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Effects Of Ball Milling Duration And Sintering Temperature On Mechanical Alloying Fe3si, Varistha Chobpattana, Chakansin Phoomkong, Peerawat Nutnual, Kritsada Thaengthong, Wanchai Pijitrojana

Journal of Metals, Materials and Minerals

Fe3Si is under interest as a ferromagnetic electrode of magnetic tunneling junctions (MTJs). Its crystalline structure is important for achieving high device efficiency. This work focuses on mechanical alloying of 3:1 ratio of 99% pure Fe and Si powder mixtures by ball milling and sintering. The mixtures were ball-milled for various durations up to 20 h. Then, they were sintered from 400°C  to 800°C for 4 h in Ar.  SEM images and particle size analysis show significant reduction in average particle size of the mixtures after ball milling for 20 h. The longer duration of ball milling process promotes powder …

Elevate Hardcase, Caleb J. Bailey, Colby M. Cordoba, Marissa Mccleod, Shaan Sandhu

Mechanical Engineering

The Elevate Hardcase project developed a portable mechanical elevation system that allows users to access rugged hard cases at a comfortable working height without needing a separate table or placing the case on uneven ground. The design focuses on improving ergonomics, portability, stability, and quick setup for users in field environments such as photography, hunting, and maintenance. Through customer research, concept development, prototyping, analysis, and testing, the final system was designed to support a loaded hard case, provide height adjustability, remain stable on uneven terrain, and be deployed by a single user in under five minutes. The final prototype demonstrates …

A Maximum Energy Release Rate Computational Framework For Fatigue Crack Trajectory And Life Prediction Under Mixed-Mode Proportional And Nonproportional Loading, Nahla Helmy Matar

Theses and Dissertations

The problem of mixed-mode fatigue crack growth has been a persistent research challenge. The determination of fatigue crack propagation direction directly impacts the safety and integrity of components and structures, making it crucial in various industrial applications, including welded drilling pipes, aerospace, and automotive engineering. Unlike uniaxial loading, mixed-mode cracks tend to change direction frequently (kinking), and nonproportional loading adds to the complexity of the problem. This research aims to estimate the crack propagation direction and fatigue crack life in linear elastic materials subjected to mixed-mode (I+II) loading conditions under proportional or non-proportional cyclic loading. Numerical software was developed based …

Simulation-Based Assessment Of Operational And Retrofit Solutions For Effluent Compliance Of A Capacity-Limited Oxidation Ditch Wwtp, Ahmed Sameh Harash

Theses and Dissertations

Oxidation-ditch wastewater treatment plants (WWTPs) across Egypt's Nile Delta are increasingly carrying hydraulic and organic loads beyond what they were designed for. This work can be considered pioneering as this work compared operational and structural retrofit alternatives for such a plant within a single verified simulation framework. The present study fills that gap by building a digital twin of the Qaha WWTP, a dual-train Carrousel oxidation ditch in Qalyubia Governorate, calibrated to a baseline flow of 7,420 m³/day in the SUMO24 platform (a third-generation, open-source wastewater treatment process simulation software) using the SUMO2c biokinetic model (a simplified variant of Activated …

Dynamic Baseline Schedule Updates Using Digital Twinning: A Case Study On Aluminum Formwork Construction, Ahmed Hamdi Sweilam

Theses and Dissertations

Repetitive high-rise construction using aluminum formwork couples consecutive floor cycles through a reused panel set and a floor-level inspection and pour barrier, so productivity loss compounds upward rather than being absorbed locally. The baseline schedule is nevertheless fixed before execution and is not revised as evidence of realized productivity accumulates. This thesis develops a simulation-based digital twin that updates the baseline from observed as-built durations and acts on its own forecast. A discrete-event simulation of a ten-story residential tower is built in AnyLogic® and verified analytically at 180.00 hours per floor. After each completed floor the twin infers activity productivity …

Sustainable – Low-Cost - Upgrade Of Activated Sludge Process For Nitrogen And Phosphorus (N&P) Removal From Wastewater, Abanoub N. Basta

Theses and Dissertations

Many municipal wastewater treatment plants (WWTPs) in developing countries were designed primarily for organic matter and suspended solids removal and therefore face increasing difficulty in meeting modern nitrogen (N) and phosphorus (P) discharge requirements. Conventional biological nutrient removal upgrades commonly require additional reactor volume, recirculation systems, aeration energy, and capital investment. Accordingly, sustainable retrofit strategies that improve nutrient removal within existing treatment footprints are increasingly needed, particularly in water-scarce and land-constrained regions.

