Engineering Commons^™

Performance Reviews In Project-Based Engineering Firms: Toward A More Holistic And Development-Oriented Approach, Xun He

Harrisburg University Dissertations and Theses

Performance reviews are widely used in engineering consulting firms to evaluate employee contributions and determine compensation and promotion decisions. However, research has shown that traditional review systems may overemphasize measurable technical results while overlooking collaboration, leadership, and innovation. In project-based engineering environments, where employees work across multiple teams and stakeholders, this structure may not fully reflect the nature of daily work. This qualitative phenomenological study explored how early-career engineers in project-based engineering consulting firms experienced performance review practices. Data were collected through semi-structured interviews with 15 engineers working in consulting firms. The study examined participants’ perceptions of fairness, completeness, and …

Efficient Energy Management In Networked Microgrids Using Multi-Agent Deep Reinforcement Learning In The Presence Of Uncertainties, Ayodele Benjamin Chukwuyem

Dissertations

Microgrid technology is essential in facilitating the transition to smart energy grids in developed countries and mitigating energy poverty in developing countries, particularly in areas where grid extensions are not feasible. Recently, the concept of networked microgrids (NMGs) has garnered tremendous attention due to the plausibility of interactions among interconnected microgrids leading to power networks that are more resilient, reliable, and stable. However, because each microgrid has diverse distributed generation resources (renewables and controllable generators) and each microgrid operator (MO) has different objectives, coordinated energy management is required to satisfy local and system-wide goals under conditions with significant uncertainty. Existing …

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 …

An Integrated Bayesian Network-Based Zero Trust Model To Quantify Cyber Risk In Small-Medium Businesses, Ahmed Abdelmagid

Engineering Management & Systems Engineering Theses & Dissertations

Small-medium businesses (SMBs) play a pivotal role in the worldwide economy as they constitute the most considerable portion of businesses in developed countries like the UK and the US. As such, SMBs are likely targets of cybercrimes by malicious agents because of their vulnerable IT systems. The digital infrastructure of SMBs is more likely to be hit by cyberattacks than large businesses due to many factors that facilitate hackers’ missions. These factors include a limited financial budget devoted to cybersecurity, a lack of knowledge, an underrating of how dangerous cyber threats are, and a shortage of IT expertise. The enormous …

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 …

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 …

Electromyography, Prosthetic Properties, And Running Biomechanics In Recreationally Active Persons With Lower Extremity Amputation, Paige M. Agnew

Rehabilitation Sciences Theses & Dissertations

Lower extremity loss affects nearly 150,000 individuals in the United States yearly yielding extreme health care costs annually. Typically, prosthetic devices are prescribed for 5-8 years despite known changes to an individual’s gait as time progresses. Patients can expect to undergo approximately 8-12 weeks of gait retraining to improve their comfort and efficiency. Biomechanical changes occur when running with a specific running prosthetic including considerable biomechanical and neuromuscular interlimb asymmetries and alterations in loading patterns. The purpose of this dissertation was to investigate the biomechanical demands for lower extremity prosthesis users during running. The first study synthesized peer reviewed evidence …

Microstructural And Thermal Studies Of Niobium On Copper Fabricated By Sputtering And Multicharged Ion Deposition, Md Obidul Islam

Electrical & Computer Engineering Theses & Dissertations

Niobium-coated copper (Nb/Cu) superconducting radiofrequency (SRF) cavities are a promising alternative to bulk niobium cavities for next-generation particle accelerators due to their reduced material cost and superior thermal conductivity of the copper substrate. However, cavity performance is fundamentally limited by the microstructural quality of sputtered Nb films and thermal transport across the Nb/Cu interface. Reduced thermal diffusivity in thin films and high interfacial thermal resistance contribute to localized heating and performance degradation under high RF fields. This dissertation addresses these challenges through a combined experimental and methodological investigation of thermal transport in Nb thin films, focusing on interface engineering using …

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 …

Optimization Of Niobium Film For Particle Accelerators And Quantum Applications, Bektur Abdisatarov

Electrical & Computer Engineering Theses & Dissertations

Niobium (Nb) films play a central role in superconducting technologies used in particle accelerators and superconducting quantum circuits. Optimizing the physical properties of Nb films is therefore critical for improving both radiofrequency (RF) performance in superconducting radiofrequency (SRF) cavities and coherence in superconducting qubits. This thesis investigates the relationship between Nb film microstructure, impurity content, and electromagnetic response across these two application domains.

