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2026 (Spring) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the spring of 2026.

Near-Wall Void Distribution Characterization In Pebble Bed Reactor Using Gamma-Ray Ct And Dem Simulation, Ahmed Jasim, Mauricio Maestri, Abdullah Al Zubaidi, Omar Farid, Muthanna Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Accurate characterization of void-fraction distributions in pebble-bed reactors (PBRs) is essential for predicting flow, heat transfer, and neutronic behavior. High-fidelity experimental benchmark data for validating such predictions remain scarce, largely due to the challenges of non-invasive measurements. In this study, gamma-ray computed tomography (CT) was employed to measure radial and cross-sectional porosity in a laboratory-scale pebble bed containing 6cm graphite pebbles. A Discrete Element Method (DEM) simulation was implemented and validated against these measurements, then applied to the full-scale geometry of the Xe-100 high-temperature gas-cooled pebble-bed reactor. Analyses included radial and axial void-fraction profiles in the cylindrical section and conical …

Artificial Intelligence In Human Spaceflight Safety-Critical Systems: A Requirements Framework For Ai-Enabled Computer-Based Control Systems, Liz Bosch

Doctoral Dissertations and Master's Theses

Currently, there is no governing standard that addresses the safe integration of AI into computer-based control systems (CBCS) in human spaceflight. The computer-based control expectations of those safety-critical systems on the International Space Station (ISS) are captured in SSP 50038, Computer-Based Control System Safety Requirements, with one caveat: the standard was not designed with AI applications in mind. SSP 50038 does not cover the probabilistic behavior, opacity, and training-data dependency of modern AI/ML systems. The objectives of this work is to develop an AI taxonomy relevant to safety characteristics (determinism, transparency, data dependency, failure predictability), systematically map AI characteristics against …

A Comparative Study On Performance Of Iot-Driven Ml-Enabled Forecasting Models For Efficient Air Quality Monitoring, Bara Ksiksi

Theses

Air pollution is one of the most critical environmental challenges affecting public health globally, responsible for approximately 4.2 million premature deaths annually according to the World Health Organisation. This thesis presents a comparative study of IoT-driven machine learning forecasting models for air quality monitoring in Abu Dhabi, UAE, introducing a zonal approach combined with satellite-based spatial validation. The primary objective is to evaluate forecasting performance across three distinct activity zones using ground station data from the Environment Agency Abu Dhabi (EAD), and to incorporate a spatial validation component using satellite imagery to assess the consistency of ground-based predictions at a …

Traditional And Machine-Learning Equalization Techniques For Bandwidth-Limited Short-Reach Optical Communication Channels, Abdullah Khawatmi

Theses

This thesis investigates equalization techniques for bandwidth-limited short-reach optical communication systems, with a focus on Visible Light Communication (VLC) and Step-Index Plastic Optical Fiber (SI-POF) links. Commercial light-emitting diodes and photodiode receivers impose severe bandwidth constraints, inter-symbol interference, and noise sensitivity, which fundamentally limit achievable data rates. The work addresses these impairments through systematic evaluation of traditional digital signal processing–based equalizers and modern machine-learning-based post-equalization methods. The primary aim of this thesis is to enhance the achievable data rate and reliability of commercial short-reach optical links while maintaining practical computational complexity. Specifically, the objectives are to (i) design and experimentally …

Modeling And Autonomous Control Systems For A Delivery Drone Application, Dana Helal Alnuaimi

Theses

This thesis focuses on the development of a multi-drone navigation and control system, aiming to enhance payload capacities beyond the limits of single-drone systems. By integrating multiple drones to work collaboratively as a unit, this study addresses the challenges associated with lifting and transporting heavier payloads.

The primary objective is to design and evaluate a multi-drone system capable of working in tandem to transport larger payloads efficiently. The research aims to develop robust control algorithms, supported by system identification for dynamic modeling, and navigation strategies to enable effective coordination between drones.

