Engineering Commons^™

Leader Election System For An Unmanned Ground Vehicle Swarm, Milan Chhetri, Brendan Beas, Paul Levin

Electrical Engineering

This senior project presents the design and implementation of a leader-election system for a leader-follower unmanned ground vehicle (UGV) swarm using embedded control and wireless communication. The objective of the project is to improve the robustness and mission longevity of a multi-agent robotic system by allowing the swarm to dynamically select the most suitable leader during operation. Each UGV is equipped with an ESP32 microcontroller, DWM1000 Ultra-Wideband (UWB) ranging modules, an MPU-6050 inertial measurement unit (IMU), motor drivers, and supporting power electronics to enable communication, sensing, and autonomous control. A battery monitoring subsystem was developed using the ESP32's built-in Analog-to-Digital …

Archimedean Spiral Antenna Array With Klopfenstein And Exponential Tapered Balun Feeds, Leo Joseph Alvelais Iv, Paul Obrecht, Naguib Abdulla, Preston Mavady, Collin Fan

Electrical Engineering

This project presents the design, fabrication, and experimental evaluation of a broadband 3x3 Archimedean spiral antenna array tile for 2.8-3.8 GHz. Each element combines a two-arm spiral on Rogers RO4350B, a printed 50 to 150 Ω tapered balun, and a conductive backplane. Klopfenstein and Exponential feed implementations were modeled in Ansys HFSS, generated and tuned with automated scripting, fabricated, and evaluated with calibrated network and anechoic-chamber measurements. The Klopfenstein-fed hardware met the -10 dB input-reflection criterion across the project band. The exponential array provided a broad matched response but reached approximately -8 dB near 2.95 GHz. Measured center-element patterns retained …

Vision-Based Autonomous Tracking Rover, Alejandro Ahumada, Erick Ayala, Jonathan Chavez

Electrical Engineering

AAC Vision designed and constructed a vision-based autonomous tracking rover capable of exploring an indoor environment, avoiding obstacles, generating a two-dimensional LiDAR map, detecting a standard orange basketball, and approaching the target without manual steering. The rover uses a Raspberry Pi 4, an Intel RealSense D435 RGB-D camera, an RPLIDAR C1, four JGB37-520 Hall-encoder motors, dual H-bridge motor drivers, a 12 V battery, and a custom aluminum chassis measuring approximately 8 in by 12 in and weighing 6.7 lb. The final mission emphasized reliable target discovery rather than travel between predetermined points. The software integrates Python, OpenCV, Ultralytics YOLO, RealSense …

Multidisciplinary Inverse Robust Co-Design Of Materials, Products, And Manufacturing Processes, H M Dilshad Alam Digonta

Theses and Dissertations

Realizing the design for Integrated Computational Materials Engineering (ICME) requires the materials, product, and manufacturing-process disciplines to be designed together. Because these disciplines interact and influence one another's decisions, coordination is needed among their distributed decision-makers. Their interactions are captured through the processing-structure-property-performance (PSPP) linkages, which must be established from limited, costly data. Moreover, each discipline introduces its own sources of uncertainty, and these propagate through the process chain to influence final product performance. The effective realization of the product-material-manufacturing system, therefore, calls for a co-design approach that enables the concurrent coordination of the interacting disciplines while quantifying and managing …

Thermal Transport Tuning Via Nanoscale Hierarchical Frameworks For Fe2val Thermoelectric Materials, Apoorva Pradip Joshi

Dartmouth College Master’s Theses

Waste heat represents a vast, untapped energy resource. Thermoelectric materials offer a promising route to harvest this energy by directly converting thermal gradients into electricity. The Heusler alloy Fe2VAl is a prime candidate for such applications because it is non-toxic and cost-effective. However, its intrinsically-high thermal conductivity severely limits performance. A detailed understanding of thermal transport mechanisms is therefore essential for improving its thermoelectric efficiency. This work examines the effect of atomic disorder on the thermal transport behaviour of Fe2VAl. We use germanium doping to introduce atomic-scale disorder and demonstrate a substantial reduction in thermal conductivity, from 28 W/m-K in …

