Engineering Commons^™

Breach Modeling Flume Tests, R. M. Monteiro-Alves, R. Moran, M. Á. Toledo, M. Morris, C. Picault, J-R. Courivaud

5th International Seminar on Dam Protections Against Overtopping

From previous flume tests conducted in the framework of the OVERCOME Project, intended to investigate the effect of different soil materials, overflow discharges, and upstream face watertightness on the breaching processes of overflowed levee sections, we determined the need for further investigation on the effect of test repeatability, content of fines and armouring caused by the coarser particles. This document presents the results of this new set of tests which have shown an impact of these variables on the breach macro erosion processes, erosion rates and breach dimensions.

Development Of Low-Carbon Cementitious Composites With Volcanic Ash And Calcium Carbide Residue Using Carbonation Curing, Jad Samir Bawab

Thesis/ Dissertation Defenses

The production and use of cement and concrete is a major contributor to numerous environmental problems, primarily centered around high carbon emissions, extensive resource depletion, and vast waste generation. This thesis aims to develop and characterize low-carbon concrete by using volcanic ash (VA) and calcium carbide residue (CCR) as partial cement substitutes while exposing the cementitious composite to accelerated carbonation curing. The study is a multi-level assessment of the incorporated materials and curing method divided into four phases. The first stage studied and optimized the CCR content and carbonation curing parameters of carbonation-cured concrete. It was revealed that using 5% …

Physically Based Assessment Of Flow Resistance In Stepped Chutes, T. L. Wahl, B. J. Heiner, K. R. Smithgall, C. C. Shupe, J. Falkenstine

5th International Seminar on Dam Protections Against Overtopping

Existing physically based methods for estimating stepped chute friction factors or energy dissipation rates consider relative step height and relative step-tip spacing to be key factors, but do not fully account for chute slope and associated step orientation. For slopes steeper than 45° each step acts as an offset into the flow, while for flatter slopes each step presents an offset away from the flow, but methods that consider only the step-tip spacing do not account for this difference. Furthermore, most experimental studies have been performed in open channel spillway models, where two-phase air-water flow and variable flow depths make …

Ahead Of His Time? A Reanalysis Of The Air-Tunnel Stepped Chute Studies Of Marcos José Tozzi, T. L. Wahl, J. A. Higgs, J. Matos

5th International Seminar on Dam Protections Against Overtopping

Stepped spillways offer energy dissipation advantages and construction efficiencies over smooth spillway chutes. Energy dissipation is typically estimated using empirical relations that depend on chute slope, unit discharge and relative step height. Open-channel tests of model spillways experience self-aerated air-water flow downstream from the aeration inception point, and the presence of air dramatically affects energy dissipation and flow depth, making it difficult to separately determine the effects of step geometry and other basic flow properties. The 1992 doctoral dissertation of Marcos José Tozzi from the Polytechnic School of the University of São Paulo included open channel stepped spillway tests with …

Hydraulic Measurements In A Saf Stilling Basin With A Stepped Chute For Embankment Protection, B. M. Crookston, N. Young

5th International Seminar on Dam Protections Against Overtopping

Stepped chutes have become commonplace in embankment dam rehabilitation projects due to project economy, constructability, and improved chute energy dissipation. Consequently, for applications where a stilling basin is merited the interaction of stepped chutes and stilling basins is of high interest. A commonly used stilling basin type for many smaller embankment dams, the St. Anthony Falls stilling basin (SAF), has no specific hydraulic design guidance for use downstream of a stepped chute. Therefore, this study was conducted at the Utah Water Research Laboratory in a flume with 0.1 m tall steps, a total drop height of 1.8 m, and an …

Enhancing Patient Safety: Exploring Virtual Sitters' Role In Fall Prevention Through Remote Virtual Monitoring, Adama Diallo, Awatef Ergai Dr., Leeanna Spiva Dr., Meriel Mccollum Dr.

Symposium of Student Scholars

Remote Virtual Monitoring (RVM) technology enhances safety for both patients and care teams by reducing falls, improving the efficiency and effectiveness of continuous patient observation, and lowering costs associated with falls and staff support. The success of fall reduction efforts largely depends on the role of virtual sitters, individuals who remotely monitor high-risk patients to prevent falls. This study aims to explore the experiences of virtual sitters, identifying key themes, challenges, and opportunities to improve the intervention. Specifically, the research investigates how technology, work shifts, and institutional support impact the effectiveness and job satisfaction of virtual sitters.

Real Time Object Detection Using Yolo, Rohit Malik, Manisha Kumari, Sanghoon Lee

Symposium of Student Scholars

This project explores the implementation of real-time object detection using the You Only Look Once (YOLO) architecture. Leveraging its speed and accuracy, we developed a system capable of identifying and localizing multiple objects within live video streams. Our implementation focused on optimizing YOLO's performance for real-time applications, specifically addressing the trade-off between speed and accuracy.