The study employs a combination of simulation and real-world …

Analysis Of A Coaxial Transmission Line Filled With An Orthorhombic Dielectric-Magnetic Medium, Fathima Manikunnath Abdul Akbar

Theses

Coaxial transmission lines are fundamental means for Transverse Electromagnetic (TEM) wave propagation in RF, microwave and high-speed electronic systems. The study of transmission lines is often familiar when they are filled with isotropic materials; however modern engineered direction dependent materials reshape field distributions. In this thesis, we consider a coaxial transmission line of an inner radius and outer radius b filled with an orthorhombic dielectric-magnetic material, which is described by two anisotropy parameters αx and αy. The potential and field distributions are studied in relation to the ratio b/a as well as the anisotropy parameters αx and αy. Due to …

Efficient Fpga Implementation Of A 1 Million-Point Fft, Jwaher Abdulqader Al Tamimi

Theses

The one-million-point Fast Fourier Transform is implemented using a radix-2 single-path delay feedback pipeline architecture. To minimize the computational overhead, twiddle factors were pre-computed and stored in memory. The design uses a fixed-point representation with two integer bits and seven fractional bits, achieving a measured signal-to-noise ratio of 37.98. Given the substantial memory requirements, a memory partitioning approach was used. It mapped the delay buffers in each stage lookup table memory, block random-access memory, or ultra random-access memory, based on word width and memory depth.

The implementation operates successfully at 100 megahertz on a mid-scale field-programmable gate array. Post-implementation reported …

Breath-Based Detection Of Liver Cancer Biomarkers Using An Swcnt-Fet Nano-Biosensor: Quantumatk, Mohamed Mohieb Rashdan

Theses

Early detection of liver cancer remains limited by the slow pace and invasiveness of current testing methods. This study proposes a single-walled carbon nanotube field-effect transistor (SWCNT-FET) designed to detect hexanal—a volatile organic compound (VOC) elevated in liver cancer—directly from exhaled breath. The device is modeled in QuantumATK using a semi-empirical Extended Hückel Hamiltonian within the non-equilibrium Green's function (NEGF) framework, emphasizing realistic contact physics by employing metallic SWCNT electrodes instead of conventional metal films. Zigzag channels with (11,0) and (12,0) chiralities are examined to analyze how geometry and contact matching influence charge transport. Simulations include current–voltage (I–V) characteristics and …

Development Of A Novel Cfd Approach For Predicting Multiphase Flow Enhanced By Machine Learning, Abdulrahman Elazazi Salem

Theses

Accurate estimation of interface orientation is crucial for ensuring both the accuracy and robustness of Volume of Fluid (VOF) schemes in multiphase flow simulations, especially when using non-uniform Cartesian meshes. Conventional gradient reconstruction approaches, such as least-squares (LSQ) methods, often suffer from significant errors and strong oscillations on highly stretched grids. This work proposes a grid-transferable, learning-based methodology that predicts interface unit normal vectors directly from the local volume-fraction field on nonuniform structured Cartesian grids using a feedforward neural network. The methodology extends earlier work originally developed for uniform grids, which is first reproduced to assess how performance deteriorates in …

An Integrated Tracking Technique For Underwater Navigation Using Acoustic And Imu Measurements, Mainul Islam Chowdhury, Quoc Viet Phung, Iftekhar Ahmed, Daryoush Habibi

Research outputs 2022 to 2026

Accurate navigation is essential for underwater vehicles like AUVs, which often operate in deep or remote areas. However, complex ocean dynamics, cumulative inertial-measurement unit (IMU) drift, and diverse noise sources often result in erratic and unreliable position estimates. To overcome these challenges, we proposed a method that combines underwater acoustic signals with onboard motion sensor data to improve the underwater position tracking system. The proposed system uses a long baseline (LBL) acoustic array of surface buoys to capture the Time-difference-of-Arrival (TDoA) of a multi-pulse beacon. We extract arrival times using a superimposed-envelope-spectrum (SES) detector, which exploits the beacon’s periodic structure …

Engineering Zinc Anodes Through Advanced Manufacturing Strategies For Next-Generation Zinc–Air Batteries, Yasir Arafat, Kareem Bakhsh, Muhammad Rizwan Azhar

Research outputs 2022 to 2026

Rechargeable zinc–air batteries (ZABs) are promising next-generation energy storage systems due to their high energy density, intrinsic safety, and low cost. Nevertheless, commercial deployment of Zn anodes is hampered by persistent challenges like dendrite formation, deformation, passivation, corrosion, and the hydrogen evolution reaction. This review systematically highlights the critical relationship between anode morphology and electrochemical performance and discusses recent advances in advanced manufacturing strategies for Zn anodes. Additive manufacturing approaches, such as 3D printing, enable the fabrication of porous and tunable Zn electrodes with enhanced surface area and uniform ion flux distribution. Furthermore, advanced materials processing techniques like alloying, coatings, …