The Neuropsychological Analysis Of The Effect Of Shame And Traumatic Memories In Paranoia: A Network Analysis, Anwesha Maitra

Clinical Psychology Dissertations

Paranoia is increasingly recognized as a multidimensional psychological phenomenon influenced by trauma-related distress, shame, maladaptive interpersonal experiences, and emotional functioning. Although these factors have been extensively associated with paranoia, their relationships with neurocognitive functioning, social cognition, and global functioning remain less well understood. The present study examined these relationships using traditional statistical analyses, network analysis, and machine-learning approaches in a non-clinical sample of 42 adults.

Participants completed self-report measures assessing trauma-related distress, childhood interpersonal experiences, shame, paranoia, depressive symptoms, fear of negative evaluation, self-esteem, and hostile attribution bias, in addition to a comprehensive neurocognitive battery, an emotion recognition task, and …

Advancing Sensing And Structural Health Monitoring Of Non-Conventional Space Structures, Scott Bender

Doctoral Dissertations and Master's Theses

Future lunar and deep-space missions will require new structural concepts that reduce mass while maintaining reliability. Two technologies that have received significant attention are inflatable habitats and additively manufactured structures; however, challenges remain in their characterization, validation, and long-term monitoring. This dissertation investigates methods to improve the testing and sensing of these non-conventional aerospace structures through the use of advanced photogrammetry and embedded distributed fiber-optic sensors. A color-filtering digital image correlation technique was developed to isolate orthogonal strain directions in woven inflatable structures, providing improved characterization of biaxially loaded softgoods. In addition, methods were developed to embed distributed fiber-optic sensors …

Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran

Doctoral Dissertations and Master's Theses

Modern multi-agent Urban Search and Rescue (USAR) operations heavily rely on mobile geospatial Common Operating Pictures (COPs) to maintain team coordination and Situational Awareness (SA). However, the proliferation of high-frequency sensor telemetry at the tactical edge has introduced a data saturation paradox challenge: while information theoretically drives informed decision-making, unmanaged data surges induce increased operator cognitive overload and alert fatigue on mobile End-User Devices (EUDs), while downstream data-broadcasting models inherently strain edge processing and viewport environments.

To resolve these constraints, this dissertation presents a context-aware Value of Information (VoI) data-management framework integrated directly with a custom, event-driven Android Team Awareness …

System Integration And Validation Of The Cal Poly Spacecraft Attitude Dynamics Simulator Mk. Iv, Bricen S. Rigby

Master's Theses

The Cal Poly Spacecraft Attitude Dynamics Simulator (SADS) is an ongoing project that seeks to enable the simulation and validation of sensors, actuators, and control logic related to spacecraft attitude control. The SADS platform rests atop a spher- ical air-bearing device which allows for nearly frictionless rotation in all three axes. The orientation of the platform is controlled by four reaction wheels arranged in a pyramidal configuration. Over the past few years, there have been significant updates to the reaction wheel subsystem, as well as requests for a more capable central com- puter. Therefore, a new system architecture for the …

Bio-Inspired Visual Intelligence: Improving Efficiency And Robustness Through Foveal-Peripheral Sampling And Learned Saccades, Jiayang Liu

Dissertations - ALL

Deep neural networks have achieved state-of-the-art performance across a wide range of computer vision tasks, yet their deployment in real-world and safety-critical domains remains limited by two major challenges: vulnerability to adversarial perturbations and high computational cost. While adversarial training can improve robustness under certain threat models, it is computationally expensive and often generalizes poorly to black-box or transferable attacks. At the same time, conventional vision pipelines process uniformly sampled high-resolution images, introducing substantial data redundancy, latency, and energy overhead. In contrast, the human visual system achieves efficient and robust perception through space-variant foveal-peripheral sampling, attention-guided saccadic eye movements, and …

Agentic Ai-Enabled Physics-Informed Machine Learning Framework For Intelligent Building Modeling, Control, And Automation, Zixin Jiang

Dissertations - ALL

Buildings account for a significant share of global energy consumption, and meeting the 2050 net-zero decarbonization targets requires retrofitting approximately 10,000 buildings per day in the United States alone. However, current human-centered workflows for building modeling, simulation, control, and operation remain too slow and labor-intensive to support deployment at this scale. This dissertation proposes an integrated two-pillar framework consisting of a physics-informed machine learning framework for integrated building modeling, control, and simulation, and a multi-agent agentic AI framework for automating building energy engineering workflows built on top of that foundation. The first pillar introduces a Physics-Informed Modularized Neural Network (PI-ModNN) …

Rapid Synthesis And Processing Of High-Capacity Layered Oxide Cathode Materials For Lithium And Sodium Batteries, Hansheng Li

Dissertations - ALL

Lithium-Manganese-Rich-Oxide (LMRO) is a type of layered oxide cathode active material with high energy densities of up to 900 - 1,000 Wh kg-1, competitive in capacity-demanding rechargeable lithium batteries. The increased energy density is beneficial for the range and recharging interval of electric vehicles. Based on layered Ni/Mn/Co oxide cathode materials, a high Mn content is chosen for this project as being abundant, while increased Ni concentration trades off thermal stability with specific capacity, while Co is carcinogenic and sourced less sustainably. Lithium content is increased along with Manganese content stoichiometrically as a second phase is introduced. Traditional synthesis routes …

Investigation Of Inlet Turbulence Effects On Mixing Characteristics Of A Jet In Crossflow, Erin Jagger

Masters Theses

Gas flaring is widely used in the oil and gas industry to dispose of excess waste gas, and improving flare efficiency is critical for reducing emissions. Flare performance depends strongly on turbulent mixing between the flare gas and surrounding crossflow. While previous studies have examined the effects of crossflow velocity and low turbulence levels, the combined effects of crossflow turbulence intensity and integral length scale on mixing remains insufficiently understood.

This study uses a non-reacting jet in crossflow (JICF) configuration to represent the mixing process between the flare and crossflow interaction. Using computational fluid dynamics (CFD), Reynolds-Averaged Navier-Stokes (RANS) simulations …

Hybrid Patrol–Staging Optimization For Freeway Service Patrols Under Cost Control: A Deterministic Milp With Dynamic Segment Adjustment & Environmental Co-Benefit, Mauricio Micolta

Electronic Theses and Dissertations

Freeway Service Patrol (FSP) programs are central to Traffic Incident Management (TIM), delivering rapid response, clearance, and motorist assistance on high-volume corridors. The prevailing continuous roaming patrol model provides broad coverage but generates substantial non-productive vehicle-miles traveled (VMT), increases responders’ exposure to risk, and treats Service Level Agreement (SLA) compliance as a statistical outcome rather than a fixed operational constraint. Existing literature lacks a framework that simultaneously optimizes corridor segmentation, jointly deploys patrol and staged units across space, time, and direction, and enforces response-time SLA as a binding constraint.

This dissertation introduces the Segmental-Spatio-Temporal Hybrid Service Model (SSTHSM), a two-tier …

Friction Stir Processing Of Cobalt-Chromium-Molybdenum For Improvements In Biomedical Applications, Kaleb Kiyoshi Bates

Theses and Dissertations

Friction Stir Processing (FSP) has been investigated as a means of microstructural modification aimed at improving mechanical properties such as corrosion resistance and wear resistance of biomedical-grade cobalt-chromium-molybdenum (CoCrMo) alloy. FSP was successfully completed on high-carbon ASTM F1537 CoCrMo plates with operating temperatures ranging from 630°C to 850°C by adjusting spindle speed, traverse speed, and forge force. Hardness, wear resistance, and corrosion resistance testing were performed, along with Electron Backscatter Diffraction (EBSD) to analyze grain refinement and phase structure. FSP produced grain refinement up to 97% relative to the untreated baseline across the investigated temperature range, with lower processing temperatures …

A Cross-Dataset Vision Transformer Study For Brain Tumor Mri Image Classification, Sharon Kawira Mungania

Masters Theses

Brain tumor MRI classification is an important medical-imaging task because MRI scans contain complex anatomical patterns that can be time consuming to interpret manually. This study evaluates whether a pre-trained Vision Transformer can classify brain tumor MRI images consistently across datasets with different class structures. Three publicly available Kaggle datasets were used: Nickparvar, Br35H, and Figshare. Nickparvar and Figshare were treated as multi-class classification tasks, while Br35H was treated as a binary tumor/no-tumor task. Images were converted to three-channel format, resized to 384 × 384 pixels, normalized using ImageNet statistics, and augmented during training. The selected model was ViT-Base Patch …

Efficient Performance Recovery Of Pruned Llms For End Devices, Paul Vardhan Bethapudi

Master’s Dissertations

Large Language Models have shown strong performance across reasoning, language understanding, and generation tasks, but their computational and memory requirements make deployment on low resource devices difficult. This dissertation studies efficient performance recovery of pruned LLMs, focusing on whether a pruned model can regain useful task performance through parameter-efficient fine-tuning while preserving the benefits of compression. The work uses Llama-3.2-3B-Instruct as the dense reference model and applies activationaware Wanda pruning at multiple sparsity levels(20%, 30% and 50%). The pruned models are evaluated on language modeling and reasoning tasks using WikiText-2 perplexity and GSM8K (Grade School Math 8000 problems) accuracy. Adaptation …

Improved Method Of Evaluating Gas-Phase Air Cleaners Considering Adsorption And Desorption Mechanisms To And From Internal Test Chamber Surfaces, Casey Douglas Coffland

Dissertations and Theses

Portable air cleaners are playing an increasingly important role in managing indoor air quality in response to pressing issues like wildfire smoke events. Smoke is a complex mixture of gases and particulate matter; while established test methods exist for particulate matter, the dynamic behavior of gaseous pollutants is not well accounted for in current test methods. This is because prevailing air cleaner testing methods typically treat background losses as irreversible, whereas gases can engage in partitioning to and from test chamber surfaces. Ignoring these sorption interactions causes inaccurate estimation of an air cleaner's impact.

A new approach has been developed …

Toward Passwordless Document Encryption, Isaac Henry Teuscher

Theses and Dissertations

Document files with sensitive information are used across nearly every industry. In recent years, cyberattacks targeting cloud-based file transfer applications have resulted in millions of sensitive documents being exposed. Although document encryption methods exist, they are often limited in usability, security, or deployability. Password-based encryption, the most widely available option, remains vulnerable to brute-force attacks, unauthorized sharing, and human error. We address these gaps in three phases. First, we present a structured comparative framework adapted from the usability-deployability-security model to evaluate nine document encryption methods across 15 design properties, identifying the benefits and limitations of current approaches. Second, we design …

Hierarchical Parcel Swapping: A Novel Model In Turbulence, Masoomeh Behrang

Theses and Dissertations

Turbulent mixing plays a central role in a wide range of engineering and natural systems, particularly in reactive flows where turbulence--chemistry interactions strongly influence reaction rates, flame structure, and emissions. Accurately modeling these interactions remains a major challenge due to the multiscale and stochastic nature of turbulence, as well as the nonlinear coupling between transport and chemical kinetics. This dissertation develops and evaluates the Hierarchical Parcel Swapping (HiPS) model, a fully stochastic framework designed to represent turbulence-driven transport and scalar mixing without relying on traditional gradient-based closures. HiPS is investigated both as a standalone turbulence model and as a subgrid …

