interest. This review examines the fundamental electrochemical principles governing iron deposition, the thermodynamic constraints imposed by the iron-water system, and the kinetic challenges posed by the parasitic hydrogen evolution reaction (HER). The three key electrolyte systems are objectively evaluated: acidic sulfate and chloride electrolytes, alkaline suspension electrolytes and water-in-salt electrolytes. Their operating parameters, faradaic efficiencies, energy consumption and deposit characteristics …

Experimental Rate Feedback Control Of A Model-Scale Hourglass-Shaped Heaving Point Absorber, James R. Halverson

Dissertations, Master's Theses and Master's Reports

Buoy geometry greatly affects a point absorber wave energy converter's dynamic response to waves. Finding the optimal buoy shape and control method remains an open research area focused on maximizing the conversion of wave kinetic energy into electricity. This work presents an experimental comparison of closed-loop energy extraction between a cylindrical and a truncated cone buoy, both with the same submerged volume, across various wave frequencies and amplitudes. To ensure a fair comparison, the optimal rate feedback gain is calculated for each buoy at each wave condition. Multiple metrics, including power output, capture width, and actuator force, are used to …

Numerical And Experimental Evaluation Of A Simple, Low-Energy Lunar Volatile Separation Technology, Eleanor L. Zimmermann

Dissertations, Master's Theses and Master's Reports

In-situ resource utilization (ISRU) is the practice of finding, extracting, and using the local resources found on extraterrestrial bodies, such as the Moon and Mars. ISRU enables in-situ production of mission consumables—such as rocket fuel and potable water—which will be critical for establishing a sustainable human presence on the Moon, a goal NASA intends to accomplish by 2028 with the Artemis missions. The separation and liquefaction of locally extracted volatiles—such as water, CO₂, and Methane—is an essential component in lunar surface sustainability, but there are very few technologies being developed for this purpose. This report introduces the Radiative …

Nondestructive Evaluation Of Additively Manufactured Parts Using Resonant Inspection And Frequency Domain-Based Correlation Criteria, Gita Deonarain

Dissertations, Master's Theses and Master's Reports

Additive manufacturing (AM) enables the production of highly customized and geometrically complex components; however, these parts remain susceptible to a wide range of defect types and severities. The combination of complex geometries and distributed defects presents a significant challenge for post-process nondestructive evaluation (NDE). Conventional inspection techniques, such as computed tomography and ultrasonic testing, are often limited by geometry, material, accessibility, and cost, while in situ monitoring is not yet sufficiently mature to replace post-process inspection.

This dissertation establishes the Frequency Domain Assurance Criterion (FDAC) as a quantitative, vibration-based framework for defect detection in AM components. FDAC captures spatial–spectral correlations …

The Excess Path Length Distribution: A Stochastic Model For Sample-Based Path Planners, Chaz B. Cornwall

Dissertations, Master's Theses and Master's Reports

Through random sampling, sample-based path planners enable autonomous agents to quickly find paths without human intervention. However, due to the paths' randomness, sample-based path planners currently require additional verification, partially nullifying agents' ability to act autonomously. I set out to characterize this uncertainty so humans know what to expect from these path planners and know how to alter the path planner to desired specifications. To ensure the results are theoretical as well as practical, I first create a stochastic model of path length uncertainty using the trade-off between sampling time and optimality. By leveraging this model, my proposed algorithm reduces …

Shm For Incipient Buckling Detection In Overloaded Structures Using Nonlinear System Identification Algorithms On Redundant Data Sets, Padmanabh Shridhar Desai

Dissertations, Master's Theses and Master's Reports

Structural health monitoring (SHM) detects and characterizes damage to predict failure, but failures such as buckling, which are not predicated on traditional damage modalities, are harder to detect. Direct load measurements are costly and difficult to implement (especially for dead loads) as they require copious numbers of sensors, which must be installed before loading is present. Vibration-based detection is a good alternative because it can infer global structural characteristics with relatively few sensors. This dissertation presents an SHM approach for detecting incipient buckling in structures under excessive loads based on non-linear models fit from measurements of small lateral vibrations due …