Enhancing Co2 Adsorption And Co2/N2 Separation Performance By Incorporating Calcium In Mil-53 (Al), Hussein Rasool Abid, Hussein Znad, Nabil Majd Alawi, Farhan Lafta Rashid, Anmar Dulaimi, Amer Alanazi, Alireza Keshavarz, Stefan Iglauer, Shaobin Wang

Research outputs 2022 to 2026

Global warming is primarily driven by the rapid accumulation of carbon dioxide (CO₂) in the atmosphere. Metal–organic frameworks (MOFs) have emerged as promising materials for mitigating CO₂ emissions due to their tunable porosity, large surface area, and structural flexibility. Among them, MIL-53(Al) has attracted widespread interest owing to its excellent thermal and chemical stability. Recent studies show that modifying MOFs with secondary metals can significantly enhance their CO₂ adsorption performance. In this work, a one-pot synthesis method was employed to incorporate calcium (Ca), functioning as a Lewis basic metal, into the MIL-53(Al) framework to produce a series of bimetallic materials: …

Zwitterionic And Anionic Ultrafiltration Membrane Modification For Efficient, Fouling-Resistant Microalgae Harvesting, Victor Okorie Mkpuma, Mohadeseh Najafi, Javad Farahbakhsh, Masoumeh Zargar, Navid Reza Moheimani, Houda Ennaceri

Research outputs 2022 to 2026

Membrane surface modification is a promising strategy for fouling mitigation in membrane-based microalgae filtration, primarily by limiting the interactions between the membrane surface and the foulant particles. This study investigated the effectiveness of modified membranes in filtering Chlorella sp. MUR 269. First, three polyethersulfone membranes with varying pore sizes were evaluated to determine the influence of pore size on filtration performance and fouling behavior. The ultrafiltration membrane that exhibited the best performance was subsequently modified using two functional monomers: the zwitterionic [2-(methacryloyloxy)ethyl]dimethyl (3-sulfopropyl) ammonium hydroxide and the negatively charged mono-2-(methacryloyloxy)ethyl succinate (MMS). The filtration performance and fouling resistance of the …

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 …

Pegasus: Vfs 2025-2026 Dbvf, A'Zhae Turay, Elisabeth Canjar, Jack Carpenter, Cheng-Ju Wu, Xander Fruin, Sophia Bennett

Mechanical Engineering Senior Theses

Pegasus is an autonomous electric vertical takeoff and landing aircraft developed for the Vertical Flight Society Design-Build-Vertical Flight competition and designed around the operational needs of early-stage wildfire response. The system was developed to provide rapid aerial situational awareness, stable hover capability, modular payload deployment, and autonomous mission execution in environments where conventional reconnaissance methods may be limited by terrain, visibility, response time, or personnel risk. The final aircraft uses a hexacopter configuration with six electric propulsion units, a modular aluminum airframe, independent propulsion and avionics power systems, a Cube Orange+ flight controller, adaptive landing gear, and a bottom-mounted payload …

Plasmoid Vortex System Retrofit A Sustainability And Efficiency Study On Internal Combustion Engines, Walker Hall

Doctoral Dissertations and Master's Theses

The thesis addresses the persistent inefficiency and environmental degradation caused by internal combustion engines in modern vehicles, a major issue as the automotive industry faces increasing pressure to reduce fuel consumption and greenhouse gas emissions. Internal combustion engines, which power most cars today, convert only about 20-30% of fuel energy into useful work, with the remainder lost as heat and exhaust waste, including carbon monoxide (CO), carbon dioxide (CO₂), hydrocarbons (HC), and nitrogen oxides (NOx). This inefficiency contributes to global carbon emissions, with transportation accounting for approximately 29% of U.S. greenhouse gases in 2021 [1]. As regulatory standards tighten (e.g., …

Antecedents And Consequences Of Consumer Behavior In Circular Fashion: Cognitive, Normative, And Behavioral Pathways Shaping Purchase And Participation Intentions, Mahmudul Hasan Sabuj

Department of Textiles, Merchandising and Fashion Design: Dissertations, Theses, and Student Research

The increasing environmental impact of the fashion industry has intensified the need for a systemic transition from linear to circular production and consumption models. Despite growing interest in circular fashion, there remains a limited understanding of the underlying behavioral dimensions that drive consumer engagement in sustainable practices. Grounded in the Theory of Planned Behavior (TPB) and Norm Activation Theory (NAT), this study examines consumer behavior through an integrated framework capturing cognitive, social, and normative influences.

