Digital Commons Network^™

Mems 4110: Precise Water Distribution System, Fadhimah Mohamed, Duyen Nguyen, Citlalli Sanchez-Ayala

Mechanical Engineering Design Project Class

Greenhouse research requires precise, repeatable watering to maintain consistent experimental conditions. As plant counts scale to 150–360 pots, manual watering becomes inefficient, inconsistent. This project aims to design an automated irrigation system that reliably delivers controlled water volumes to an initial set of 36 pots, operates under greenhouse conditions with minimal user intervention, and provides a scalable foundation for future expansion.

Mems 4110: Remotely Deployed Banner, Amiel Josiah Mari B. Silbol, Maxwell A. Fargo, Brant M. Weir, Elias Barro

Mechanical Engineering Design Project Class

This project works in tangent with the Design, Build, Fly club at Washington University in St. Louis as one of the specific challenges required for the 2026 American Institute of Aeronautics and Astronautics' national competition. A banner must be stowed, deployed, and released during flight and must not interfere with the existing flight mechanics of the remote control aircraft.

Mems 4110: Soft Boiled Egg Peeler, Nina Fischer, Ruth Mellin, Jack Salamon, Malaya Hill

Mechanical Engineering Design Project Class

This report outlines the design and evaluation of a hard-boiled egg–peeling device developed for the Saint Louis restaurant Neon Greens. The restaurant prepares an average of 150 soft-boiled eggs daily for dishes such as the Protein Salad. They requested a device able to autonomously peel 150 eggs per hour with minimal employee involvement.

Mems 4110: Air Hockey Table Physics Education Exhibit, Olaoluwa J. Adeniji, Salomon Dessalines, Gyvnn Mendenhall

Mechanical Engineering Design Project Class

This project centers on creating an educational air-hockey exhibit designed for use in a science museum. The goal of the device is to transform a familiar game into a hands-on demonstration of basic physics and engineering concepts such as motion, momentum, energy transfer, and impact forces. Through discussions with our customer, Professor Potter, we established that the exhibit must balance two priorities: it must be fun and intuitive for visitors of all ages, and it must provide meaningful real-time feedback that helps users understand the science behind the experience.

Mems 4110: Science Museum Bernoulli's Demo, Emma Sloan, Carter Hahnfeldt, Luke Mccann

Mechanical Engineering Design Project Class

This report outlines the design and prototyping process of the Science Museum Bernoulli’s Demo (SMBD), a capstone project for MEMS 4110 Senior Design Project at Washington University in St. Louis. The SMBD is a fun game for a children’s science museum designed to demonstrate how the exit velocity of water from a pipe changes based on the pipe diameter. The design intends to teach kids about Bernoulli’s principle by allowing them to choose from two different sized pipes to spray water at a target. The key aspect of the game is that the water flows more slowly out of the …

Deep Learning-Based Change Detection In High-Resolution Remote Sensing Imagery, Hazem Badawy

Theses and Dissertations

Remote sensing has become a key tool for monitoring Earth’s surface over time, offering valuable insights into both natural and human-driven changes. Among its many applications, change detection focuses on analyzing multi-temporal imagery to reveal how specific areas evolve across different time periods. It plays a pivotal role in Earth observation applications, including urban development monitoring, environmental degradation assessment, and disaster response. However, existing approaches often struggle with limited contextual awareness, high sensitivity to noise, and imprecise localization of change boundaries, especially with high-resolution imagery. This thesis investigates the complex problem of change detection in remote sensing imagery by proposing …

2025 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the fall of 2025.