Mechanical Fractionation Of Wheat Middlings For Application In Pyrolysis And Animal Feed, Okwudili I. Obiakor

Dissertations, Master's Theses and Master's Reports

Wheat middlings are grain byproducts that are underused for bioenergy production despite having a high lignocellulose content. Its use as a feedstock for catalytic pyrolysis depends on effective and sustainable fractionation to enhance efficiency and product yield. This study tested mechanical pre-fractionation (sieving and air classification) to reduce ash content of certain fractions to < 1% for catalytic pyrolysis and enrich nutrient levels of other fractions for feed applications. Wheat middlings were separated into 11 fractions using screen sizes from 106 µm to 1651 µm, and the composition of each fraction was characterized (ash, protein, structural carbohydrates, lignin, starch, and simple sugars). For cyclone separation, a full factorial design was used to study the effect of air velocity (15,18, 20 m/s) and feed rate (33, 35, 38 kg/h) on the amount of material collected in the underflow and overflow, and the composition of these fractions was characterized. Sieving showed a pronounced segregation of ash content, from 4.5% to 6.5% in wheat middlings fractions, with 5.7% being the lowest for coarse fractions which has higher lignocellulose content, and 4.5% in the fine fraction (150-212 µm). The same defined enrichment was observed in all nutrients except for protein. Starch enrichment zone were defined in the fine fractions (212 µm and below), for structural carbohydrates and lignin in the coarse fractions (600 µm and above), and for ash in coarse fractions (1180-1651 µm). In contrast, protein content was not significantly different between various fractions (p value=0.787). The fiber rich fraction (> 600 µm), suitable for pyrolysis, which have a composite ash value of 6.0% can be sorted and mixed with intermediate fractions to reduce ash to 5.3% and the remaining fractions rich in digestible nutrients used for animal feed formulation. Compared to sieving, cyclone separations did not …

Computational And Ai Frameworks For Identifying Key Regulatory Genes And Their Target Genes In Plants And Humans, Md Khairul Islam

Dissertations, Master's Theses and Master's Reports

This dissertation presents computational and AI-driven frameworks for identifying key regulatory genes and their downstream targets across plant and human biological systems. Three studies address distinct challenges in genomic regulation using advanced machine learning and bioinformatics approaches.

The first study introduces DyGAF (Dynamic Gene Attention Focus), a dual-attention transformer framework that identifies and ranks disease-relevant biomarker genes by simultaneously modeling independent molecular responses and interdependent regulatory network behavior. Two attention models provide complementary perspectives on gene importance and are fused through a novel combination metric. Applied to COVID-19 nasopharyngeal swab profiles, the attention-weighted representations achieved 94.23% classification accuracy, high sensitivity, …

Machine Learning And Multi-Scale Optimization For Control And Energy Management In Connected And Automated Vehicle Propulsion Systems, Joshua D. Orlando

Dissertations, Master's Theses and Master's Reports

This dissertation presents a multi-scale optimization framework leveraging machine learning (ML) to enhance energy efficiency in connected and automated vehicle (CAV) propulsion systems. As transportation transitions toward hybridization and automation, the integration of vehicle-to-everything (V2X) connectivity and advanced control algorithms offers unprecedented opportunities for energy reduction. This research addresses three critical scales of vehicle energy management: multiple vehicle-level coordination, component-level powertrain dynamics, and real-time vehicle parameter estimation.

