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An Investigation Of A Mach 15 Flow Over A Blunt Wedge Using First-Principles Potential Energy Surfaces: Influence Of Wall Temperature, Paolo Valentini, Zach Davis, Maninder S. Grover, Nicholas J. Bisek

Space Dynamics Laboratory Publications

The simulation of a Mach 15 air flow over a blunt wedge is conducted using the direct molecular simulation (DMS) method. Due to partial dissociation of the air mixture at the imposed free stream conditions, the shock layer contains N₂, O₂, NO, N, and O. All potential energy surfaces (PESs) used to model the various molecular interactions only describe electronic ground states energetics. Thus, no electronic excitation is modeled. An isothermal wall boundary condition is imposed, with full momentum and energy accommodation. Two wall temperatures are considered in this work, namely 1,000 K and 2,000 K. …

Hypersonic Non-Equilibrium Cfd And Dsmc Model Comparisons With The Varda Reentry Capsule, Jack D. Crespo, Paolo Valentini, Ashwin P. Rao, Zach S. Davis

Space Dynamics Laboratory Publications

Nonequilibrium aerothermodynamic modeling of the Varda hypersonic testbed capsule is conducted with direct simulation Monte Carlo (DSMC) and computational fluid dynamics (CFD) solvers. Flowfield properties at the 78 km reentry trajectory point are extracted to compute line of sight spectral radiance using two radiative emission codes, namely HARA and NEQAIR. Computed spectra are compared to spectral radiance measured by an in situ optical emission spectroscopy payload flown on Varda’s W-2 capsule in 2025. Model comparisons to the experimental data reveal discrepancies between the HARA and NEQAIR radiative emission predictions in both overall magnitude and qualitative behavior. NEQAIR was found to …

A Contextual Attention-Based Transformer Model For Enhanced Hate Speech Detection On Twitter, Mira Mansour, Nancy Akoum, Seifedine Kadry

Iraqi Journal for Computer Science and Mathematics

Hate speech on social media poses significant societal challenges, necessitating accurate and context-sensitive automated detection. Traditional machine learning (ML) models typically rely on lexical or superficial features, limiting their ability to capture nuanced or contextually ambiguous expressions of hate speech. Recent transformer-based methods (e.g., RoBERTa) provide improved contextual understanding but often lack explicit mechanisms guiding the model’s attention to critical semantic tokens, thereby reducing interpretability and sensitivity to nuanced linguistic contexts. This paper introduces a novel contextual attention-guided transformer model that explicitly incorporates lexicon-guided attention supervision into RoBERTa fine-tuning, significantly enhancing semantic precision in hate speech detection on Twitter. Evaluations …

Finite Element Analysis Of Tire–Pavement Interaction Effects On Noise Reduction In Porous Asphalt Pavements, Miao Yu, Geyun Lv, Anqi Li, Jing Yang, Zhexi Zhang, Dongzhao Jin, Rong Zhang, Jiqing Li

Michigan Tech Publications

This study investigated the noise reduction performance of porous asphalt concrete (PAC) pavement under tire–pavement coupling conditions, addressing the limitations of field measurements and laboratory testing. First, tire excitation amplitude parameters were determined based on vibrational contact operational scenarios. Then, finite element simulations were conducted to systematically analyzing the tire–pavement coupling noise characteristics of PAC pavement. The results indicate that PAC pavement effectively reduces the air pumping noise due to its highly porous internal structure, leading to significant noise attenuation. Furthermore, the study examined the key factors influencing the tire–pavement coupling noise in PAC pavement. When maintaining constant vehicle parameters …

Multivariate Stochastic Mine Scheduling Targeting Stationary Grades Considering Risk Uncertainty And Hierarchical Variables, Augusto A. T. Toledo, Joao F. C. L. Costa, Diego M. Marques, Luciano N. Capponi

Journal of Sustainable Mining

In short-term mine planning for deposits characterized by multiple variables, sequential diglines are generated with an emphasis on maintaining consistent grade distributions across mining periods. This research integrates an array of mineral variables, including deleterious elements, to facilitate the establishment of excavation geometries that enable precise grade and volume control within operational production zones. Through the systematic application of geostatistical analysis coupled with process optimization, geological risks associated with grade uncertainties are minimized, and an optimized operational sequence for the extraction of mineral blocks is pursued. The main point of this approach is maintaining grade distributions aligned with the historical …

An Innovative Implicit Modeling Technique To 3d Deposit Modeling: A Case Study Of The Chromite Mine, Ali Can Ozdemir Ozdemir, Yavuz Tore