Ai-Driven Autonomous Manufacturing: A Novel Taxonomy, Vision-Guided Planning, And Diversity-Aware Active Learning Frameworks, Ibrahim Yousif

Theses and Dissertations

Manufacturers face two opposing challenges: the escalating demand for customized products and the pressure to reduce lead times. Current manufacturing equipment, although reliable, operates at the limits of its technology and lacks adaptability to dynamic environments. This trade-off has been described as the optimal degree of automation, a threshold beyond which further automation incurs more cost than benefit. Smart manufacturing has introduced adaptive, data-driven systems, but many deployments still lack the contextual adaptability and autonomous decision-making required to handle unplanned disruptions. This underscores the need for intelligent, autonomous systems capable of real-time adaptation without costly reconfiguration, minimizing human intervention during …

Towards Accurate First-Principles Modeling In Heterogenous Catalysis: Ethane Dehydrogenation And Hydrogenolysis Over Pt Catalysts, Mubarak Ayo Bello

Theses and Dissertations

First-principles modeling has become central to heterogeneous catalysis research, offering mechanistic insight and guiding catalyst design, yet conventional approaches often struggle to accurately describe complex catalytic systems due to methodological uncertainties, simplified assumptions, and the structural diversity of nanoparticle catalysts. This dissertation addresses these challenges using ethane dehydrogenation (EDH) and hydrogenolysis (EH) over platinum catalysts as model systems. The first study benchmarks density functional theory (DFT) functionals against the random phase approximation (RPA) for the EDH network on Pt(111), identifying cost-effective functionals and demonstrating the efficiency of BEEF-vdW ensembles for capturing functional uncertainty. The second study (addressed in prior work) …

Machine-Learning-Assisted Discovery Of Lattice Dynamics Signatures Of Sodium Superionic Conductors, Ogheneyoma Maxwell Aghoghovbia

Theses and Dissertations

Sodium superionic conductors are key to the development of all-solid-state sodium batteries. Discovery of new superionic conductors has traditionally relied on insights from material defect chemistry and the transition/hopping theory, while the role of lattice vibrations, i.e., phonons, remains underexplored. We identify key lattice dynamics signatures that govern ionic conductivity by analyzing the phonon mean squared displacement (MSD) of Na⁺ ions. By high-throughput screening of a dataset of 3903 Na-containing structures, we establish a strong positive correlation between phonon MSD and diffusion coefficients, providing a quantitative correlation between lattice dynamics and ion transport. To accelerate this discovery, we incorporate …

Building Services Engineering September/October 2025

Building Services Engineering

No abstract provided.

Exploring The Effects Of Excipients On Complex Coacervation, Xianci Zeng, Pratik U. Joshi, Alexander Lawton, Lynn M. Manchester, Caryn Heldt, Sarah L. Perry

Michigan Tech Publications

Complex coacervation is an associative liquid–liquid phase separation phenomenon that takes place due to the electrostatic complexation of oppositely-charged polyelectrolytes and the entropic gains associated with the release of bound counterions and rearrangement of solvent. The aqueous nature of coacervation has resulted in its broad use in systems requiring high biocompatibility. The significance of electrostatic interactions in coacervates has meant that studies investigating the phase behaviors of these systems have tended to focus on parameters such as the charge stoichiometry of the polyions, the solution pH, and the ionic strength. However, the equilibrium that exists between the polymer-rich coacervate phase …

Machine Learning Classification Of Eeg Responses To Pain-Related Vs Non-Pain-Related Stimulus In Preterm Infants, Lojain Hamwi, Hang Du, Sara Jasim, Xiaogang Wang, Vibhuti Shah, Carol Cheng, Lorenzo Fabrizi, Maria Fitzgerald, Judith Meek, Nicole Racine, Ian Stedman, Rebecca Pillai Riddell

Michigan Tech Publications

INTRODUCTION: Unmanaged pain in preterm infants can lead to long-term developmental consequences. Current pain assessment methods lack specificity, resulting in possible pain mismanagement in Neonatal Intensive Care Units (NICUs). This study explores the application of machine learning (ML) to differentiate between pain-related and non-pain-related cortical activity in preterm infants. OBJECTIVE: To evaluate the performance of ML models in distinguishing cortical EEG activity during a painful procedure in preterm infants across different postmenstrual ages (PMAs). METHODS: This observational study was conducted from June 2015 to May 2024 at Mount Sinai Hospital in Toronto, Canada, and University College London Hospital, United Kingdom. …

Characterization Of Cooled Turbine Efficiency For Off-Design Performance Models, Alberto Garcia