This study investigated the integration of water hyacinth (Eichhornia crassipes) into the aeration stage of an activated sludge process as a hybrid nature-based enhancement for nitrogen and phosphorus …

Deep Brain Stimulation In Early-Stage Alzheimer's Disease: A Systematic Review Of Neuropsychological Outcomes, Nora Huey

Doctoral Dissertations

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairment, and disruption of neural networks involved in cognitive functioning. Although existing treatments may provide symptomatic benefit, there remains a need for interventions capable of slowing or stabilizing disease progression. Deep brain stimulation (DBS) has emerged as a potential neuromodulatory intervention for early-stage AD through stimulation of memory- and cognition-related neural circuitry. This dissertation employed a systematic review research methodology to examine teh neuropsychological and neurobiological outcomes associated with DBS targeting the fornix (DBS-f) and nucleus basalis of Meynert (DBS-NBM) in individuals with early-stage AD over 12–24 …

Enhancing Shipboard Safety Management Under The Ism Code: An Innovative Risk Assessment Framework With A Stern Tube Case Study, Pi-Yen Lin

Journal of Marine Science and Technology–Taiwan

The shipboard safety management system (SMS) is designed to enhance safe operations, risk management, and emergency response to improve overall ship safety and efficiency. This paper demonstrates the use of an engine room simulator (ERS) for collecting failure modes and applies it to a comprehensive failure analysis of the stern tube lubricating oil system. A new risk closeness coefficient method was developed, integrating expert background knowledge and weighted risk assessments. The analysis, based on multiple expert evaluations, covered five subsystems, eight main components, 23 failure modes, and 112 failure causes. This study presents 26 recommendations for maritime practitioners and onboard …

Port And Vessel Communication Traffic Intrusion Detection: A Variational Autoencoder‑Enhanced Multilayer Perceptron Approach, Chien-Lin Chiang, Hsien-Cheng Chou, Ming-Yuan Peng, Yi-Yuan Chiang, Yu-Shun Liu

Journal of Marine Science and Technology–Taiwan

Port and vessel networks increasingly operate on IP/Ethernet backbones with high‑noise, high‑dimensional traffic. We present a lightweight hybrid intrusion‑detection model that couples a variational autoencoder (VAE) with a multilayer perceptron (MLP) and augments training with a boundary‑oriented latent‑space mixup strategy. The VAE models the distribution of normal traffic and identifies anomalies through reconstruction errors. Subsequently, it generates robust latent vectors, enabling the MLP to perform highly accurate supervised classification. On the UNSW‑NB15 dataset, the proposed pipeline attains ≥97% accuracy and an outstanding recall of 99.56% in binary intrusion detection, and visualization of the latent space (PCA) together with reconstruction‑error analyses …

Sar Ship Detection Based On Shallow Feature Guidance, Chenxu Xia, Peng Chen, Ya Zhang, Ying Li

Journal of Marine Science and Technology–Taiwan

Maritime ship detection is of great significance for both military security and civilian applications. Synthetic Aperture Radar (SAR), with its all-weather and all-day imaging capability, plays a vital role in maritime surveillance. Nevertheless, SAR ship targets typically appear small in scale, embedded in complex backgrounds, blurred at boundaries, and easily confused with near-shore features, which pose substantial challenges for accurate detection. To address these issues, we propose a SAR ship detection network that integrates dual enhancements of small-object representation and edge information. The network introduces two key components: the Small Target Refine Pyramid (STRP) to strengthen shallow feature representation for …

Adaptive Active Snore Noise Control Using Microphone And Loudspeaker Arrays, Nathan Walker

All Graduate Theses and Dissertations, Fall 2023 to Present

Snoring can wreck a good night’s sleep, not just for the snorer but for their partner, and over time it can strain relationships. Common fixes like CPAP machines, nasal strips, and earplugs either have to be worn or don’t do much against the deep, low-pitched rumble that makes snoring so hard to ignore.

This research explores a different approach, a device that doesn’t need to be worn at all. It uses a small set of microphones to listen to the snoring and a set of speakers to play back carefully timed anti-snore noise, which is sound designed to cancel out …

Scalable Quality Assessment Of Ground Motion Records Via Interpretable Deep Learning Architectures, Ali Montazeri Namin

All Graduate Theses and Dissertations, Fall 2023 to Present

Earthquake engineers rely on accurate recordings of ground shaking to design safe and resilient buildings. However, sorting through thousands of these recordings to find the reliable ones and throwing out those ruined by sensor errors or background noise is traditionally done by hand. Because modern seismic networks collect massive amounts of earthquake data every day, this manual checking process is much too slow. To fix this, researchers are turning to artificial intelligence to automatically check the quality of these recordings.