Journal of Sustainable Mining

The location of an orebody known to show regional variability in space is determined only through 3D geological modeling. A reliable 3D orebody model must be obtained to ensure resource efficiency and sustainability in the mining industry. In addition, 3D geological modeling has become indispensable in intelligent mining, smart mining, and mining 4.0. In previous years, explicit methods were widely used for 3D geological modeling. However, the validity of geological models produced with these methods has been debated. It has been understood that they are inadequate in modeling vein-type mineralizations with complex geometry in particular. For this reason, implicit modeling …

Integrated Optimization Of Underground Mine Ventilation Using Hardy Cross, Monte Carlo Simulations, And Machine Learning Techniques: A Step Toward Sustainable Mining, Hussein A. Saleem

Journal of Sustainable Mining

Underground mine ventilation is crucial for ensuring worker safety, air quality, and operational efficiency. Effective optimization of ventilation systems reduces energy consumption, enhances airflow distribution, and minimizes risks associated with harmful gases and fire hazards. This study proposed an integrated framework combining the Hardy Cross (HC) method, Monte Carlo (MC) simulations, and machine learning (ML) techniques to optimize the ventilation system at the Jabal Sayid mine in Saudi Arabia. The HC method was employed to provide deterministic baseline airflow calculations, while the MC simulations accounted for uncertainties in resistance values and environmental conditions, generating probabilistic distributions of key parameters. Among …

Study On Visualization Simulation And System Dynamic Optimization Of The Ore Drawing Process In Mine Chutes, Liang Juan, Zhu Quanjie, Hao Yingnan, Quan Zhongxue, Zhang Zhiwu, Liu Xiaohuic, Ouyang Zhihua

Journal of Sustainable Mining

The ore release process in metal mine chutes is a critical part of the mining operation. Based on the urgent demand for intelligent mining construction, this paper proposes a visualization simulation and dynamic optimization method for the mine chute ore release process using the open-source programs Python and Blender. The main research content includes: designing the simulation method and model for the ore release process, including the main control program, process subprograms, etc.; proposing a visualization simulation method for the mine chute ore release process based on Blender, studying the impact of ore shape and size on ore release efficiency, …

Intrinsically Safe Pneumatic Seismic Source For Controlled Rock Mass ,Monitoring And Imaging In Underground Mining, Przemysław Sierodzki, Leszek Remiorz, Mateusz Ćwiękała, Krzysztof Krawiec

Journal of Sustainable Mining

This article explores the technical principles of pneumatic seismic sources, focusing on their application in underground mining operations, including environments prone to fire hazards. It introduces an intrinsically safe pneumatic seismic source as a cost-effective solution for quasi-continuous seismic excitation, useful for detecting stress concentrations in mining settings. These stress concentrations are identified through anomalies in seismic wave velocity, which may indicate potentially hazardous deformations in the rock mass. The developed system enables fully remote operation from the surface and integrates with a seismic monitoring system to capture high-resolution waveforms. The study provides an overview of the pneumatic system’s technical …

Ai In Society: A Regulatory Framework For Responsible Integration, Ziad Doughan, Sari Itani, Hadi Al Mubasher

BAU Journal - Science and Technology

This review paper studies the influence of Artificial Intelligence (AI) and Machine Learning (ML) on society in various categories in detail. AI and ML have developed rapidly in the past two decades, thus changing our lifestyles. These developments have various positive and negative impacts on society. This paper explores the many societal impacts of AI and ML, in economics, social aspects, ethics, and policy, shedding light on the opportunities and challenges that arise. An interdisciplinary insight is capable of understanding the challenges society faces when it uses AI and ML, locking opportunities that lie ahead and identifying promising paths towards …

Electronic Structure With Rovibrational Calculation For The Molecule Ali, Including The Spin-Orbit Coupling Effect, Hana Abdelnabi, Ghassan Younes, Dunia Houlla, Mahmoud Korek

BAU Journal - Science and Technology

The adiabatic potential energy curves for the lowest singlet and triplet electronic states in the representations 2S+1Λ+/- and Ω(+/-) (with and without spin-orbit coupling) of the molecule AlI have been computed by using the complete active space self-consistent field (CASSCF) with multireference configuration interaction (MRCI+Q) method. The spectroscopic constants ωe, Re, Be, and Te have been calculated. Using the canonical quantum mechanics approach, the rovibrational constants Ev, Bv, Dv, Rmin, and Rmax were calculated for the low-lying electronic states with and without spin-orbit coupling. A comparison between our calculated values and those available in the literature reveals excellent agreement.

