Engineering Commons^™

Electrical Grid Architectures For Smart Cities From Digitalized Power Systems To Ai-Enabled Urban Energy Ecosystems, Ehab Bayoumi

Mechanical Engineering

Smart cities increasingly depend on electrical grid infrastructures capable of operating under high levels of digitalization, decentralization, and intelligence while maintaining reliability, security, and governance at the city scale. However, conventional power systems, historically designed for centralized generation and passive operation, are poorly aligned with the operational complexity, multi-actor coordination, and cross-sector integration characteristic of urban energy systems. This review develops an architecture-first perspective on smart-city electrical grids, tracing their evolution from digitalized power networks to decentralized and AI-enabled urban energy ecosystems. Rather than focusing on individual technologies, the study evaluates grid architectures using a multi-layer framework that integrates physical …

Data-Driven Lpv Modeling Via Parametric Dmd And Predictive Control Of Highly Flexible Aircraft, Larry Catalasan, Tianyi He, Weihua Su

Mechanical and Aerospace Engineering Student Publications and Presentations

This paper presents a method of data-driven parametric dynamic mode decomposition (p-DMD) to derive a linear parameter-varying reduced-order model (LPV-ROM) and predictive control for the nonlinear aeroelasticity of highly flexible aircraft. It directly uses the data snapshots obtained at varying flight conditions and encodes a nonlinear model’s polynomial dependency on flight conditions to produce a polynomial-dependent LPV-ROM. The modeling method can handle not only equilibrium flight conditions but also continuously varying flight conditions. In numerical studies, the proposed data-driven p-DMD modeling is applied to a highly flexible cantilever wing perturbed around equilibrium conditions and a flexible aircraft with time-varying angles …

How Fe(Ii)/2-Oxoglutarate Oxygenase Chooses Chlorination Over Hydroxylation: Electric Field-Driven Ligand Exchange Governs C-Cl Formation, Simahudeen Bathir Jaber Sathik Rifayee, Midhun George Thomas, Anandhu Krishnan, Kritika Gupta, Carter Davis, Tatyana Karabencheva-Christova, Christo Z. Christov

Michigan Tech Publications

Non-heme Fe(II)/2-oxoglutarate (2OG)-dependent halogenases catalyze highly selective C-H halogenation. BesD is a non-heme Fe(II)/2OG halogenase that performs regio- and stereoselective chlorination of the l-lysine (l-Lys) substrate. Understanding the mechanism by which halogenation is favored over canonical hydroxylation is essential for guiding enzyme engineering efforts aimed at converting hydroxylases into halogenases. Here, we combine molecular dynamics (MD) and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations to elucidate the origin of chlorination selectivity in BesD and variants derived from a homologous hydroxylase. Our results indicate that, although the initial inline Cl-Fe(III)-OH intermediate is inherently predisposed toward hydroxylation, it undergoes a two-step isomerization in …

Field Monitoring And Geometric Representation Of A Uhpc-Repaired Bridge Structure, Robert Lawler

Honors Scholar Theses

Ultra-High Performance Concrete (UHPC) has shown promise in bridge rehabilitation broadly, but its application to steel gusset plate repair represents a novel use case with limited prior research. Therefore, when the Commodore Isaac Hull Bridge in Derby, Connecticut, was issued an emergency declaration due to gusset plate section loss, a UHPC repair was implemented. This project represented the first known field implementation of this type of UHPC gusset plate repair, marking a significant advancement in the rehabilitation of deteriorated steel bridge components. To support long-term performance assessment and ensure the success of the repair, field monitoring efforts were also incorporated …

Replication And Architectural Enhancement Of Omni Aggregation Networks, Matteo Calviello

Rose-Hulman Undergraduate Research Publications

Single Image Super-Resolution (SISR) reconstructs high-resolution images from low-resolution inputs, a capability valuable across many application domains. This thesis focuses on the replication and architectural enhancement of the Omni Aggregation Network (OAN), a lightweight super-resolution architecture designed to balance reconstruction quality with computational efficiency through a novel omni-axis self-attention mechanism.