First, the research investigates the energy consumption characteristics of heterogeneous propulsion systems—ranging from internal combustion engines to battery electric vehicles across light- and heavy-duty sectors—on arterial roadways. Utilizing Particle Swarm Optimization (PSO) and …

Application Of Reactive Power Theory To Wave Energy Converters Under Multi-Frequency Excitation: Analysis And Experimentation, Mckenna R. Collins

Dissertations, Master's Theses and Master's Reports

There is abundant energy surging in the oceans across the globe. However, there have been technological challenges in extracting that energy for use. Wave energy converter (WEC) technology is being developed to find innovative ways to convert wave kinetic energy into electricity, but there are still efficiency obstacles that inhibit large-scale use. Focusing on heave-point absorber control theory, this thesis continues the work to improve the efficiency of WECs. This is done by leveraging a superposition of linear mass-spring-damper models to analyze a WEC under multi-frequency excitation and applying proportional-derivative gains to each linear model. However, to analyze this system, …

Open Source Tools For Ecological Research, Alex P. Riebe

Dissertations, Master's Theses and Master's Reports

This thesis presents the development of an open source wireless sensor network for hibernacula manipulation with an emphasis on accessibility and reproducibility. It addresses the design of the electrical hardware, guidance on antennas and RF implementation, and design of an application-specific communication protocol, all with the explicit goal of enabling ecologists and other conservationists to be able to manufacture, deploy, operate, and maintain the system for their research. The resulting sensor network designed in this thesis is to control the temperature inside bat hibernacula during the winter to study the relationship between temperature and bat mortality rate due to White …

Design And Experimental Evaluation Of A Custom Vision-Guided Approach To 2d Part Localization For Industrial Robots, Faisal Ali

Dissertations, Master's Theses and Master's Reports

Vision-guided robots offer a clear advantage over teach-pendant programming for battery handling, where modern packs hold thousands of cells and teaching each position by hand does not scale. Commercial vision systems address this need, but their calibration, detection, and coordinate-conversion stages are closed to the user, making it hard to incorporate newer learning-based methods. This work presents a modular, custom-built vision-guided system using an Orbbec Gemini 435Le eye-in-hand camera, an NVIDIA Jetson Orin Nano, an Allen-Bradley Micro850 PLC, and a FANUC LR Mate 200iC, communicating over Modbus TCP and EtherNet/IP. A per-hole classification model resolves each known hole into a …

Design And Validation Of A Low-Cost Wearable Electromyography (Emg) System For Monitoring Exercise-Induced Changes In Muscle Activity, Ingrid E. Halverson

Dissertations, Master's Theses and Master's Reports

Wearable technologies have expanded opportunities for monitoring athletic performance, but many existing systems remain costly and confined to laboratory or medical settings. This thesis presents the design, development, and evaluation of a low-cost, wearable EMG platform for monitoring neuromuscular activity during exercise. A wireless device incorporating a surface EMG sensor, an ESP32 microcontroller, and Wi-Fi transmission was developed to acquire muscle activation data. Signal processing techniques, including filtering, root-mean-square (RMS), mean frequency (MNF), and median frequency (MDF) analyses, were used to evaluate changes in muscle activation. Experimental testing demonstrated reliable wireless data acquisition and successful capture of physiological changes before …

High-Performance Circuit Manufacturing And Testing Exercises, Benjamin S. Keppers

Dissertations, Master's Theses and Master's Reports

An advanced demonstrator Printed Circuit Board (PCB) has been designed and implemented providing a framework for advancing students’ knowledge in hands-on PCB design and manufacturing process through industry recognized test coupons, stack ups, and transmission lines. Students are guided through several key aspects of design and simulation relating to manufacturing and qualifications. Manufacturing allows students to refine process development and analyze performance data with respect to qualification tests specified by Global Electronics Association standards. Results are then used to build a stackup model, and complete a design activity for calculating expected test results for a series of controlled impedance electrical …

Robust State Estimation And Scene Understanding For Autonomous Ground Vehicles In Challenging Environments, Nader J. Abu-Alrub

Dissertations, Master's Theses and Master's Reports

Autonomous ground vehicles require reliable state estimation and scene understanding to operate safely in challenging environments. Poor illumination, adverse weather, degraded visibility, snow-covered roads, and sensor noise can reduce the reliability of conventional localization and perception pipelines. Addressing these challenges requires sensing and algorithmic strategies that exploit the complementary strengths of different modalities. Radar is particularly attractive because of its resilience to lighting and weather variations, while inertial, camera, and lidar measurements provide additional motion, appearance, and geometric information. This dissertation investigates compact radar-based and sensor-fusion approaches for improving autonomous ground-vehicle state estimation and scene understanding under degraded sensing conditions. …