Data-Driven Prediction Of Concrete Bridge Deck Corrosion Using Ground Penetrating Radar (Gpr), Nafisa Shafiullah

Civil Engineering Theses

Corrosion detection remains a crucial factor in the proper maintenance of Reinforced Concrete (RC) structures. While several studies have used Ground Penetrating Radar (GPR) for corrosion detection, quantitative models for prediction are still limited. This study presents an approach for the quantitative prediction of rebar corrosion in concrete using GPR data obtained from a prior experimental program involving accelerated corrosion. A total of 36 RC samples were cast, varying in cover depth, rebar diameter, and concrete porosity. The samples were subjected to an impressed current of 0.65 A in a 5% NaCl solution over three phases: 10, 20, and 30 …

Study Of Clustering Technique And Communication Topologies For Cooperative Control-Based Volt-Var Optimization, Gaurav Yadav, Yuan Liao, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

Introducing renewable distributed generation (DG) in the power distribution system causes rapid voltage fluctuations due to its intermittency. This intermittency renders conventional voltage regulation devices such as on-load tap changers (OLTCs) and capacitor banks (CBs) inefficient to regulate rapid voltage changes and leads to reduced equipment lifetime and high operation and maintenance costs. Hence, this calls for non-conventional methods to mitigate such voltage fluctuations. This paper presents a cooperative control-based method aimed to optimally control the reactive power of DG inverters to mitigate the voltage deviations by establishing communication among the DG nodes, and between DG and non-DG nodes. This …

Elli’S Liquid Flow In A Wavy Channel With Slip Effect, Wall Properties, And Heat Transfer, P. Devaki, Yatin Sood

Mansoura Engineering Journal

The dual behavior of Elli’s fluid motivated us to work on it. The fluid behaves as both Newtonian/ non-Newtonian based on the low and high shear rates, respectively. The paper focused on the flow of Ellis fluid in a peristaltic channel with wall properties and heat transfer. The channel is symmetric in nature, and slip conditions are considered near the elastic walls. The governing equations of the flow are solved analytically using suitable boundary conditions, which yield velocity and temperature functions. The novelty of the paper is to analyze the nature of Newtonian/non-Newtonian fluids under the same conditions so that …

Teleoperated Robotic Arm With Vision-Based Imitation Learning, Favour E. Emmanuel, Hunter J. Donahue

Williams Honors College, Honors Research Projects

This report presents the design, development, and deployment of a teleoperated robotic arm system capable of vision-based imitation learning. The system uses a leader-follower architecture with myArm C650 and myArm M750 robots manufactured by Elephant Robotics. The leader arm movement is controlled by the operator, whereas the follower performs actions acquired from demonstrations. Data collection included synchronized joint-angle recording and multi- camera video streams capturing human demonstrations.

These demonstrations were processed with a deep learning imitation algorithm called Action Chunking with Transformers (ACT). The main capability of this algorithm is its ability to make future action predictions based solely on …

Areosense, Josephine Turney

Williams Honors College, Honors Research Projects

The AeroSense growing system is designed to make indoor aeroponic gardening easy and accessible for everyone. By combining sensors, automation, and AI, the system can monitor and adjust humidity, lighting, and nutrient levels to help plants thrive without requiring expert knowledge. The goal is to create a self-regulating garden that takes the guesswork out of growing fresh herbs and vegetables at home. The project involves building a working aeroponic prototype equipped with misters, pumps, and environmental sensors, all managed by a Raspberry Pi. Using computer vision and machine learning, AeroSense will be able to assess plant health and respond automatically …

Parking Information And Supervision System, Joshua A. Thum, Alex J. Kinch, Jacob A. Dye

Williams Honors College, Honors Research Projects

In densely populated areas, finding parking can be an arduous and time-consuming struggle, especially in large and tall parking decks. Drivers would benefit from a convenient way to find an open parking spot without having to scour the entire lot first. The goal of this project is to sense available parking spots in a parking garage or parking lot using physical object detection and visual detection with computer vision verification, and display the open spots to drivers entering the lot. This information will be displayed locally at the lot and in an app, with the latter allowing someone to see …

High-Speed Non-Pneumatic Tire (Npt) Design For Speeds Above 60 Mph, Jacob Grams, Brady Maurer, Jake Groewa

Williams Honors College, Honors Research Projects

This project focuses on developing a high-speed non-pneumatic tire (NPT) capable of safely operating at speeds greater than 60 mph, a performance range where most existing airless tire designs fail due to structural instability and performance limitations. The objective of this work is to design, analyze, and prototype a structurally optimized honeycomb-based tire structure with improved load distribution, deformation control, and durability. Multiple geometries were evaluated using finite element analysis (FEA) to assess stress and maximum resultant (total) displacement behavior under loading conditions, and a material selection study was performed to identify a suitable material for the design. The final …