Independent replication remains a persistent challenge in machine learning research, and this work addresses that issue directly. Initial replication attempts trailed the original reported results by approximately 6-10% in performance metrics before several undocumented implementation details were identified. After correcting these discrepancies, the replicated implementation achieved results within 4% of …

Polymer-Derived Silicon Oxycarbide (Sioc) And Silicon Carbonitride (Sicn) Ceramics For Advanced Electrochemical Energy Storage Applications, Saja Al Ajrash, Erick S. Vasquez-Guardado

Chemical and Materials Engineering Faculty Publications

Preceramic polymers, especially silicon oxycarbide (SiOC) and silicon carbonitride (SiCN) ceramics, have gained significant attention due to their wide range of applications in many fields, particularly in energy storage devices beyond conventional lithium-ion batteries (LIBs). This review focuses on the synthesis, structural characteristics, and properties of SiOC and SiCN ceramics as electrodes for battery applications. Furthermore, their promising applications as electrode materials for energy storage systems are explored, along with the most recent advances in the development of such materials and their use in lithium-ion batteries (LIBs), lithium-sulfur batteries (LSBs), potassium-ion batteries (PIBs), sodium-ion batteries (SIBs), and supercapacitors. This review …

Accelerating Wound Healing Rates With Cucurbita Pepo Leaf Extract Loaded Electrospun Poly(Methyl Methacrylate)/Halloysite/Chitosan/ Caco₃ Composite Nanofibers Through In Vitro And In Vivo Assessments, Samar A. Salim

Nanotechnology Research Centre

Cucurbita pepo leaf extract (CPE) was incorporated into electrospun poly(methyl methacrylate)/ halloysite/chitosan/ CaCO₃ (PMMA/Hal/CS/CaCO₃) composite nanofibers to develop a novel biomaterial for accelerating wound healing rates. The different nanofibrous scaffolds were successfully fabricated and characterized through scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). SEM analysis revealed uniform, smooth nanofibers, while FTIR and XRD confirmed the integration of CPE into nanofiber matrix, indicating an amorphous structure and effective dispersion of the extract. In vitro agar well-diffusion and antibiofilm assays revealed that the optimized formulation exhibited potent antimicrobial activity against wound-associated pathogens. The nanofibers composite based on …

Real-Time Fraud Detection, Haidi Aly Fahmy, Abdelhadi Nait-Zerrad, Shiva Krishana Reddy Ravuula, Sangwhan Cha

Harrisburg University Other Works

Financial fraud detection is a high-volume, high-velocity analytics problem. Traditional rule-based systems are often easy to deploy, but they are limited by static thresholds, delayed response, high false-positive rates, and weak explainability. This report presents a formalized end-to-end Big Data architecture for real-time fraud and anomaly detection in financial transaction streams.

The proposed architecture ingests transaction events through AWS Kinesis, enriches them through an Apache Flink stream-processing layer, scores them with an XGBoost classifier, explains model outputs using SHAP, and converts structured evidence into human-readable summaries through a controlled GPT explanation layer. Results are persisted through a hybrid storage strategy …

Characterizing Stiffness Dynamics Of Normal And Malignant Breast Spheroids Using Brillouin Microscopy, Razanne Rafat Zaghloul, Karlin Hilai, Chenjun Shi, Jitao Zhang

Medical Student Research Symposium

Background: Breast cancer progression and metastasis are closely linked to alterations in the mechanical properties of tumor cells and their microenvironment. Softer, more deformable cells are often associated with higher metastatic potential. While atomic force microscopy (AFM) is the current gold standard for mechanical characterization, it is limited to surface measurements and can damage 3D cultures. It remains unclear how the mechanical properties evolve over time in normal versus malignant spheroids. This study utilizes Brillouin light-scattering microscopy, a non-contact and label-free optical technique, to assess stiffness changes in normal and malignant breast epithelial spheroids over time. Understanding these mechanical signatures …

The Structural Limitations Of Mining Output Growth In Nevada, Mckinley Brown, Emma Kitchen

Undergraduate Economics Working Paper Series

This study compares short and long trends in Nevada to the production output within the mining industry. Nevada produces around 70% of the United States gold and about 15% of the world's critical minerals. From its position as one of the most resource rich mining regions globally to its emergence as a growing economic hub, mining played a central role in Nevada's economy. However, despite the industry’s importance, Nevada still faces inefficiencies in production output due to insufficient attention to key inputs such as labor, infrastructure, technology, and energy resources.