Beyond Receptive Measures: Development And Validation Of The Spatial Grid Drawing Assessment (Sgda) As A Productive Measure Of Spatial Skill, Katrina L. Carlson

Dissertations, Master's Theses and Master's Reports

Spatial skills are vital in many STEM disciplines, starting at or prior to university training, and often extending throughout one’s career. The most widely used spatial ability measures (e.g., PSVT: R, MRT) rely on what I refer to as receptive skills: examining an object or design, mentally transforming it, and comparing it to given alternatives. But because work in many STEM disciplines also involves productive spatial skill such as drawing, I hypothesize that a productive measure of spatial skill may predict distinct aspects of spatial ability. This research investigates the relationship between traditional receptive Spatial Visualization (SV) assessments, such as …

Using Automotive Lidar To Reduce The Energy Consumption Of An Ego Autonomous Vehicle, Logan P. Schexnaydre

Dissertations, Master's Theses and Master's Reports

There is significant potential to reduce the energy consumption of the transportation sector through autonomous vehicles. Prior work on autonomous vehicle energy efficiency focuses on the whole system or the control subsystem. Yet, the sensing and processing components, which have direct and indirect effects on net energy use, are less explored. This dissertation fills this gap by modeling and evaluating these effects for lidar sensors, which provide high-resolution spatial data at the cost of high power and processing demands. I apply lidar to the energy-saving tasks of automated vehicle following and road surface profiling. For automated vehicle following, I model …

Methodology Development For Evaluating Relative Heat Checking Resistance Of Open-Die Forge Tooling, Jack F. Schaller

Dissertations, Master's Theses and Master's Reports

Heat checking, characterized by biaxial networks of surface cracks induced by thermomechanical cycling, can cause premature failure of open-die forge tooling. To facilitate the evaluation of heat checking resistance of die steels, a simulation‑informed out-of-phase thermomechanical fatigue (OP-TMF) testing methodology was developed using 4330V steel as a baseline material. Temperature‑dependent material properties and flow stress data were collected and compiled into a material data file for use with finite element analysis software. Forging and cooling scenarios were simulated across a range of die preheat temperatures. Temperature and in-plane strain histories extracted from the die surface provided a foundation for laboratory …

Designing Narrative-Based Ai Assistance For Sensemaking In Collaborative Environments: Case Studies In Education And Dementia Care, Dylan Edward Moore

Dartmouth College Ph.D Dissertations

This thesis addresses a gap in the human-computer interaction literature regarding the design, development, and evaluation of narrative-based AI assistance for collaborative, complex problem solving. I explore this design space through three case studies across the domains of education and dementia care. This work encompasses multi-year industry partnerships and longitudinal fieldwork, user-centered design, dataset curation, model training, and system evaluation.

Specifically, the first case study considers a story-based web platform for teaching AI literacy through peer-generated, personalized narrative scaffolding. Learners on the platform showed significant knowledge gains and other learning-related outcomes. To describe the novel design of this system, I …

Stress-Strain Behavior Of Saturated Clays From Vane Shear Test Results: A Numerical Approach, Gustavo Rodrigues De Avila Oliveira

Master’s Theses

The vane shear test (VST) is widely used to estimate the undrained shear strength of soft cohesive soils; however, it does not directly provide constitutive information such as the stress–strain response. Smoothed Particle Hydrodynamics (SPH), a mesh-free numerical method, offers an attractive alternative for modeling the large deformations involved in the VST and extracting additional information from the test.

This study develops and calibrates a two-dimensional SPH model to simulate the field vane shear test and investigate the stress–strain behavior of soft soils. The VST was implemented within an SPH framework, while field and laboratory data were used to define …