Robotic Air Hockey Table, William Forcey, Andrew Piunno, Kaden Carpenter, Xander Zavatchen

Williams Honors College, Honors Research Projects

Air hockey, a popular arcade game, is traditionally designed for two players. This limits the game’s accessibility for individuals who wish to practice or enjoy it as a single player. To solve this problem, a robotic system was implemented to play air hockey against a human player. The speed and acceleration of the puck and mallet were measured from a game played between humans to inform the required movement capabilities of the robot. The robotic opponent implemented observes the location of the puck on the table using a camera and predicts where it will be in the future. A Cartesian …

Nissan Leaf Disassembly Tool And Test Stand Design, Mariah Z. Hodge

Williams Honors College, Honors Research Projects

The Akron Engineering Tribology Laboratory has developed a water-based lubricant and aims to test and observe if the water-based lubricant could work in an electric vehicle environment. As parameters for creating a test stand to mimic an electric motor environment are not readily available online, the goal of this senior design project is to take apart a used Nissan Leaf engine to define the parameters a test stand must meet to accurately recreate an electric motor environment. Knowing these parameters, a test stand will then be designed for testing the water-based lubricants. The purpose of building a test stand to …

Solar Charging Chair, Joseph Austrian , ‘26, Jude Hemmins , ‘26, Neghemi Micah , ‘26

Senior Theses, Projects, and Awards

For our E90 project, we constructed an outdoor Adirondack-style chair with a built-in battery and solar panel, so users can charge their devices while sitting outside. Through data collection and analysis, we were able to verify that our solar energy system, consisting of a 30W panel, 96Whr battery, MPPT charge controller, and DC-AC inverter, performs better than theoretically expected. The chair was built using pressure-treated lumber with the electrical components in a weatherproof box and solar panel attached to the back rest. The total cost was $667.15.

Yk-4-250, A Synthetic Telmisartan-Tempol Conjugate: Crystal Structure Of A Stabilized Free Radical Containing An Angiotensin At₁ Receptor Inhibitor, Simon Friedrich, Yali Kong, Faik N. Musayev, Milton L. Brown, B. Frank Gupton

Department of Biomedical and Translational Sciences Faculty Publications

We report the first crystal structure of the telmisartan-tempol conjugate 2,2,6,6-tetramethyl-1-(λ'-oxidaneyl)piperidin-4-yl 4'-[(1,7'-dimethyl-2'-propyl-1H,3'H-[2,5'-bibenzo[d]imidazol]-3'-yl)methyl]-[1,1'-biphenyl]-2-carboxylate free radical (YK-4-250, C₄₂H₄₆N₅O₃), a dual-function inhibitor designed to target both the angiotensin II type 1 receptor (AT₁R) and reactive oxygen species (ROS). Structural analysis reveals a unique crystal architecture in which the nitroxide radical is stabilized within a sterically protected environment while preserving the telmisartan pharmacophore essential for high-affinity receptor antagonism. YK-4-250 is a novel small-molecule conjugate of telmisartan and tempol that incorporates a catalytic stabilized nitroxide radical and was rationally designed to mitigate gastrointestinal acute radiation syndrome (GI-ARS).

Deep Learning-Based Co-Current Upward Gas-Liquid Two-Phase Flow Regime Identification In An Annular Conduit, Joshua Robert Macomber

Graduate Theses, Dissertations, and Problem Reports (ETD)

Flow regime identification in co-current upward gas-liquid flow through annular conduits remains a significant challenge in petroleum engineering, with major safety and operational implications. It is also important across industries involving the transport of multiphase fluids. Misidentifying flow regimes can introduce major operational risk, yet regime boundaries in annular gas-liquid flow are often visually complex and context dependent.

The objective of this study was to evaluate the utility of convolutional neural network (CNN) classifiers for flow regime identification. The CNN was trained using annular flow image dataset published by Texas A&M University. The dataset consists of approximately 947 RGB images …

Unified Bayesian And Machine Learning-Based State Of Charge Estimation In A Pv Battery System, Showrov Rahman

Open Access Dissertations

The state of charge (SOC) of a battery indicates the remaining charge in the battery relative to its nominal maximum charge capacity. The accurate estimation of SOC is of utmost importance for efficient energy management as it indicates the level of energy stored in the battery.