Data Driven Estimation Of Pore Size Using 1d Light Emissions For Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jorge Barron, Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

The quality assurance of the Laser Powder Bed Fusion Process (LPBF) has been extensively investigated over the last decade for in-situ monitoring of metal additive manufacturing. The process inherently generates voids within the bulk of the part, which can detrimentally affect the quality of the printed part. The characterization of these voids by estimating their size and identifying their geometrical features remains a challenge. This study introduces a Machine Learning (ML) based framework for estimating void sizes of varying geometries using layer-wise one-dimensional (1D) average light intensity signal obtained from the optical tomography system during the 3D printing of metallic …

Build Digital Annual Survey 2025 And Trends & Comparisons 2022 - 2025, Clare Eriksson, Robert Moore, Bilal Succar

Reports

The Build Digital Annual Survey 2025 provides an overview of digital transformation across Ireland’s construction and built environment sector, drawing on responses from 205 participants across industry, government, and academia. The findings show continued sector engagement with digital transformation, driven by government mandates, project benefits, and partner expectations. Common digital deliverables, such as model-based design, documentation, coordination, and clash detection, are now widely used, while more advanced uses linked to operations, sustainability, interoperability, and AI remain less mature. The report also highlights ongoing challenges, including skills gaps, uneven training provision, limited OpenBIM adoption, and inconsistent implementation of ISO 19650 and …

A Predictive-Correlational Study Investigating Flight Students' Perceptions Of The Use Of An Artificial Intelligence Instructor In The Simulated Flight Training Environment, Zachary L. Lamothe

Doctoral Dissertations and Projects

The purpose of this quantitative predictive-correlational study is to investigate how perceived ease of use, perceived usefulness, performance expectancy, and perceived enjoyment impact attitude towards use and the behavioral intention to use an artificial intelligence flight instructor in simulated flight training among aviation students earning an aeronautical degree at a collegiate flight training school in the Mid-Atlantic region. Aviation has benefited from different technological advances, and using artificial intelligence technology for flight training could be another improvement as it becomes increasingly sophisticated. The study adds to the literature by addressing the problem of limited information on the perception of artificial …

From Frames To Strains: Analytically Modeling Inelastic Deformation Under Mapped Single-Site Impacts From High-Speed Footage To Internal State Variable Codes, Joby Milo Anthony

Doctoral Dissertations and Projects

This work adds insight to the physical phenomena of microstructural and stress strengthening of metal components by the inelastic deformation from Surface Mechanical Attrition Treatment (SMAT). Impact behaviors observed by high-speed footage of a Crank-Slider Mechanism (CSM) are examined in the context of analytically moving rigid bodies in spacetime and resolving kinematics upon impact until restitution via Finite Element Analysis (FEA). A Coupled Discrete-Finite Element Model (CDFEM) leverages Bammann plasticity, Horstemeyer damage and void nucleation, growth, and coalescence and Cho recrystallization Internal State Variable (ISV) models to show the localization of plastic strain and onset of recrystallization under any single …

The Impact Of Dispatch Weight Restrictions On Derivative Aircraft Propulsion Technology Evaluation, Timothy T. Takahashi

Faculty Publications

This paper arises from an ARPA-E-sponsored project seeking design opportunities to retrofit existing aircraft with hybrid electric propulsion systems. Engineers typically configure aircraft to fly a given payload over a long range, which is subject to field performance constraints. In practice, operators fly transport aircraft (civilian and military) in a manner where dispatch consciously trades payload and/or range to enable safe operations to and from short runways. This work describes a simple yet novel analytical process suitable for inclusion in conceptual design or technology portfolio trade study evaluations to assess the impacts of weight-restricted dispatch upon usable payloads. We find …