For particle accelerator applications, we studied Nb films deposited using high-power impulse magnetron sputtering (HiPIMS) with DC bias onto a 1.3 GHz elliptical SRF cavity. Nb film cavities exhibit a pronounced medium-field Q-slope, limiting their achievable accelerating …

Mechanisms Of Synergy Between Nanosecond Pulsed Electric Field (Nspef) And Cold Atmospheric Pressure Plasma Discharge (Cap) In Pancreatic Cancer: The Role Of Ros-Mediated Oxidative Stress And Apoptosis, Zobia Minhas

Theses and Dissertations in Biomedical Sciences

Pancreatic ductal adenocarcinoma is a highly lethal malignancy characterized by poor prognosis and resistance to conventional therapies. Novel treatment strategies are needed to overcome this resistance. Non-thermal physical modalities, including nanosecond pulsed electric field (nsPEF) and cold atmospheric pressure plasma discharge (CAP), have emerged as potential anticancer approaches; however, the mechanisms underlying their combined effects remain unclear.

This study evaluated whether nsPEF enhances CAP-induced cytotoxicity and investigated the associated molecular mechanisms using the murine Pan02 pancreatic cancer cell line. Cell viability was assessed by WST-1 metabolic activity assays and electric cell–substrate impedance sensing (ECIS). Intracellular reactive oxygen species (ROS) were …

Bleachers Constructed From Reclaimed Structural Lumber, Ben Aaron , ‘26, Amelia Landry , ‘26, Zoe Sperduto , ‘26

Senior Theses, Projects, and Awards

This project designs bleachers from reclaimed structural lumber for the new Fieldhouse at Swarthmore College. Wood is a sustainable and renewable building material, and diverting wood from the waste stream for high-value applications offers an opportunity to promote a circular economy. Wood reuse is not a common practice in the United States, and this project aims to serve as a case study of how it can be performed on small, local scales. First, deconstructed lumber is obtained from a local residential demolition site and processed. Then, destructive material testing is performed to determine the residual material properties, strength and stiffness, …

Optimization Of Pumping Kite Wind Energy Conversion System, Jamie Pickar , ‘26, Sam Peterson , ‘26, Luke Magnuson , ‘26

Senior Theses, Projects, and Awards

Airborne wind energy systems (AWES) promise access to higher-altitude wind resources at lower capital cost than conventional turbines. This thesis presents a rigid-wing, ground-generation AWES prototype developed across two coupled subsystems: a kite designed for harnessing wind energy and a generator station designed for efficient pumping-cycle operation.

The kite subsystem progressed through three design generations. We replaced ball-joint wing mounts with fixed joints, derived a tail design using tail volume coefficients, and validated the tail through fusion 360 stress testing and Unity game engine simulation. The final prototype of the kite demonstrated approximately 25 seconds of passive transient flight stability …

Breaking The Fourth Wall: Structural Accessibility In Theaters, Maddie Adams-Miller , ‘26, Abbey Peters , ‘26

Senior Theses, Projects, and Awards

Historic theaters, especially those on Broadway, are in high demand but often lack appropriate access for patrons with disabilities. This work evaluates existing barriers to physical accessibility in historic theater spaces and develops a model to address as many of these barriers as possible. Through the implementation of the double diamond research method, it was ensured that the experience of the end user was centered, and prototypes were created to address these identified needs. This two-part design solution includes a scale model of an idealized theater and a prototype of a universally accessible seat, as well as a set of …

Time-Correlated Photons From Spontaneous Parametric Down-Conversion (Spdc), Aaron Dubois , ‘26, Tanvir Islam , ‘26, Prashan Thapa Magar , ‘26

Senior Theses, Projects, and Awards

Time-correlated photons can be used to demonstrate emerging technical applications such as ghost imaging, and they can demonstrate quantum-based phenomena in order to interest undergraduate students in engineering applications involving optics and quantum mechanics. In this work, we use spontaneous parametric down-conversion to generate time-correlated photons. To achieve this, we simulated laboratory parameters with MATLAB and designed optical and electrical setups. Specifically, we used a 405 nm diode laser, various common optical components, and a nonlinear crystal designed to generate time-correlated photons, and we used single-photon detectors, time-to-amplitude converters, custom flash-conversion analog-to-digital converters, a Teensy 4.1 microcontroller, and the Arduino …

An Interpretable Hybrid Deep And Reinforcement Learning Paradigm For Glioma Prognosis, Renuga Devi M Ms

Theses and Dissertations

Brain tumors are highly aggressive and lethal types of cancer, particularly gliomas. These cancerous growths show complicated pathophysiological behaviours and with poor prognosis despite therapeutic advances. Due to their biological differences and infiltrating growth, as well as overlapping radiological characteristics, they pose great difficulty in diagnosis, grading, and survival prediction. Artificial intelligence technology, which includes machine learning , deep learning, and reinforcement learning has developed into a new paradigm for the automation of brain tumor diagnostics and personalized treatment. The main goal of this study is to create an integrated AI-based framework that can perform brain tumor segmentation, grading and …

Development Of Deep Fused Neural Architecture For Ancient Tamil Palm-Leaf Manuscript Recognition, Hariharan P Mr

Theses and Dissertations

Digitizing Tamil palm-leaf manuscripts is important for education, communication, and the preservation of cultural heritage. The complex structure of the Tamil script, the wide range of handwriting styles, and the degradation seen in ancient Tamil palm-leaf manuscripts make these texts very difficult to read and understand. Digital Image Processing (DIP), document analysis techniques, and traditional Optical Character Recognition (OCR) are unable to handle noise, background interference, faded ink, and limited labelled data, motivating the need for robust, effective Deep Learning (DL)- based solutions.