Doctoral Dissertations and Master's Theses

Gas turbine performance modeling is essential for predicting engine behavior across design and off-design conditions. Yet the treatment of cooling or service flows remains inconsistent, as these streams interact with the main flow in complex ways and their contribution to turbine work depends on how they are represented in performance models. The challenge is especially present in “black-box” approaches, where only inlet and outlet conditions are known and engineers must decide whether to introduce cooling flows upstream (if performing useful work) or downstream (if not). This thesis examines how different definitions of isentropic power and cooling-flow treatment affect the apparent …

Characterization Of The Fatigue Threshold Behavior Of Uhmwpe, Bethany B. Smith, Anurag Roy, Robert O. Ritchie, Lisa A. Pruitt

Faculty Journal Articles

Ultra-high-molecular-weight-polyethylene (UHMWPE) has been the material of choice for bearings in total joint replacements (TJRs) for decades as a result of its excellent wear resistance, chemical inertness, energetic toughness, low friction, and biocompatibility. Utilization of this polymer in orthopedic devices requires oxidation, wear, and fatigue resistance. Balancing these important properties by tailoring processing techniques and modulating microstructural features has been an ongoing endeavor in the field. Research into the clinical applications of UHMWPE has primarily focused on the challenges of wear and oxidation while studies into the realm of fatigue have been more limited. Literature gaps exist in fully understanding …

Lightweight Population-Based Policy Optimization For Pickup And Delivery Problems, Yizhou Liu, Li Li, Yixin Xu, Tang Liu, Rong Cheng, Die Wu, Jilin Yang, Jingwen Li

Research Collection School Of Computing and Information Systems

In recent years, applying deep models to automatically learn construction heuristics for vehicle routing problems has achieved remarkable advancements. However, they are less effective in searching solutions due to two primary limitations: relying on deterministic probability distributions and overlooking the strategic advantage of prioritizing nearby unvisited nodes during the route construction process, resulting in suboptimal policies In this paper, we propose a novel lightweight population-based policy optimization (LPPO) framework that learns a diverse population of solution strategies through the utilization of innovative perturbation factors, in order to facilitate search exploration. Moreover, we design a localized attention synthesis (LAS) network to …

Exploring Object Status Recognition For Recipe Progress Tracking In Non-Visual Cooking, Franklin Mingzhe Li, Kaitlyn Ng, Bin Zhu, Patrick Carrington

Research Collection School Of Computing and Information Systems

Cooking plays a vital role in everyday independence and well-being, yet remains challenging for people with vision impairments due to limited support for tracking progress and receiving contextual feedback. Object status — the condition or transformation of ingredients and tools — offers a promising but underexplored foundation for context-aware cooking support. In this paper, we present OSCAR (Object Status Context Awareness for Recipes), a technical pipeline that explores the use of object status recognition to enable recipe progress tracking in non-visual cooking. OSCAR integrates recipe parsing, object status extraction, visual alignment with cooking steps, and time-causal modeling to support real-time …

High-Fidelity Modeling Of Evtol Rotor Unsteady Aerodynamic And Aeroacoustic Response To Time-Harmonic Gust, Vadim Voropayev

Doctoral Dissertations and Master's Theses

The rapid emergence of Urban Air Mobility (UAM) demands accurate prediction and mitigation of noise generated by electric vertical take-off and landing (eVTOL) aircraft operating in complex urban environments. Among the various noise sources, the aerodynamic and acoustic response of rotors to unsteady inflow represents a major uncertainty in community-noise assessment and certification. This thesis investigates the aerodynamic and aeroacoustic behavior of a representative eVTOL rotor subjected to time-harmonic inflow disturbances, providing a detailed numerical framework to quantify how periodic gusts influence rotor performance, unsteady loading, and sound radiation.