An Open-Source Linear Actuated-Quartz Tube Furnace With Programmable Ceramic Heater Movement For Laboratory-Scale Studies Of Combustion And Emission, Casey Coffland, Ryan Bixler, Elliott T. Gall

Mechanical and Materials Engineering Faculty Publications and Presentations

The Linear Actuated Quartz Tube Furnace (LA-QTF) is an instrument engineered to heat and combust materials under controlled conditions, capable of achieving flaming and smoldering states. A ceramic ring furnace is linearly actuated parallel to the length of a quartz tube. The mode of combustion depends on temperature, fuel composition, and oxygen availability; the LA-QTF regulates combustion by controlling the temperature and position of the ring furnace, and airflow within the tube. The LA-QTF can maintain temperatures between 23 °C and 530 °C for extended time periods, with stable temperatures over long-duration (∼120 min) experiments. Flow rate is dependent on …

On The Application Of Machine Learning Techniques For Quality Assurance In An Automobile Paint Shop, Anis Fatima, Shakeel Ahmed, Muhammad Akif Shan

Michigan Tech Publications

The automotive industry depends on high-quality paint coatings for both aesthetic appeal and functional performance. However, surface imperfections such as scratches, paint runs, and orange peel can arise from process and environmental variations. This study employs machine learning (ML) and exploratory data analysis (EDA) to identify key factors that influence surface defect formation in automotive painting. Using historical production data from Lucky Motor Corporation Limited, models based on linear regression, support vector machines (SVM), and random forests were developed and validated under various process conditions. The best-performing model achieved an R² of 0.94, with a mean absolute error (MAE) of …

The Impact Of Optimization Approximation Algorithms On The Performance Of The Bht-Qaoa, Ali Al-Bayaty, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

This article investigates the performance impact of five classical optimization approximation algorithms on our previously introduced quantum search algorithm, termed the Boolean–Hamiltonians Transform for Quantum Approximate Optimization Algorithm (BHT-QAOA), to effectively search for all best-approximated solutions for Boolean-based problems. These optimization approximation algorithms are BFGS, L-BFGS-B, SLSQP, COBYLA, and COBYQA. Their performance impact is evaluated and compared using two proposed performance metrics—(i) the final number of function evaluations (the lower numbers denote the best optimization approximation algorithms) and (ii) the final quality of qubit measurements (the higher values indicate all best-approximated solutions were found for a problem). Arbitrary classical Boolean …

Advanced Finite Element Modeling And Design Enhancement Of Slender Square Concrete-Filled Double-Skin Steel Tubular Columns, Mahmoud T. Nawar, Ayman El-Zohairy, Mohamed Emara, Raghda I. Halima

Faculty Publications

Limited research exists on the behavior of square CFDST slender columns, especially under the consideration of the relation global buckling and confinement effect. This study evaluates square concrete-filled double-skin steel tubular (CFDST) columns using nonlinear finite element analysis (FEA) to simulate structural behavior under axial and eccentric loads until failure. Parametric analyses of extensive specimens of square CFDST pinended columns evaluate various parameters, providing design insights for engineering applications. The study was conducted over a wide range of slenderness ratios. Four concrete varieties with compressive strengths were tested: normal concrete (NC), engineered cementitious composites (ECCs), high-strength concrete (HSC), and ultra-high-strength …

Machine Learning Approaches For Predicting Biochemical Oxygen Demand And Ammonium Nitrogen: A Decade-Long Weekly Field Study At A Full-Scale Water Resource Recovery Facility, Hoda Khoshvaght, Ratish Ramyad Permala, Amir Razmjou, Mehdi Khiadani

Research outputs 2022 to 2026

Unlike previous studies that rely on high-frequency (15-min or hourly) datasets, this study is among the first to use low-frequency (weekly) data to evaluate the performance of linear and nonlinear machine learning (ML) algorithms for predicting biochemical oxygen demand (BOD) and ammonium nitrogen (NH4⁺-N) in the primary and secondary treatment effluents from the Subiaco Water Resource Recovery Facility (WRRF) in Western Australia. Various feature selection methods, including filters, wrappers, and embedded methods, were employed to identify the most effective approach that achieves the highest model performance while enhancing computational efficiency. The results demonstrate that a reduced set of …