Using data collected from a structured online survey (N = 575), the study employs Exploratory Factor Analysis (EFA), reliability analysis, and multiple regression techniques to …

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 …

X-Ray Tomography Of Damage Dynamics In Advanced Materials Using A Laser Wakefield Accelerator, Vigneshvar Senthilkumaran, Nicholas F. Beier, Sylvain Fourmaux, Peter Kenesei, Sean Dobson, Joël Maltais, Alvaro R. Arce-Borkent, Tait Richards, Michael G. Lipsett, Le Zhou, John A. Moore, Amina E. Hussein

Mechanical Engineering Faculty Research and Publications

Additively manufactured (AM) metals offer the potential for customizable, cost-effective components, but qualification and certification are crucial. Key to this process is understanding pore dynamics under stress, typically analyzed using micro-computed tomography. This study introduces laboratory-scale “betatron” x-rays from laser wakefield acceleration as a high-throughput alternative for x-ray tomography of advanced materials, such as AM AlSi10Mg alloys. Coupled with 3D finite element modeling, this method provides detailed insights into stress-porosity interactions. The approach delivers high-resolution scans, revealing that pore shape and local triaxiality significantly influence fracture dynamics, supporting advanced material characterization. This work also demonstrates the potential and versatility of …

Natural Convection Of Cuo-Water Nanofluid Flow Along A Vertical Plate With Variable Thermophysical Properties And Discrete Heat Sources, Nepal Roy, Ioan Pop, Rama Subba Reddy Gorla

Faculty Publications

Effects of discrete heat sources along a vertical plate are of practical importance due their occurrence in electronic devices. For growing demand of electronic appliances and their advancement, cooling processes of them must be improved. As usual fluids have limited heat transfer, nanofluids made by dispersing nanoparticles into them are utilized to enhance thermal performance. However, flow characteristics and heat transfer of a nanofluid for discrete heat sources along a vertical plate need to be explored. For this reason, this study analyzes the natural convective heat transfer and flow behaviors of CuO-water nanofluid induced by discrete heat sources along a …

Unveiling Value In Plastic Waste: Synthesis Of 1,3-Dioxolan-4-Ones From Polylactic Acid And Polyoxymethylene To Enhance Plastic Biodegradation, Mi-Hyun Lee, Joohyun Park, Hyeongyeong Lee, Woo Yeon Cho, Semin Son, Pyung Cheon Lee, In-Hwan Lee, Hye-Young Jang

Mechanical Engineering Faculty Publications

Catalytic plastic upcycling protocols are essential for resolving the environmental and economic challenges associated with massive plastic production and disposal, as they convert complex waste streams into value-added chemicals. We report an efficient acid-catalyzed upcycling strategy for transforming poly(lactic acid) (PLA) and polyoxymethylene (POM) plastic waste. This innovative process directly yielding dioxolanones (DOXs) can be extended to use POM with various naturally abundant α-hydroxy acids. This work significantly expands the high-value chemical portfolio derivable from common plastic wastes. Incorporation of the synthesized DOXs into the poly(L-lactic acid) (PLLA) backbone results in materials with enhanced thermal stability and superior biodegradability. Critically, …

Cure Sound Project: Library Loudness, Jordan Cosgrove, Adrian Cruz, Lilliana Cantu, Izabella Grinnell, Idaly Oropeza, Maria Gamez, Regina Losoya, Kayla Martinez, April Martinez, Emiliano Rueda

Posters - 2026

The Louis J. Blume Library has three floors. Each floor has a different purpose and expected sound level. Ideal sound levels can vary based on task. Tasks requiring intense concentration may be negatively impacted by high sound levels1. However, for tasks requiring creativity, higher sound levels may be beneficial2-3. The purpose of this study is to examine noise levels on all floors of the library and determine which floor is most suitable for different tasks and studying types.

Evaluation Of An Affordable Prosthetic Liner In Resource Limited Settings, Samerial Brown

Posters - 2026

The lower limb prosthesis is an important assistive technology for persons with limb amputations and differences. The interface (prosthetic liner) between the rigid prosthetic socket and the residual limb is often made of silicone, urethane or thermoplastic elastomer gel. This material provides cushioning and support as well as suspension for the transtibial (below knee) prosthetic leg. Unfortunately the cost of liners range from $3-$600. This cost precludes its use in resource limited settings such as Sri Lanka. As a result patients are fit with a foam liner which has less cushioning and suspension capabilities than a gel type liner. This …

Agglomeration Of Particles Streaming Down A Zigzag, Juan Llamas

Posters - 2026

Zigzags or “letdown ladders” limit the flow speed of dry grains as they flow downward by gravity when loading silos, ships, barges, railcars, or trucks.