Bayesian and machine learning (ML) approaches represent two distinct estimation strategies for battery state estimation. Bayesian filters, such as the Kalman filter (KF) and particle filter (PF), operate sequentially by incorporating physical models of battery dynamics. In contrast, ML-based methods are data-driven, and their performance largely depends on the quantity and quality of training …

Comparative Evaluation Of Deep Learning Models: Resnet18, Minivgg, And Yolov8 For Five-Class Blood Cell Classification, Keita Sakurai

Master's Theses or Doctor of Nursing Practice

Accurate classification of blood cell types is a critical task in automated hematological analysis. This study presents a comparative evaluation of three deep learning architectures, ResNet18, MiniVGG, and YOLOv8, for five-class blood cell image classification. To ensure a fair comparison, all models were trained under standardized conditions, including a consistent 90:10 training–validation split, controlled dataset size, and fixed training epochs. ResNet18 was trained to establish a baseline using residual learning. MiniVGG employed a compact VGG-inspired design with regularization to balance efficiency and accuracy, while YOLOv8 leveraged a lightweight, pretrained classification backbone with integrated data augmentation. Experimental results demonstrate a clear …

Eletric Charging Arm Mechanism - E-Charm, Jacob A. Lewis, Gabriel A. Greer

Williams Honors College, Honors Research Projects

As demand for electric and hybrid vehicles continues to rise, many EV owners rely on home charging in their garages. Gabriel Greer and I’s Senior Design Project, the Electric Charging Arm Mechanism (ECHARM), addresses this by creating a robotic system that autonomously detects a vehicle’s charging port, connects to it, and returns to a rest position when charging is complete. ECHARM is designed as a six-axis robotic arm with wrist and shoulder joints driven by stepper motors through custom cycloidal drive gearboxes. A closed-loop control system using rotary potentiometers ensures precise motion control. At the end of the arm is …

A Deep Neural Approach To Network-Based Obfuscated Malware, Meera Parmar, Sunil Gautam

ASEAN Journal on Science and Technology for Development

The rising prevalence of obfuscated malware poses a critical threat to network security, undermining traditional detection methods and jeopardizing data integrity and system reliability in an increasingly connected world. This growing danger highlights the urgent need for advanced solutions to protect against evolving cyber risks. This research intro-duces a novel framework to enhance malware detection, employing a hybrid architecture that integrates spatial and temporal analysis with attention mechanisms. The approach leverages a large dataset subsample, focusing on key feature selection and augmentation to improve robustness against evasion techniques. This innovative framework offers a significant advancement in identifying malicious network traffic, …

When Words Flow Like Water: How The Enbridge Line 3 Pipeline Environmental Impact Statement Failed To Prevent Hydrogeologic Harm In Minnesota, Carly Gutzmann

Journal of Earth and Life Science

For the aquifers of Minnesota, the environmental impact statement (EIS) was a promise of protection that never left the page. An environmental impact statement is meant to be an aid in the decision making process in order to ensure that projects consider potential environmental harms that may occur. However, they are often used instead as another regulatory box to check, rather than as active considerations when planning. As such, a project plan can be flawed from the start—if project developers only consider environmental impacts after they have already put considerable time, effort, and funding into their project as-is, they may …

Numerical And Machine Learning Based Recreation Of Damage Morphologies Of Barely Visible Impact Damage, Oscar A. Valdez

Mechanical and Aerospace Engineering Dissertations

Composite laminates are highly sought after in the aerospace industry as they provide strength without dramatically increasing the weight of manufactured structures. However, composite laminates are susceptible to barely visible impact damage caused by routine activities. This type of damage can easily go unnoticed while significantly reducing the load-carrying capability of the laminate. Current non-destructive evaluation techniques, such as ultrasonic scanning, can reveal the damage footprint but provide no insight into delamination through-the-thickness due to the shadowing effect. Micro-computed tomography offers ply-by-ply damage resolution but is unsuitable for field inspections and is constrained by specimen size. This study aims to …

Ai Data Center Dynamic Load Effects On Current Transformer Saturation, Sergio A. Hernandez

Electrical Engineering Theses

AI data centers can produce rapid changes in electrical demand that may influence current transformer performance during faults. This study evaluates the effect of an AI data center transient on CT saturation during single line-to-ground faults using a 400 V, 60 Hz grid connected inverter model in MATLAB/Simulink. The normal condition transient produced a maximum RMS current rate of approximately 211 A/ms, which was used along with the maximum power condition to define fault inception cases. A MATLAB time-domain CT model then swept the fault current DC offset coefficient to determine the minimum offset required for CT saturation. The calculated …