Liquid-Phase Chemical Melting Deposition For Anchored Nanoparticle–Nanofiber Architectures, Hiep Pham, Kiernan O'Boyle, Gracie Boyer, Jonghyun Park

Mechanical and Aerospace Engineering Faculty Research & Creative Works

We report chemical melting deposition (CMD), a manufacturing strategy designed to overcome the low mass loading and weak interfacial bonding inherent to vapor-based synthesis. Unlike conventional vapor routes, CMD leverages a transient liquid-phase transfer (TLPT) mechanism driven by the differential thermal degradation of carrier fibers to transfer and anchor nanoparticles directly onto target fibers. This process thermodynamically drives the wetting and interfacial fusion of nanoparticles, establishing a liquid-phase contact pathway that enables markedly higher active material loading. To validate the structural resilience of this fused architecture against extreme volumetric stress, we utilized lead oxide (PbO) as a model system, which …

Vegetated Canopy Heterogeneity Footprints In The Roughness Sublayer, Giulia Salmaso, Raul Bayoan Cal, Marc Calaf

Mechanical and Materials Engineering Faculty Publications and Presentations

Turbulent flows over horizontally homogeneous rough surfaces are categorized as rough‐wall boundary layer flows, while flows over homogeneous vegetated canopies are better described through a mixing‐layer analogy. At present, numerous studies have investigated canopy density as a transition mechanism between rough‐wall and mixing‐layer‐type flows. Yet, most considered canopies have been spatially homogeneous, with few exceptions investigating agricultural arrangements. However, most vegetated canopies are not homogeneously distributed, but instead contain gaps and spatial heterogeneities of different scales. In these cases, it remains unclear which are the dominant flow traits, and how spatial heterogeneity affects them. To help overcome these knowledge gaps, …

Investigating Affordable Indoor Mobile Lidar Sensing For Bim-Based Facility Management: A Usability And Condition Sensitivity Study, Amr Mousa, Ahmed Elyamany, Mohamed Nabawy

Civil Engineering

This paper analyzes how capture parameters affect indoor mobile LiDAR scan fitness for-purpose for BIM-based facilities management. Despite extensive research on geometric accuracy and automated modelling performance, limited work has systematically examined how acquisition conditions influence the practical usability of raw scans for BIM/FM applications. A controlled experimental investigation used an Apple iPhone 16 Pro's integrated LiDAR sensor to capture 36 indoor scans under twelve factorial combinations of scan speed, illumination level, and motion pattern. Each condition was repeated three times. Usability was assessed using several components,Fco a gate-based pass/fail criterion, enclosure geometry, openings, ceiling services, and geometric clarity using …

Simulation Of Post-Tensioned Clt Rocking Wall And Platform Structure Response Under Earthquake Lateral Loads With Simplified Equivalent Model, Yunxiang Ma, Qingli Dai, Da Huang, Miaomiao Li, Xiang Zhao

Michigan Tech Publications

The post-tensioned cross-laminated timber (CLT) rocking wall is a recently developed resilient CLT lateral force-resisting system with a self-centering feature. The structural responses of the systems with different designs need to be determined and evaluated efficiently to promote the development and standardization of industrial applications. This study developed a computationally efficient, component-assembled numerical model for post-tensioned cross-laminated timber (PT CLT) rocking walls that captures decompression, post-tension self-centering, and energy dissipation within a framework. The single wall model was assembled using nonlinear zero-length springs for the compression at the CLT bottom, truss bar element for the PT tendon, and elastic shell …

A Novel Machine-Learning Based Method For Resolving Secondary Structure Topology In Medium-Resolution Cryo-Em Density Maps, Bahareh Behkamal, Mohammad Parsa Etemadheravi, Ali Mahmoodjanloo, Amin Mansoori, Mahmoud Naghibzadeh, Kamal Al Nasr, Mohammad Reza Saberi