While artificial intelligence offers a fast solution, there are limitations. These computer models can become massive and expensive to run, …

Cascaded Pid Control Of A Passive Bio-Inspired Rotating Empennage Aircraft, Zachary T. Jenkins

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis presents an autopilot for a Bio-Inspired Rotating Empennage (BIRE) aircraft. Most airplanes control yaw using a vertical stabilizer and a moving rudder, a design that has stayed essentially unchanged for nearly a century but adds weight, drag, and surface area to the aircraft. The BIRE removes the vertical tail entirely and instead allows the horizontal tail to rotate about the body x-axis of the airplane; tilting the horizontal tail produces a yaw force, doing the job of a rudder. This thesis first develops a controller for the BIRE where the empennage angle is commanded directly, then extends …

Physics-Data-Hybrid Modeling And Control For Vtol Aircraft, Samantha Dawn Burton

All Graduate Theses and Dissertations, Fall 2023 to Present

Vertical takeoff and landing (VTOL) aircraft are hybrid aircraft having both a helicopter flight mode and a fixed-wing plane flight mode. The objective of this dissertation is to examine and evaluate a new approach, physics-data-hybrid (PDH), for VTOL aircraft modeling and control. The PDH approach combines traditional, physics-based methods (Newtonian mechanics) with data driven methods (a machine learning technique called a Koopman operator model) to create an efficient and accurate modeling and control framework—mitigating the disadvantages of the purely physics-based and purely data-driven methods. The PDH approach is used to model scenarios when the VTOL aircraft transitions between helicopter mode …

Enhancing Agricultural Sustainability Under Climate Change: A Multi-Scale Framework Integrating Climate Extremes, Resource Efficiency, And Data-Driven Modeling, Shahryar Fazli

Computational and Data Sciences (PhD) Dissertations

Agricultural systems are increasingly challenged by climate variability, where shifting temperature regimes, hydrological variability, and the rising frequency of compound and cascading extremes threaten global food security and resource sustainability. Addressing these challenges requires integrated frameworks that bridge biophysical monitoring, predictive modeling, and adaptive decision-making. This dissertation develops a data-driven, multi-scale framework to quantify and enhance agricultural resilience by integrating remote sensing, climate analytics, and machine learning across the United States, with a focus on California and the Western U.S.

First, hyperspectral and thermal remote sensing data from EMIT and OpenET are integrated to characterize crop nitrogen–water interactions and assess …

Evaluating The Impact Of Research Equipment Availability On Scientific Rigor, Reproducibility, And Innovation Across Stem Disciplines, Lyndi G. Hraban

Honors Program: Senior Projects (Public)

Research infrastructure plays a central role in shaping the quality and innovative capacity of scientific research. This study evaluates how the availability of research equipment influences scientific rigor, reproducibility, and innovation across STEM disciplines. Drawing on literature from science-to-science research, policy studies, and discipline-specific analyses, this project synthesizes existing scholarship to explore the relationship between access to infrastructure and key research outcomes. Findings across the literature indicate that access to advanced and well-maintained equipment can strengthen scientific rigor by enabling more precise measurements, improved experimental control, and the implementation of standardized research protocols. Shared and centralized facilities are also associated …

Power At Sea Develop Phase, Jake Lauer, Isabella Heinemann, Bailey Gargasz, Zachery Boyer

Mechanical Engineering

This project develops a renewable, wave-powered charging system designed to extend the mission duration of Autonomous Underwater Vehicles by eliminating the need for frequent manual battery replacement. Building upon a prior oscillating water column prototype from the CONCEPT phase, the team redesigned and tested an improved system capable of converting wave-induced air motion into electrical power using a Wells turbine. Key enhancements include doubling the column diameter to increase displaced air volume, integrating a flared inlet and bi-directional nozzle to improve airflow, and selecting corrosion-resistant materials suitable for long-term deployment in marine environments. Multiple prototypes were constructed and evaluated through …

Psychometric Evaluation And Cognitive Correlates Of The Tactile Mental Cutting Test: Investigating Reliability, Validity, Gender Differences In Spatial Ability, Executive Function And Social Emotional Competence Among Native American Elementary Students, Sujata Basnet

All Graduate Theses and Dissertations, Fall 2023 to Present

Spatial ability-the ability to understand, visualize, and mentally manipulate shapes and objects-is important for learning in science, technology, engineering, and mathematics (STEM). However, many traditional spatial ability tests rely heavily on drawings and other visual representations and have often been developed and evaluated with populations that do not adequately represent culturally diverse students. As a result, there is a need for assessment approaches that are developmentally appropriate, engaging, and potentially more inclusive for young learners. The Tactile Mental Cutting Test (TMCT) provides one such approach by allowing students to explore three-dimensional objects through touch and physical manipulation while solving spatial …