Calibration And Validation Of An Ogden Material Model For Thermoplastic Polyurethane In 3d-Printed Tensegrity Structures, Caleb C. Swain

Theses and Dissertations

This work is motivated by ongoing efforts within the Smart Materials, Adaptronics, and Shock Laboratory (SMASH Lab) at Brigham Young University (BYU) to develop variable-stiffness, external fixators using 3D-printed tensegrity structures. In the process of designing and evaluating these systems, the need arose to accurately model the nonlinear mechanical behavior of thermoplastic polyurethane (TPU), the primary material used in prototype fabrication. This thesis investigates how accurately a calibrated Ogden material model can predict the nonlinear mechanical response of TPU in 3D-printed tensegrity structures. Experimental data were used to calibrate the parameters of the hyperelastic constitutive model through nonlinear optimization. An …

Engineering 3d Optical Interconnects And Low-Power Radio Frequency Gaze Tracking, Blake P. Crosby

Theses and Dissertations

This thesis presents two independent research works in optical in- terconnects and radio-frequency (RF)-based gaze tracking. The first work demonstrates a silicon optical waveguide fabricated from four through-silicon vias (TSVs) produced using two-photon-absorption- assisted photo-electrochemical etching. Unlike conventional TSV fabrica- tion methods, this approach enables highly localized, non-line-of-sight etching in silicon using a focused femtosecond laser. Four approximately 5 μm diameter TSVs were etched through a 200 μm silicon wafer in a 7 μm by 7 μm pattern, leaving a central silicon region that functions as a waveguide. The fabricated structure achieved an aspect ratio of approxi- mately 40:1 with …

Operational Feasibility Of Reinforcement Learning For Vehicle Routing Under Heterogeneous Fleet Capacity Constraints, Freddy Giovanny Aviles Moreno

Electronic Theses and Dissertations

Reinforcement learning methods have demonstrated strong performance on vehicle routing benchmarks, yet their behavior under severe capacity constraints remains unexplored. This dissertation investigates whether PPO-based neural routing policies maintain operational viability when vehicle capacity is severely constrained, as occurs in resource-limited rural logistics settings.

Through controlled experiments on synthetic instances and validation on real-world rural healthcare networks in Florida, this research reveals a critical capacity threshold effect. Moderate capacity reductions from 40 to 20 produce negligible performance loss (4.1%), while severe reductions to capacity 10 trigger catastrophic failure with 243% degradation, manifested through degenerate single-customer routing patterns. Convergence analysis identifies …

Topographical Mobility Envelope Modeling And Geometric Analysis For Off-Road Unmanned Ground Vehicles, Huashuai Fan

ETDs from 2020-2029

This dissertation introduces topographical mobility as a quantitative framework for assessing off-road unmanned ground vehicle performance based on geometric interaction between the vehicle and terrain. Rather than relying on conventional discrete indices, the proposed formulation evaluates mobility directly from vehicle and terrain geometry, expressing vehicle capability in terms of radius constraints implied by its dimensions and suspension state. On the vehicle side, longitudinal and lateral mobility radii are derived analytically from vehicle geometry—wheelbase, track width, ground clearance, and lowest underbody point location—quantifying the minimum terrain radius negotiable without underbody interference. Suspension state is shown to alter longitudinal mobility radius by …

Development And Standardization Of Teds Actuator Templates Under Ieee 1451 Framework, Jim Kang

Theses and Dissertations

The IEEE 1451 standard is a family of standards that defines a framework for smart transducers, including both sensors and actuators, to support consistent, interoperable, and cost-effective integration across diverse applications. However, the current IEEE 1451.4 standard templates only define the method for encoding Transducer Electronic Data Sheet (TEDS) information for a broad range of sensor types and applications; they do not address actuator TEDS. Specific types of sensors and actuators are being developed to assess underground environmental conditions in cold regions with widespread permafrost. Evaluating subsurface conditions before construction can help prevent high construction expenses for structures built on …