We employed a pre-trained YOLO model and fine-tuned it on a custom dataset tailored to specific object classes. This fine-tuning process aimed to enhance the model's ability to recognize objects in our target environment. The system was implemented using Python and the OpenCV library, enabling …

Campus Navigator: A Mobile App For Seamless University Navigation, Hafsa Mohammed, Ali Rahimzadehfard, Rachab Wilson, Mathias Rossi, Turaj Ashuri, Amir Ali Amiri Moghadam

Symposium of Student Scholars

Navigation services play a big role in everyone’s daily lives, from directing them on new roads to guiding them through buildings. Outdoor navigation services have evolved from physical maps to digital ones like Google Maps for ease of use and accessibility. Upon conducting literature research, the team found that many navigation apps lack clear and accurate instructions for how to navigate university campuses such as Marietta campus. Due to the size of KSU’s Marietta campus and its buildings, effortless navigation has been a common challenge for students, faculty, and visitors alike. Additionally, all buildings are referred to by letters, numbers, …

Assessing A Solution For Ga Work Zone Safety Through Cross Classification, Asiah Lightfoot, Sunanda Dissanayake

Symposium of Student Scholars

Work zone safety is a health risk for drivers and construction workers. In Georgia, work zone crashes have decreased over the past 5 years, but the number of fatalities has still been over 1,000 each of those years. Studies have proven solutions such as lowering the speed limit or relying on current traffic control devices to be ineffective. The risks associated with these crashes must be recognized to improve upon previous solutions or innovate new ones from the results. The objective of this study is to utilize cross classification to identify factors that contribute to work zone crash deaths and …

Sandrapp: A Digital Intervention To Enhance Social Connectivity And Emotional Support Among Older Adults, Pavan Chowdary Chilukuri, Purna Chandu Anukula

Symposium of Student Scholars

Social isolation and loneliness are significant challenges affecting the well-being of older adults, often leading to adverse mental and physical health outcomes. Prolonged isolation has been linked to increased risks of depression, anxiety, cognitive decline, and chronic illnesses such as hypertension and cardiovascular diseases. As digital technology continues to evolve, innovative solutions have emerged to address these issues and foster meaningful social interactions for older adults.

SANDRApp is a user-friendly digital platform designed to reduce loneliness and enhance social connectivity among older adults. The platform caters to three primary user groups: (1) families with elderly loved ones living far away, …

Low Cost Additive Manufacturing Of Segmented Stator Composite Polymer Permanent Magnet Dc Motors, Ben Goldberg, Jordan Bailey, Connor Hawkins, Colin Haskins, Razvan Voicu

Symposium of Student Scholars

This study presents a novel approach to the design, manufacture, and optimization of segmented stators for composite construction axial flux permanent magnet DC motors. Traditional axial flux stator manufacturing is both challenging and expensive, creating a bottleneck in rapid prototyping and innovation. To overcome these limitations, the stator is divided into individually fabricated segments using advanced composite polymer materials and low-cost additive manufacturing techniques. This segmentation not only drastically reduces production complexity and cost but also allows for customized coil geometries that maximize the surface area for improved heat dissipation.

A key innovation of our design is the integration of …

2d Probabilistic Scour Model For Predicting The Time-Rate Of Scour For Spillways And Overtopping Dams Based On The Erodibility Index Method, M. F. George, G. W. Annandale

5th International Seminar on Dam Protections Against Overtopping

Time-dependent prediction of rock scour for dams and spillways has largely remained elusive given limited available data on rock erosion rate parameters in literature. Recently, a theoretical framework for determining the rate of rock scour was developed by Annandale (2025), enhancing the Erodibility Index Method (EIM). The EIM is the most commonly used and accepted approach for evaluation of scour in rock for dam applications. This theoretical framework has been incorporated into the 2D probabilistic jet impingement scour model (George & Annandale, 2023) so that scour progression due to head-cutting in a spillway channel (lined or unlined) or overtopping onto …

Deep Learning Algorithms For Traffic Flow Predictions, Adegoke Ojeniyi, Prince Pal Singh, Ankita Vashisht, Swati Kumari, Karan Karan

AUIQ Technical Engineering Science

Given the growing complexity of urban transportation systems, precise traffic flow forecasting is essential for reducing not only issues of congestion but also, for boosting road safety and enhancing mobility management. This study integrates Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), Long Short-Term Memory (LSTM), and Recurrent Neural Networks (RNN) to present a hybrid deep learning framework for traffic prediction. Of these, the CNN-LSTM model is a reliable option for real-time traffic forecasting since it successfully captures both spatial and temporal dependencies, resulting in superior predictive performance. The dataset used to assess the framework includes 48,120 records from a traffic monitoring …