Computer Science Faculty Research

Medium-resolution cryo-electron microscopy (cryo-EM) density maps preserve substantial information about protein secondary-structure organization; however, accurately recovering the topology and connectivity of α-helices and β-strands remains challenging due to noise, structural heterogeneity, and the intrinsic resolution limitations that obscure residue-level detail. Topology determination is a key intermediate step toward building atomic protein models from medium-resolution cryo-EM density maps. It requires identifying the correct correspondence and orientation between secondary-structure elements (SSEs), i.e., α-helices and β-strands, predicted from the amino-acid sequence and those detected in the three dimensional (3D) density map. Despite significant advances in cryo-EM reconstruction and molecular modelling, this correspondence problem …

2025, Significant Natural Disasters And Global Carbon Capture, Utilization, And Storage—Annual Progress Report, Shangli Shi, Yun Hang Hu

Michigan Tech Publications

This annual review summarizes the progress of carbon capture, utilization, and storage (CCUS) technologies in 2025. During this year, the growth rate of atmospheric CO2 concentrations slowed, yet anthropogenic CO2 emissions continued to rise. At the same time, the increasing frequency of severe natural disasters underscored the urgency of climate action and further intensified global efforts to advance CCUS deployment. Scientific interest in CCUS expanded markedly, with the annual number of related publications increasing by 18.5% compared with 2024, reaching 63935. Meanwhile, the total number of operational commercial CCUS facilities worldwide grew by 54%, accompanied by an approximate 25% increase …

A Review Of Magnesium-Based Stents: Manufacturing Strategies And Future Trends, Amir Motaharinia, Amir Sanati Nezhad, Jeremy Goldman, H. R. Bakhsheshi-Rad, J. Drelich

Michigan Tech Publications

Coronary artery disease is often treated with vascular stents to restore the blood flow. Recently, there has been growing interest in biodegradable metal stents, especially those made from magnesium (Mg). This review starts by explaining the complex pathophysiology of atherosclerosis and the current treatment options. It then discusses stents, including their potential benefits, capabilities, and limitations, as they represent the gold standard for percutaneous coronary intervention in treating atherosclerosis. Given the vital role of stents, we provide a thorough review of the manufacturing techniques involved, such as wire forming, subtractive manufacturing, and additive manufacturing, with a specific focus on stents …

Effects Of Niobium On The Mechanical And Oxidation Properties Of Additively Manufactured Tungsten, Alexander Lesieur, Cayla Eckley, Ryan A. Kemnitz

Faculty Publications

Although additive manufacturing presents a novel and customizable approach to fabricating tungsten (W) alloys, the layer-by-layer production technique presents a unique set of processing challenges which are further exacerbated by the metal’s refractory properties. In this study, additions of niobium (Nb) were found to improve the mechanical properties and oxidation resistance of additively manufactured W. Microstructural investigation revealed the effect of Nb on the cracking, grain size, and texture in the as-built material. Mechanical compression testing showed significant improvement in ductility with increasing Nb content. The low concentrations of Nb used did not induce large changes in the yield strength …

Valorization Of Ductile Cast Iron Solid Waste As A High-Performance Adsorbent For Crystal Violet Removal: Characterization, Optimization, And Mechanistic Insights, Ibrahim Ibrahim Mr., Abdel Mohsen Turky Dr., Nasser Mostafa Prof., Mai H. Roushdy

Chemical Engineering

Industrial textile wastewater containing synthetic dyes cause serious environmental and health risk, whereas ductile cast iron (DCI) foundries generate over 500 000 tons of waste annually. This study utilizes DCI solid waste as an adsorbent to remove the crystal violet (CV) dye from wastewater. Techniques (XRF, XRD, BET, SEM-EDX, FTIR, TGA-DTG, zeta potential) proved that the waste contains 88.0 wt% periclase (MgO) with nanoscale, high surface area, and abundant surface hydroxyl groups. Response surface methodology showed that the most significant parameters were the adsorbent dose and time contact. The optimal conditions give 93.7% removal efficiency at initial concentration: 38.7 mg …

Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca

Publications

As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …