Other Engineering Commons^™

Insect Inspired Behavioral Strategies For Improving Multi-Agent System Resilience In The Presence Of Contagious Faults, James E. Hand

Doctoral Dissertations and Master's Theses

As Multi-Agent Systems (MASs) become increasingly involved in every aspect of everyday life the need to maintain reliability and resilience within these systems grows. However, in equal measure bad actors wishing to maliciously control or alter these systems are growing in both scale and capability. Thus, there is a present need for control schemes and agent behaviors that provide security against these threats while also avoiding large degradation in system performance as a tradeoff. Current research has covered a wide breadth of avenues and strategies that provide measurable resilience to faulted agents. However, these strategies often require group consensus, specialized …

Quantification Of The Depth-Of-Field In A Self-Aligned Focusing Schlieren System, Alexander Ephraim

Doctoral Dissertations and Master's Theses

This thesis investigates self-aligned focusing schlieren (SAFS) as a step toward future volumetric and quantitative measurements of three-dimensional compressible flows. Conventional schlieren imaging provides valuable visualization of density gradients, but it records only a line-of-sight projection and therefore does not directly resolve the spatial distribution of structures through the depth of the flowfield. SAFS addresses part of this limitation by introducing depth sensitivity, but its depth response has not been well characterized quantitatively. To help lay the foundation for future volumetric and quantitative SAFS methods, this work addresses two related problems. First, calibrated quantitative schlieren imaging is applied to an …

Cavitation-Aware Design Of Hydrofoil Sections For Marine Propeller Blade Development, Samuel G. Bacon

Mechanical & Aerospace Engineering Theses & Dissertations

Cavitation is a major design constraint for marine propeller blade sections because it can reduce hydrodynamic performance, increase vibration and noise, and contribute to surface damage. This thesis develops and applies an exploratory computational framework for cavitation-aware hydrofoil-section design relevant to marine propeller blade development. The framework combines section-level CFD validation, CST-based geometry parameterization, pressure-based pre-screening, matched-load comparison, and focused predicted inception envelope or cavitation-bucket analysis.

The CFD methodology was validated against published YS-920 hydrofoil water-tunnel data using selected fully wetted, near-inception, and cavitating reference cases. The validation results showed that the adopted framework reproduced the key experimental trends needed …

A Theoretical Framework For Recursion In Complex System Governance, Gilbert Goddin

Engineering Management & Systems Engineering Theses & Dissertations

The purpose of this research was to construct an original theoretical framework for understanding recursion in Complex System Governance (CSG), grounded in the propositions and axioms of systems theory and management cybernetics. This framework addresses a research gap for cybernetic recursion relating to the governance of complex systems. Leveraging the CSG framework (Keating & Katina, 2019; Keating, 2022), holonic principles (Koestler, 1970; Mella, 2009), management cybernetics (Beer, 1979; Beer, 1984; Beer, 1995), and metacybernetics (Yolles, 2021; Yolles & Fink, 2015c; Yolles & Frieden, 2021), recursion is theorized as a governable capability, whereby metasystemic governance anticipates emerging complexity and purposefully regulates …

Development Of A Benchmark Building Condition Index Utilizing Discrete Facility Subsets For Use In Risk Prioritization Analysis, Christopher A. May

Engineering Management & Systems Engineering Theses & Dissertations

Within the healthcare facilities management arena, key performance-based condition indices such as a calculated Building Condition Index (BCI) are currently utilized as a governing indicator of facility health and performance. However, BCI alone does not adequately support enterprise-level risk prioritization and fails to provide a validated facility-to-facility risk prioritization model. Assets within the same enterprise receiving similar sustainment funding experience different rates of degradation depending on asset type and construction age thus impairing the BCI rating scale. Statistical analysis of facility metrics indicates a strong correlation between facility degradation drivers and prediction of a subset-based benchmark BCI. The research validates …

Downstream Effects Of Post Aerobic Digestion And Divalent Cation Treatment: Dewaterability, Phosphorus Mitigation, And Process Odors, Maya Marisol Quijano Garcia

Civil & Environmental Engineering Theses & Dissertations

This study evaluated post-aerobic digestion (PAD) with aeration, mixing, and divalent cation addition to improve phosphorus capture, dewaterability, and odor control in thermal hydrolysis process (THP)–treated anaerobic digestate at the Hampton Roads Sanitation District’s Atlantic Treatment Plant. A three-day PAD process was operated under constant air flow (5 LPM) and dissolved oxygen (DO)-setpoint (0.2 mg/L) aeration conditions with Ca(OH)₂ or Mg(OH)₂ dosing. Aeration and mixing alone increased polymer demand by 14–46 % relative to untreated influent, indicating enhanced extracellular polymeric substance release. Chemical conditioning partially mitigated this increase but did not restore polymer demand to baseline levels. Dewatered cake total …