Bias Before Generation: Attention-Based Preemptive Fairness Signals In Large Language Models, Aniket Das

Master’s Dissertations

Warning: This paper includes examples of language that may be perceived as inappropriate or offensive. Large language models (LLMs) are known to propagate social biases embedded in their training corpora, producing outputs that disproportionately disadvantage individuals based on sensitive attributes such as gender, religion, race, sexual orientation and nationality. Existing mitigation strategies are either computationally prohibitive, require access to model parameters, or apply corrections only after biased content has already been generated. This work addresses a different question: can the model’s own internal attention dynamics, observed at inference time, serve as a reliable early-warning signal for bias, enabling intervention before …

The Effect Of Mwcnt-Oil Impregnation Of Sintered Components On Their Wear And Corrosion Resistance, Maha Khaled Abdelfadeel

Theses and Dissertations

Powder Metallurgy (PM) offers an advantageous route for manufacturing complex and near net-shape components. Their inherent interconnected porosity that promotes the action of self lubrication compromises their structural integrity by creating pathways for corrosion and excessive wear. This research investigates the efficacy of Multi-Walled Carbon Nanotubes (MWCNTs) as a nano additive within the impregnating base oil (SN-150 base oil). An experimental matrix was designed to evaluate the influence of MWCNTs with different concentrations of 0.05, 0.1, and 0.2 wt.% and ultrasonic dispersion with varying sonication times of 30 and 60 minutes on the tribological and electrochemical performance of sintered steel …

Engineering Nanoelectrocatalytic Systems For Co2 And Nitrate Conversion Into Value-Added Chemicals, Abdelrahman Mohamed Abdelmohsen

Theses and Dissertations

The thesis addresses two major related environmental crises: nitrate pollution of water systems and the ever-increasing levels of atmospheric carbon dioxide. Both challenges are closely linked to anthropogenic disturbance of nitrogen and carbon cycles and require sustainable, energy efficient mitigation techniques. In this study, we investigate electrochemical conversion routes as a unified approach to convert these pollutants into value-added compounds: ammonia (NH3) via nitrate reduction (NO3-RR) and ethylene (C2H4) via carbon dioxide reduction (CO2RR). The first half of this work deals with the design and engineering of Cu-Zn alloy electrocatalysts for efficient NO3-RR. Tuning the alloy composition and surface nanostructure …

Tuning Ion Mobility And Molecular Confinement In High-Performance Polymer Electrolytes For Energy Storage, Ezzeldien Yousef Muhammed Yousef

Theses and Dissertations

This research addresses the critical energy density limitations of aqueous supercapacitors, which are traditionally constrained by the narrow electrochemical stability window (ESW) of water 1.23 V. By employing two distinct molecular engineering strategies, this study developed high-performance electrolyte systems that significantly extend voltage stability and thermal resilience.

The first system, CsBr@PAM/HA, utilizes a polyacrylamide and hyaluronic acid hydrogel matrix. This system exploits the chaotropic nature of Cs⁺ ions to disrupt the aqueous hydrogen-bonding network, enhancing ionic conductivity to 104 mS cm^-1. Through systematic salt screening, CsBr was identified as the optimal electrolyte, enabling a stable 2.0 V …

Energy Efficient Load Balancing In Multi-Band Cellular Networks Via Reinforcement Learning, Ahmed Shoukry El Soukkary

Theses and Dissertations

This thesis investigates energy-efficient load balancing in homogeneous multi-band cellular networks through the joint design of user association (UA) and transmit power allocation (PA). The original mixed-integer nonlinear formulation is decomposed into two coupled yet tractable subproblems: a UA stage and a PA stage for high-frequency bands. For UA, a SINR-ratio-based heuristic is proposed to prioritize users that are most sensitive to suboptimal band assignments, and it is benchmarked against a Max- SINR baseline. For PA, the high-band power control problem is addressed using reinforcement learning, where a Proximal Policy Optimization (PPO) agent learns power levels and band-activation decisions under …