As a prerequisite to understanding and designing effective recognition systems for ancient manuscripts, this thesis first examines …

Evaluating Runtime Monitoring For Reinforcement Learning-Based Flight Control, Andrew Zubyk

Doctoral Dissertations and Master's Theses

Ensuring safety in adaptive flight controls systems is an ongoing challenge in aviation, especially as advancements in artificial intelligence and machine learning (AI/ML) trend upwards. Reinforcement learning is becoming more common in aerospace applications due to the ability to improve these models through training.  While models such as reinforcement learning enable controllers to learn complex behaviors from interaction with the environment, their unpredictability in novel or disturbed conditions raises severe concerns in safety-critical domains. This research investigates the integration of runtime monitoring, a real-time assurance technique, with reinforcement learning-based flight controllers to ensure safety and reliability during flight. By supervising …

A Pretraining-Based Framework For On-Device Training Of Imu-Based Locomotion Mode Detection For Wearable Active Exoskeletons, Muhammad Tahir Khan

LSU Master's Theses

Active exoskeletons are being developed to support human movement in physically demanding industries such as construction. For these systems to work effectively, they must be able to correctly identify the user’s current activity. This process is known as locomotion mode detection and plays an important role in selecting the appropriate control parameters for exoskeletons. Many existing approaches use inertial measurement units (IMUs) to recognize these activities and have shown strong performance. However, most of these methods depend on large amounts of labeled data collected under specific conditions. As a result, they often do not perform well when applied to new …

Wearable Sensor System Used To Measure Linear And Angular Acceleration Of The Head Of American Football Players, David A. Emerson

LSU Master's Theses

American football players are repeatedly subject to high-velocity impacts; collisions can exceed 100 g in the NFL [1]. Rotational accelerations of the head caused by high-velocity collisions have been proven to be extremely damaging to the highly organized brain fibers at the brain-skull interface [2]. The sensor system (SS) measures the nonplanar acceleration at four locations on a chin strap using ADXL314 accelerometers and utilizes rigid-body kinematics to estimate the head rotational state from the measured acceleration of the SS [3]. The SS was validated through progressive testing, including steady-state, linear impact, and rotational impact testing. The ADLX314 sensor exhibited …

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 …

Electrochemical Sensors And Processes In Molten Salts: Chlorine Production, Electroanalytical Chemistry, And Thin-Layer Electrodes, Tyler Williams

Theses and Dissertations

Molten salt electrochemistry has historically played a substantial role in the metallurgical industry, and this trend is only accelerating in areas of green steel, direct ore processing, and rare-earth processing. In addition, the recent surge of interest in molten salt nuclear reactors has provided an additional application for molten salt electrochemical processes, including the reprocessing of used nuclear fuels and the development of electrochemical sensors for nuclear applications. In this work, the development of a chloride volatility separation process for used nuclear fuel is advanced; electroanalytical methods are improved for identifying and quantifying unknown analytes with and without the presence …

Mould Risk Prevention In Healthcare Facilities In Hot And Humid Climates Through Acmv Air Supply Parameter Optimisation: Development And Validation Of A Multi-Objective Optimisation Framework, Jiang Kaiyun

Student Works (2020-2029)

Air conditioning mechanical ventilation (ACMV) supply parameters—such as airflow rate, temperature, and humidity—significantly influence indoor thermal and hygrometric conditions, influencing airflow patterns and mould proliferation. In healthcare facilities, mould poses significant health risks, particularly for immunocompromised patients, contributing to respiratory issues, allergic reactions, and infections. While ACMV systems are central to infection control and indoor air quality, conventional designs often fall short in hot and humid climates. Existing practices typically prioritise high air change rates (ACH) without sufficient dehumidification, underestimate humidity control, and assume spatial homogeneity, overlooking microclimates conducive to localised mould growth. To address these limitations, this research develops …

Rigorous Electromagnetic Beamforming Simulations For Realistic Vehicular-To-Infrastructure (V2i) Scenarios In 5g Systems, Mohanad Hussam Aldean Ahmed Almuzian