Long Range Battery-Free Wireless Power Transfer Testbed For Underground Mines Iot And Lpwan Devices, Anabi Hilary Kelechi, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

Underground mines are susceptible to occasional roof falls and cave-ins, temporarily destroying the existing wireless communications and telemetry infrastructure. During this temporary outage, intermittent provision of electrical energy wirelessly to the already deployed low-power wireless area networks (LPWAN) and Internet of Things (IoT) devices assumes a fundamental requirement. In this article, we propose and design a long-range far-field radio frequency (RF) wireless power transfer (WPT) testbed to power LPWAN and IoT devices at 35 m in an underground mines facility. Class AB external power amplifier (PA) was introduced to achieve a long-distance RF WPT, in the 880 MHz band. Thus, …

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …

A Data-Driven Koopman Framework For Station-Keeping On Near Rectilinear Halo Orbit, Anusha Sharma Malladi

Theses and Dissertations

Cislunar missions have gained significant attention in recent decades, motivating the need for efficient modeling and reliable control. In this work a Koopman operator based framework is developed for approximating the error dynamics around a reference Near Rectilinear Halo Orbit (NRHO) in the Earth-Moon Circular Restricted Three-Body Problem (CR3BP). A decoder free neural network is used to learn a lifted linear representation of the nonlinear CR3BP dynamics and a residual based approach is used to identify the corresponding control input matrix. The model is then implemented in a receding-horizon target point controller and compared with uncontrolled propagation and a State …

Comparative Performance Of Physiological Vital-Sign Forecasting Under Random And Patient-Wise Splitting Using Deep Learning, Lavanya Vasavi Chittem Reddy

Theses and Dissertations

Physiological vital-sign forecasting estimates future measurements based on recent temporal patterns and can support analysis of continuously recorded monitoring data. This study comparatively evaluated deep feedforward, recurrent, bidirectional recurrent, long short-term memory, and bidirectional long short-term memory architectures for one-step-ahead forecasting of peripheral oxygen saturation, heart rate, and pulse rate. Each model received consecutive observations of peripheral oxygen saturation, heart rate, pulse rate, respiratory rate, and age, while separate single-output models predicted the next value of the selected target.

Random and patient-wise data splitting were compared using identical input definitions, preprocessing procedures, model architectures, and training hyperparameters. The strongest architecture …

Developing Imitation Learning Policies By Exploring Diffusion Framework For Quadcopters, Likith Swamireddy

Theses and Dissertations

Imitation learning offers a promising approach in developing near-optimal onboard policies for nonlinear systems, by learning from computationally expensive trajectory planners during offline training. Existing State-of-the-art methods commonly learn deterministic mappings from observations to actions by training fast neural networks to mimic the expert demonstrations, which can limit their ability to capture the action distribution, when the policy is trained on multiple possible expert commands to reach the same target, and this may lead to unsafe scenarios in the obstacle environments. To address these challenges, this study explores Diffusion Models (DMs) as a feedback controller for quadcopters that learns the …

Effect Of Preheating Palm Oil Biodiesel Fuel On The Performance And Emissions Of Diesel Engine Common Rail Direct Injection, Nanang Romandoni, Achmad Aminudin, Hari Setiapraja, Bima Randi Wardiasaputra, Kelvin Dwi Wardana, Ahmad Yusril Aminullah, Deni Nur Fauzi, Kholis Nur Faizin, Nur Ihda Farikhatin Nisa

Journal of Mechanical Engineering Science and Technology (JMEST)

Fossil fuel consumption continues to increase while its reserves continue to decrease and produce high emissions that trigger global warming. Therefore, more environmentally friendly alternative energy is needed. Biodiesel is a sustainable choice because it is biodegradable, low in sulphur, and can replace fossil fuels. This study investigates the influence of biodiesel fuel preheating temperature on engine performance, fuel consumption, and emissions in a Common Rail Direct Injection (CRDI) diesel engine. The experimental method was carried out by heating B40 and B50 fuels at temperatures of 40°C to 60°C at intervals of 10 °C. Engine performance was evaluated using a …

Structural And Electrochemical Characterization Of Na2co3/ Γ- Al2o3 Electrodes For Supercapacitor, Wiwin Dwiana, Jeniva Dinta Nanda Fahreza, Anissa Chairani Alfin Nadhira, Fatimatuz Zahra, Erma Surya Yuliana, Muhammad Safwan Abd Aziz, Nandang Mufti