The study employs a three-stage computational methodology using the open-source solver …

Internal Resonance Of A T-Shaped Electrostatic Levitation Actuator, Ali Eskandari, Mohammad Alzgool, Yu Tian, Mohammad I. Younis, Shahrzad Towfighian

Mechanical Engineering Faculty Scholarship

This study explores the internal resonance of a T-shaped beam subjected to electrostatic forces at the MEMS scale. The actuator's unique configuration includes a side substrate, a fixed bottom substrate, and a suspended beam, enabling out-of-plane movement when excited. The T-shaped beam is designed to have a commensurate ratio of 1:2 between the fifth and sixth modes. The mathematical model of the system is developed and the shooting method is used to solve the reduced order model. Theoretical and experimental results reveal the interaction of two modes. The results indicate that due to the exchange of energy between the two …

Rain, Rain, Go Away: Geoengineering And The Illusion Of Control, Hannibal Newsome

The Lender Center for Social Justice

In this article, Newsom critiques geoengineering proposals by examining how they reflect a human impulse to exert control over nature; a control that may be illusory. The piece argues that while geoengineering is increasingly touted as a solution to climate change, it brings with it ethical, ecological, and political risks that are often underappreciated, including unintended side effects, issues of governance, and moral hazard. The author calls for more caution, rigorous oversight, and humility in considering geoengineering as part of climate policy.

Advances In Encapsulated Phase Change Materials For Integration In Thermal Management Applications, Muhammad Ghufran, David Huitink

Mechanical Engineering Faculty Publications and Presentations

Encapsulated phase change materials (ePCMs) have the potential to emerge as a key solution for efficient thermal management in various applications. This review paper explores the recent advancements in ePCMs for thermal energy storage and thermal management. We start with a basic overview of the PCMs and then performance enhancements of PCMs through the encapsulation, critical parameters for encapsulation, various encapsulation methods, and their evaluation are discussed. This review also discusses key properties and proposed figure of merit for ePCMs, impact of encapsulation on thermophysical properties, performance evaluation of ePCMs, thermal management needs, and the role of PCMs. The paper …

Performance Limiting Factors For Silicon Anodes In Lithium-Ion Batteries, Najmaddin Bashirzada

Theses and Dissertations

The rising global demand for high-performance and sustainable energy storage solutions has placed lithium-ion batteries (LIBs) at the forefront of technological progress. However, the energy density limits of traditional graphite anodes require the investigation of alternative materials. Silicon (Si), with its high theoretical capacity, is a promising anode material. Still, its practical use faces major challenges such as volumetric expansion, unstable solid electrolyte interphase (SEI) formation, and low conductivity. This thesis examines the electrochemical behavior and limitations of Si-based electrodes using coin cells and ex-situ three-electrode cells. A comparison of electrochemical testing methods – i.e., Galvanostatic Intermittent Titration Technique (GITT) …

Downwind-Upwind Flux Path Analysis Method For Model Reduction Performance Evaluations, Christian Robert Smith

Theses and Dissertations

Large, complex chemical kinetic models have long since been limited by the computational cost it takes to evaluate said model. Over time many reduction methods have been developed to combat this computational cost. However, very little has been done towards evaluating the limitations of reductions as a way of understanding the original model’s characteristics. This paper aimed to use a path flux analysis-based reduction algorithm to rapidly develop multiple reduced mechanisms for a 96 species FFCM-2 methane chemical kinetic model as well as an 858 species n-Dodecane chemical kinetic model. The goal of formulating these reduced mechanisms was to identify …

Towards Accurate First-Principles Modeling In Heterogenous Catalysis: Ethane Dehydrogenation And Hydrogenolysis Over Pt Catalysts, Mubarak Ayo Bello

Theses and Dissertations

First-principles modeling has become central to heterogeneous catalysis research, offering mechanistic insight and guiding catalyst design, yet conventional approaches often struggle to accurately describe complex catalytic systems due to methodological uncertainties, simplified assumptions, and the structural diversity of nanoparticle catalysts. This dissertation addresses these challenges using ethane dehydrogenation (EDH) and hydrogenolysis (EH) over platinum catalysts as model systems. The first study benchmarks density functional theory (DFT) functionals against the random phase approximation (RPA) for the EDH network on Pt(111), identifying cost-effective functionals and demonstrating the efficiency of BEEF-vdW ensembles for capturing functional uncertainty. The second study (addressed in prior work) …

A Building Block Approach To Certification By Analysis Applied To A Ditching Analysis, Preliminary Studies, Sean Taylor

Theses and Dissertations

Extended Twin-Engine Operations (ETOPS) certification ensures safe trans-oceanic operation of transport category aircraft. A critical aspect of ETOPS certification is compliance with ditching regulations. The importance of ditching analysis has grown significantly and come under greater scrutiny because of the ‘Miracle on the Hudson’ incident. For transport category aircraft certified under 14 CFR 25 regulations, compliance with ditching requirements, rests on two major components. First, demonstrating acceptable aircraft dynamic behavior during the ditching event and second, ensuring the airframe can withstand the loads generated because of water impact.