• Reduce cracking and shattering of grains.

• Increase grain shelf life.

• Increase grain resale value. • Increase ability of grain to germinate.

• Reduce generation of grain dust, an explosion and environmental hazard.

How can we design a zigzag that we know will not plug?

Aiw26s: Machine Learning Of Structured Data, Moumita Saha

Paul English Applied Artificial Intelligence (AI) Institute Publications

This workshop introduces the fundamentals of machine learning for structured data, focusing on tabular datasets and real-world applications. Participants explore key concepts such as data types, data preprocessing, feature engineering, and supervised learning methods. The session covers commonly used models, including linear regression, logistic regression, decision trees, and neural networks, along with evaluation metrics such as RMSE, accuracy, and confusion matrices. By the end of the workshop, participants will have gained a practical understanding of how to build, interpret, and evaluate machine learning models for structured data.

Effect Of Curing Duration On Bridge Deck Concrete Performance, Zhaniya Omarova

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

This study evaluates the influence of curing duration on the performance of bridge deck concrete and investigates the feasibility of reducing curing periods without compromising structural and durability properties. Two concrete mixtures, a standard Nebraska Department of Transportation (NDOT) bridge deck mix (47BD) and an optimized reduced-cement-content mix (O47BD-R100), were evaluated under multiple curing durations Fresh, early-age, mechanical, durability, and shrinkage properties were assessed to characterize the effect of curing on concrete behavior. Internal relative humidity and temperature were monitored using embedded sensors to investigate moisture diffusion and its role in shrinkage development for lab specimens and full-scale slabs.

Results …

Aisc/Asce 2026 Student Steel Bridge Competition, Gabriel Barrantes, Matthew Beltran, Vance Debrabander, Robert Miller, Wyatt Nipp

Civil, Environmental and Sustainable Engineering Senior Theses

This report documents the design, fabrication, and construction of a 1:10 scale steel truss bridge developed by Santa Clara University’s Steel Bridge Team for the 2026 ASCE/AISC Student Steel Bridge Competition. Marking SCU’s first participation in the competition since 2013, the project was completed over a six and a half (6.5) month period from October 2025 to April 2026, with financial support from McCarthy Building Companies, Inc. The bridge design is a modular truss structure spanning 23 feet six and one quarter inches (6.25) inches, constructed entirely of low carbon steel in compliance with SSBC rulebook requirements. Primary structural members …

How Do Social Network Models Compare To All-To-All Models For Forecasting Tuberculosis Epidemics? A Mathematical Modeling Study, Masabho Peter Milali, Hae-Young Kim, George Corliss, Anna Bershteyn

Electrical and Computer Engineering Faculty Research and Publications

Background. Mathematical models guide tuberculosis (TB) target-setting, yet most assume homogeneous “all-to-all” mixing. We compared projected intervention impacts between an all-to-all compartmental model and a Barabási–Albert (BA) scale‑free social network model under otherwise identical disease assumptions.

Methods. We calibrated transmission parameters so both models produced similar baseline trends, then introduced vaccination (coverage 30–70%; efficacy 80–95%) and treatment (20–50% increases in recovery) after a 400‑day burn‑in. Outcomes were assessed 300 days post‑intervention.

Results. Under 60% coverage, increasing vaccine efficacy from 80% to 95% yielded smaller projected reductions in active TB with the network model than with all‑to‑all mixing. Treatment improvements showed …

Exploring Hemodynamic Signatures Using Event Camera, Zaid Ahmed

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis investigates event-based sensing for hemodynamic measurements in transmission mode through the human finger. Conventional frame-based imagers are limited by exposure time, frame rate, and motion blur, which reduce sensitivity to fast optical transients. To address these bottlenecks, this thesis introduces a novel transmission-mode sensing framework using a Prophesee EVK4 HD neuromorphic sensor. By capturing asynchronous ON/OFF events generated by local intensity changes, this work presents a new approach to three tasks: intra-finger pulse transit time (PTT) and pulse wave velocity (PWV) estimation, event-based transmission mode laser speckle contrast imaging (LSCI), and Flicker Spike Arrival Time (FSAT) Delay Mapping, …