Bridging Mission And Execution: Integrating Participatory Design In Early-Phase Mission Engineering For Stakeholder Alignment And Mission Clarity, Rafi Soule

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation develops and evaluates an integration-centered approach to early-phase Mission Engineering that improves mission clarity under ambiguity. Stakeholder interpretations diverge, and interoperability constraints are not surfaced early. These conditions reduce mission clarity and weaken mission-to-system mapping readiness. The dissertation proposes an integration-centered approach that strengthens early mission framing through two complementary mechanisms: (1) a participatory design-inspired, artifact-first workflow that surfaces and repairs interpretation divergence, and (2) closed-corpus, RAG-enabled retrieval that grounds mission-to-system mapping in traceable evidence. The study was organized around a construct spine linking shared understanding, stakeholder alignment, and interoperability feasibility to mission clarity. A three phase mixed-methods …

Deep Learning Based Control System For Multi-Zone Hvac Residential Buildings, Mohammad H. Z. Alghalayeeni

Mechanical Engineering Theses

Heating, ventilation, and air conditioning (HVAC) systems are major contributors to residential energy consumption. However, most homes continue to rely on single zone thermostat control, which regulates temperature based on a single sensor and cannot account for thermal variations across multiple rooms. This often leads to uneven thermal conditions and inefficient energy use in multi-zone residential buildings. This thesis presents a deep reinforcement learning based approach for improving HVAC zoning control through dynamic airflow distribution. A physics based multi zone thermal model of a residential house was developed to simulate heat transfer processes including conduction, convection, solar and internal heat …

Multi-Modal Tensor Fusion For Alzheimer’S Disease Recognition, Mason Li, Tiffany Le, Jiajing Huang, Yuxin Wen

Engineering Faculty Articles and Research

Accurate and early diagnosis of Alzheimer’s disease (AD) is critical for effective intervention, disease monitoring, and patient care. Traditional diagnostic approaches rely on a single modality, such as clinical assessments, neuroimaging, or genetic markers, which may fail to capture the complex, multifaceted nature of AD. Multimodal learning has therefore been explored to integrate complementary information across data sources. However, conventional fusion strategies, including early feature concatenation and late decision-level fusion, often model modalities independently and fail to capture high-order cross-modal interactions. To address these limitations, we propose a multimodal tensor fusion network (MTFN) that integrates heterogeneous data sources, including visual …

Sustainability Tool Inventory, Robert Moore, James O'Donnell

Tools

The purpose of this inventory is to inform Irish organisations, including the private sector, public agencies and semi-states, about Sustainability Tool

Developing Low-Cost Gnss Remote Sensing Hardware To Measure Precipitable Water Vapor For Flash Flood Nowcasting In Southern Appalachia, Austin Gleydura

Student Research Symposium (SRS)

Flash flood prediction in Southern Appalachia is particularly challenging due to steep terrain, narrow valleys, highly localized rainfall patterns, and limited measurement coverage. Traditional remote sensing methods, such as Doppler radar and microwave radiometry, suffer from reduced resolution at extended range and signal blockage by mountains, while satellite instruments like MODIS lack sufficient spatio-temporal resolution for sub-kilometer measurements critical to flash flood nowcasting. GNSS-Meteorology offers an established alternative for measuring precipitable water vapor (PWV) and is currently integrated into several numerical weather models. Recent research demonstrates that GNSS-derived PWV products can be used to accurately predict rainfall intensity and timing …

Dual-Function Plasmonic Structure For Logic Operations And Circular Polarization Detection, Marjan Bazian, Mark C. Harrison

Engineering Faculty Articles and Research

Many integrated photonic devices have a high potential for dual applications, making them more versatile components in photonic integrated circuits. In this study, we show that a plasmonic XOR gate structure, originally designed to perform logic operations, can also be used as a circular polarization detector. This multi-purpose capability stems from the phase-encoded input mechanism that controls the output response of the structure. We adapted this mechanism to select the output based on the polarization state of light. The design of this structure, utilizing the subwavelength field confinement of plasmonic waveguides, enables the integration of logic and detection functions into …

Computational Modeling Of Enhanced Nonlinear Optical Response In Plasmonic Waveguide Devices With Epsilon-Near-Zero Films, Kevin T. Le, Mark C. Harrison

Engineering Faculty Articles and Research

Silicon photonics faces fundamental limitations in nonlinear applications due to weak Kerr nonlinearity, substantial two-photon absorption, and coupling challenges with subwavelength structures. This work investigates epsilon-near-zero (ENZ) materials integrated into plasmonic waveguide architectures for enhanced nonlinear photonic devices. ENZ materials exhibit nonlinear refractive indices several orders of magnitude higher than conventional materials near their zero-permittivity wavelength, enabling giant optical effects over deeply sub-wavelength interaction lengths. We present finite element method simulations of plasmonic ENZ waveguides, investigating layer thickness optimization for nonlinear enhancement while minimizing optical losses. Initial modal analysis confirms superior field confinement in hybrid plasmonic-ENZ structures compared to conventional …