Historically, original equipment manufacturers (OEMs) relied on comparisons to existing aircraft with …

Implicit Neural Representation For Image Reconstruction, Canyu Zhang

Theses and Dissertations

Image reconstruction seeks to restore corrupted images and recover visual content that has been lost or degraded. Such degradation may result from low resolution, occlusion, masking, or shadow interference. This problem has become an increasingly significant research topic, as visual information plays a central role in almost every aspect of modern life. Neural network based approaches have recently emerged as highly effective solutions for this task. In particular, convolutional neural networks and transformer based architectures have demonstrated remarkable success in producing visually convincing reconstructions. However, these models remain constrained in several important ways, one of the most critical being that …

Recognizing The Unexpected: Deep Learning Across Complex Environments, Ge Song

Theses and Dissertations

Ensuring the security, trustworthiness, and operational integrity of modern autonomous and cyber-physical systems presents a critical challenge. While widely utilized in various engineering applications, such as intelligent transportation and industrial manufacturing, these systems require robust monitoring frameworks to identify unexpected anomalies in real-time, thereby maintaining operational safety and efficiency. This dissertation develops advanced deep learning methodologies for anomaly detection and health monitoring, with a particular emphasis on semisupervised reconstruction-based approaches that identify anomalies in complex environments using models trained only with normal operational patterns.

Building on this theme, the first study focuses on analyzing pedestrian behavior and detecting anomalies at …

Spectral Modeling Of Electromagnetic Radiation From Power Converters, Regan A. Varner

Theses and Dissertations

Switching power converters are increasingly utilized in contemporary electronics. They are becoming more compact and operate at higher frequencies, which contributes to radiated electromagnetic interference (EMI). This EMI is important to quantify for electromagnetic compatibility of the converters with other nearby systems. In this thesis, analytical models have been developed for both ideal and non-ideal switching waveforms, employing piecewise functions to describe time-domain waveforms, with their corresponding frequency spectra derived and compared to empirical spectra. The results demonstrate that the comparisons with measured frequency data exhibit agreement with the analytical models up to approximately 25 MHz. Additionally, our analysis indicates …

Calculating Surface Current Velocities From Video Generated From A Near Forward-Facing Camera, Colby James Weeks

Theses and Dissertations

This work presents a camera system for estimating surface currents. A combined camera and IMU system provide high resolution images and high precision orientation information, respectively. This eliminates the need for leveling and enables forward looking operation. The hardware stack includes a Lucid Vision Triton TRT162S monochrome camera, an SBG Ellipse D with dual antenna GNSS for precise pose, and an Nvidia Jetson Orin for acquisition and processing. The Ellipse D provides a hardware trigger at 10 Hz to time stamp each frame and to synchronize images with inertial measurements.

A camera calibration step estimates the intrinsic camera parameters and …

Towards Robust Bmocz Schemes For Non-Coherent Wireless Communication, Anthony Joseph Perre

Theses and Dissertations

Non-coherent communication has emerged as a promising approach to address several challenges at the physical layer. A particular scheme called binary modulation on conjugate-reciprocal zeros (BMOCZ) uses the zeros (i.e, roots) of a polynomial to convey information bits. In this thesis, we strive to improve the reliability of BMOCZ in various scenarios. In particular, we utilize machine learning (ML) methods to determine the parameters for BMOCZ and improve upon the decoding performance. Moreover, we introduce a smooshed BMOCZ variant to combat typical impairments encountered within wireless communications, including timing offsets (TOs) for noncoherent orthogonal frequency division multiplexing (OFDM). Through numerical …