Theses and Dissertations

Millimeter-wave (mmWave) Vehicle-to-Infrastructure (V2I) communication is a key enabling technology for next-generation intelligent transportation systems, offering high data rates and low latency to support safety-critical and autonomous driving applications. However, mmWave communication at 28 GHz suffers from severe path loss, sensitivity to blockage, and strong dependence on antenna directivity and beam alignment, particularly in complex urban environments. As a result, advanced beamforming and multi-antenna techniques are essential to ensure reliable and high-capacity V2I links. This thesis investigates mmWave V2I communication performance using realistic electromagnetic modeling and beamforming techniques. Full-wave antenna simulations and deterministic ray-tracing are employed using Ansys Electronics Desktop, …

Marine Vehicle Dynamics Using Koopman Operator Theory With Hybrid Observables, Mikhalib A L Green

LSU Master's Theses

Accurate modeling of marine vehicle dynamics remains challenging due to strong nonlinear hydrodynamic effects, environmental disturbances, and sensitivity to configuration changes, particularly for small-scale platforms. Classical physics-based models require extensive parameter identification and often exhibit degraded performance outside narrow operating regimes, while purely data-driven approaches may lack structure or impose high computational cost. This thesis presents a data-driven Koopman operator framework with hybrid observables for modeling the dynamics of unmanned marine vehicles. The proposed approach combines structured monomial observables with a learned neural network embedding to construct a lifted state representation in which the nonlinear vehicle dynamics are approximated by …

Large-Scale File Fragment Classification Via Multi-View Learning, Samuel Hildebrand

LSU Master's Theses

File reassembly is one of the most fundamental tasks in digital forensics, enabling recovery of data from potentially damaged storage media even when file system metadata is unavailable. This thesis reviews more than two decades of work in the realm of file carving, with a particular focus on fragmented file carving, which remains a focus of research, and file fragment classification, a principal component of fragmented file carving. This thesis serves a literature review of both file carving and fragmented file carving, surveys the massive amounts of data needed for the task of fragment classification and the datasets that serve …

Arid: Agglomerative Regionalization Via Information Divergence, A Novel Clustering Algorithm For Geo-Spatial Data, Joshua David Sills

Dissertations and Theses

Regionalization is a clustering problem that seeks to partition geospatial data into geographically contiguous regions while remaining internally homogeneous in their attributes. It has been successfully applied towards the development of urban planning, natural resource discovery, and ecological analysis. Existing popular approaches optimize homogeneity using Euclidean or variance-based criteria, which ignore distributional differences such as variance shifts, multimodality, and higher-order dependence. This thesis introduces ARID (Agglomerative Regionalization via Information Divergence), a spatially constrained agglomerative clustering framework that replaces distance-based merging with an information-theoretic, Ward-like criterion that utilizes the Kullback-Leibler (KL) divergence. ARID constructs a neighborhood graph from coordinate space and …

Identification Of Thruster Faults In Underwater Vehicles By Using Custom Encodings In Spiking Neural Networks, Donovan Gegg

LSU Master's Theses

Autonomous Underwater Vehicles (AUVs) are untethered robotic platforms used for tasks such as seafloor mapping, infrastructure inspection, and environmental monitoring. Recent technological advances have produced smaller, more affordable platforms, broadening access to research teams and small companies alike. This miniaturization comes at the cost of them handling drawbacks associated with a more compact machine such as reduced battery capacity as well as limited processing and sensing capabilities. These constraints make small-sized marine vehicle’s reliability critical as they can cause malfunctions, making the loss of a vehicle more likely. Actuator faults are particularly consequential as unintended and unstable control in an …

Polymer Microstructures For Advanced Biomanufacturing, Tongyao Wu

LSU Doctoral Dissertations

With the continued growth of the biopharmaceutical industry, the demand for scalable, robust, and resource-efficient platforms for large-scale mammalian cell culture is amplified. Recent developments in microfluidic technology, such as precise control of the microenvironment, showed the potential to improve the performance of cell culture systems. However, constrained by scalability and operational efficiency, applying such approaches to large-scale cell culture and biopharmaceutical production presents challenges. This dissertation addresses these challenges through three independent but conceptually related technological developments. First, a roll-to-roll (R2R) fabrication process was developed for the scalable production of hollow microcarriers (HMCs). HMCs provide three-dimensional microenvironments suitable for …

Graph-Based And Uncertainty-Aware Machine Learning For Academic Performance Prediction, Anca Olivia Muresan

Electronic Theses and Dissertations

Early identification of students at risk of academic failure is essential for timely pedagogical interventions and reducing dropout rates. While Artificial Intelligence (AI) has significantly advanced predictive modeling in education, two primary challenges persist: effectively modeling the complex, evolving relationships within heterogeneous educational data, and ensuring the reliability of model outputs for high-stakes decision-making. This dissertation addresses these challenges by proposing a comprehensive framework for early and continuous student performance prediction applied to the Open University Learning Analytics (OULA) dataset. First, we introduce a Heterogeneous Graph Neural Network (HGNN) approach that utilizes metapath structures to capture latent interactions between diverse …