Journal of Mechanical Engineering Science and Technology (JMEST)

The development of electrode materials with suitable structural and surface properties is crucial for improving electrochemical energy storage systems. Gamma alumina (𝛾-Al₂O₃) has attracted considerable interest in electrochemical research due to its unique structural and surface properties. However, its charge-storage capacity is still limited, highlighting the need for structural and compositional modifications to improve its electrochemical performance. In this study, Na₂CO₃ was introduced into 𝛾-Al₂O₃ as a sodium precursor to induce phase modification and enhance the electrochemical activity. The systematic incorporation of Na₂CO₃ also provides an opportunity …

A Systematic Review Of Alkali-Treated Polylactic Acid Biocomposites Relevant To Pineapple Leaf And Water Hyacinth Hybrid Design, Muhammad Rizky Adrianto Subandi, Tri Hartutuk Ningsih, Hanna Zakiyya

Journal of Mechanical Engineering Science and Technology (JMEST)

The increasing demand for sustainable materials has accelerated the development of biodegradable polymer composites. Polylactic acid (PLA)-based natural fiber composites have attracted significant attention due to their renewable characteristics; however, their performance remains limited by weak fiber–matrix compatibility, moisture sensitivity, and inconsistent interfacial behavior. Alkali treatment has been widely applied to modify lignocellulosic fibers by removing non-cellulosic components and improving surface characteristics, although its effectiveness remains dependent on treatment conditions and fiber properties. This systematic review evaluates the influence of alkali treatment on PLA-based natural fiber composites and assesses the available evidence supporting future pineapple leaf fiber (PALF) and water …

Machine Learning Local Potentials For Accelerated Electron-Phonon Interactions Calculations Within The Projector Augmented-Wave Framework, Yi Xia

Mechanical and Materials Engineering Faculty Publications and Presentations

No abstract provided.

A Review Of Gallium And Germanium Recovery From Industrial Solid Residues, Ernest V. Oteng, Marthias Silwamba, Lana Alagha, Alex Luyima

Mining Engineering Faculty Research & Creative Works

The global demand for critical elements such as gallium (Ga) and germanium (Ge), and the shift toward circular mining has accelerated the development of new extraction and recovery processing these metals from industrial solid residues. This transition is driven by a substantial surge in demand for advanced technologies and the depletion of primary ore. Consequently, industrial solid residues, particularly zinc processing residues, smelter slags, flue dusts, and coal fly ash, are emerging as viable alternative sources. These residues incorporate Ga and Ge through isomorphic substitution in phases such as ferrites, silicates, and glassy aluminosilicates, and are enriched by industrial processes, …

Prototyping Pinhole Collimators For Imaging Irradiated Nuclear Fuel, Narrie Loftus, Ashish Avachat, Joseph T. Graham, Ryan Fronk, Jordan Fox, Rachel Shaffer, Seth Kilby

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

Collimator design and fabrication is a costly and time-consuming process that does not lend itself to simplified testing. This manuscript presents an approach for the rapid prototyping of sub-millimeter pinhole collimators for nuclear fuel applications using low-melting-point, high-mass-density materials. Multiple collimators were fabricated to test collimator parameters and properties, including acceptance angle, aperture diameter, and magnification. The fabricated collimators were paired with a position-sensitive CdZnTe detector to determine the detector response convolved with the collimator. Preliminary analysis using these collimators showed that they were effective in collimating multi-energy gamma laboratory sources. Radiography was performed to confirm magnification and determine coarse …

Lrq-Solver: A Transformer-Based Neural Operator For Fast And Accurate Solving Of Large-Scale 3d Pdes, Peijian Zeng, Guan Wang, Haohao Gu, Xiaoguang Hu, Tiezhu Gao, Zhuowei Wang, Aimin Yang, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

Solving large-scale PDEs on complex three-dimensional geometries remains a central challenge in scientific and engineering computing, often due to expensive pre-processing stages and high computational overhead. We present Low-Rank Query-based PDE Solver (LRQ-Solver), a physics-integrated deep learning framework for efficient CAE simulations of complex three-dimensional geometries in CAD-driven design analysis. Built upon the Parameter-Conditioned Lagrangian Modeling (PCLM) that embeds physical consistency into the learning process and the Low-Rank Query Attention (LR-QA) module that reduces attention complexity from O(N2) to O(NC2+C3) via covariance decomposition, LRQ-Solver supports multi-configuration analysis within iterative design workflows. On two benchmark datasets, it achieves a 28.6% error …