Cancerseg-Xa: Medical Histopathology Segmentation System Based On Xception Backbone And Attention Mechanisms, Alaa Youssef, Wessam H. El-Behaidy, Aliaa Youssif

Computer Science

Accurate segmentation of histopathological images is essential to support early diagnosis and effective treatment planning in cancer care. This study presents CancerSeg-XA, a deep learning-based histopathology segmentation system designed to deliver robust performance across diverse tissue types and imaging sources. Built upon the DeepLabV3+ framework, CancerSeg-XA incorporates architectural enhancements to strengthen feature representation and improve model stability. The system was evaluated on three widely recognized datasets—BCSS, PanNuke, and PUMA—each presenting distinct structural and clinical challenges. Across all datasets, CancerSeg-XA consistently outperformed the baseline DeepLabV3+ in terms of segmentation accuracy, recall, and F1-score. Specifically, it achieved accuracy improvements of 4.78%, 4.31%, …

Dynamic Soliton Solutions And Stability Analysis Of The (2+1)-Dimensional Wazwaz Kaur Boussinesq Equation Using An Efficient Method, Nivan Mohamed Elsonbaty, Hamdy Mohamed Ahmed, Niveen Mohamed Badra, Wafaa B. Rabie

Basic Science Engineering

This paper presents the first application of the Modified Extended Direct Algebraic (MEDA) method to the (2+1)-dimensional Wazwaz-Kaur-Boussinesq equation, a model governing wave dynamics in shallow waters. The approach successfully uncovers previously unreported classes of exact solutions, including combo dark–singular solitons and Jacobi elliptic function solutions. The spectrum of obtained solutions–which also encompasses bright, dark, and singular solitons, as well as hyperbolic, periodic, exponential, and rational functions–reveals rich and complex soliton dynamics. A comprehensive stability analysis confirms the robustness of these solutions under perturbation. These results significantly advance the understanding of wave propagation in nonlinear systems, providing valuable insights for …

Mycelium-Based Composites Using Minimally Processed Industrial Hemp Biomass: Impact Of Species And Feedstock Ratio On Mechanical Performance Compared To Polystyrene Packaging, Radika Bhaskar, Tanisha Rutledge, Kevin Trangone, Oneal Latimore

School of Design and Engineering Papers

Mycelium-based composites (MBCs\) are formed from lignocellulosic substrates and biopolymer matrices derived from fungal mycelium. Due to their low fossil energy demand and biodegradability, MBCs represent a versatile and sustainable material suitable for a range of applications, with increasing interest focused on packaging. Hemp fibers are an example of natural fibers with great promise as a substrate to improve the mechanical properties of MBCs. However, the separation of bast and hurd fiber requires processing and commercial-scale facilities that are logistically challenging and may be cost-prohibitive. Here, the potential for minimally processed hemp, with no separation of fibers, is evaluated for …

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 …

Assessing The Influence Of Land Use Land Cover Alterations On Climate Variability In Thimphu & Chhukha, Sonam Zangpo, Karma Choki, Tashi Tobgay, Phurpa Rinchen, Tandin Tshewang

ASEAN Journal on Science and Technology for Development

This study examines the spatiotemporal dynamics of land use and land cover (LULC) changes and their influence on local climate variability in Bhutan using an integrated geospatial and machine learning framework. LULC changes during the period 2004 to 2022 were analyzed to understand their relationship with localized climate responses. Despite increasing urbanization pressures, comprehensive assessments linking LULC dynamics with climate variability in Bhutan remain limited. Geographic Information System (GIS) techniques and Random Forest classification were used to map LULC changes, while non-parametric trend analyses (Mann–Kendall test and Sen’s slope estimator) were applied to evaluate trends in key meteorological variables, including …

Automation And Habitat Development For A Space Based Marine Life Environment, Logan Trimmer, Alexander Hang

Harrisburg University Other Works

This project was a cross-collaboration between the Environmental Sciences and Advanced Manufacturing and Robotics programs for the company Monolith Space.

The goal of this project was to design an autonomous system to be able to track qualities of water in an aquaculture system designed to be sent to space.

Ai-Based Porosity Detection In Babbitt Bore Turning, Kaylee Leggett, Hannah Adams Gemmell, Kaisa Shingleton

Williams Honors College, Honors Research Projects

For this project, an external company reached out to the University of Akron requesting assistance with defect detection during their vertical turning operations. As babbitt is removed in a vertical turning process, it occasionally reveals defects, mainly porosity, which can lead to costly downstream failures of the part. Current inspection techniques involve use of dye penetrant, which is time consuming, labor intensive, unergonomic, and a source of human error. The goal of the project is to create an alternative inspection method using an AI-based machine-learning model. After the turning operation, a camera is deployed to perform an in-place inspection, taking …