Investigating The Impact Of Waterhead, Time And Temperature On Dam Displacement: Application Of Computer Aided Models, Maaz Abdullah

AUIQ Technical Engineering Science

Dam displacement is a crucial indicator for assessing the safety of a concrete dam through structural health monitoring. Since the displacement data exhibits a non-linear and complex relationship with influencing factors like waterhead, time and temperature, machine learning models are deployed to accurately predict dam displacement. Furthermore, the limited availability of monitored data in the majority of the dams renders the studies conducted with a large number of observations valueless. In order to address the aforementioned issues, this study proposes a feature selection approach to predict dam displacement by examining the ability of four ensemble machine learning models on different …

Comparative Assessment Of Land Surface Temperature In Urbanized Areas Of The Saudi Arabia, Rauf Khan, Syed Ilyas, Ziaul Haq Doost

AUIQ Technical Engineering Science

Land Surface Temperature (LST) has become a critical urban climate concern due to rapid urbanization and land cover transformation in Saudi Arabian cities. This study aimed to analyze the spatial and temporal variability of LST in three climatically distinct cities encompassing Riyadh (hot desert), Dhahran (hot humid), and Abha (cold desert) over the summer months (May to September) from 2017 to 2021. LST was retrieved through the RSLab Landsat LST web application. A total of 80 samples per year were compiled for each city using a structured sampling approach, and results were aggregated using the RS-LST Aggregation Framework (RSLAF). The …

Optimizing Hydrological Pan Evaporation Prediction Using Advanced Machine Learning Techniques With Spectral Clustering, Labib Sharrar

AUIQ Technical Engineering Science

Accurate prediction of pan evaporation remains a significant challenge due to inconsistencies across different climatic regions. This study aims to enhance pan evaporation estimation by developing a robust hybrid machine learning (ML) model that integrates spectral clustering with advanced regression techniques, specifically the Histogram-based Gradient Boosting Regressor (HGBR) and Extreme Gradient Boosting Regressor (XGBR), to improve prediction accuracy and adaptability across diverse environments. The research developed a novel methodology by employing spectral clustering for models' performance enhancement, followed by rigorous hyperparameter tuning, sensitivity analysis to assess the impact of individual features on each model. Finally, models underwent lack of fit …

Classification Of Daily Weather Conditions Using Decision Tree-Based Machine Learning Models: A Case Study Of Kabul, Afghanistan, Ahmad Bilal Ahmadullah, Ahmad Shah Irshad, Basir Ahmad Khaled

AUIQ Technical Engineering Science

As global climate variability intensifies, the need for accurate and reliable weather forecasting becomes increasingly important. This study aimed to classify daily weather conditions in Kabul, Afghanistan, by comparing two decision-tree-based machine learning (ML) models that includes Decision Tree Classifier (DTC) and Extra Trees Classifier (ETC). A complete year dataset consisting of 366 daily meteorological observations collected from a central weather station in the region for 2024 was used. Results revealed that the DTC model consistently outperformed the ETC model, obtained an overall accuracy of 99% in both the training and testing phases, compared to the ETC model's accuracy of …

Distal Weight-Bearing Implants Design Featuring An Integrated Groove Or Thread, Muntadher Saleh Mahdi, Dunya Abdulsahib Hamdi

AUIQ Technical Engineering Science

The distal weight-bearing implant was selected from a pool of approximately 17 implant systems that utilize the osseointegration mechanism currently available globally. It stands out due to its modernity, rarity, and creative concept, offering amputees with ``above-knee amputation'' a range of options that ensure their satisfaction and fulfill their requirements. However, this implant requires additional refinement and adaptation to achieve the highest level of perfection. This research implemented various modifications to the mechanical design of the implant, which were subsequently evaluated using the finite element analysis software ``ANSYS.'' Modifications included substituting the threads along the femoral stem with a groove …

Surface Urban Heat Island Effects Analysis In The Most Populated City In Thailand: Towards Sustainable Urban Development, Abdul Maulud Khairul Nizam, Muhammad Noor, Zafar Iqbal

AUIQ Technical Engineering Science

The fast and unprecedented urban growth process may violate cities' responsibilities by causing an urban heat island (UHI) and increasing the public's risk of heat-related illnesses due to vegetative area reduction and urban area inclination. The Bangkok Metropolitan Area (BMA)'s variations in Land Use Land Cover (LULC), Land Surface Temperature (LST), UHI, and several geospatial indicators, as well as the daytime and nighttime LST, are the main subjects of the study. Between 2015 and 2021, the highest Daytime LST (DLST) rose consistently from 36.77°C to 38.14°C, then slightly decreased to 37.22°C in 2023. There is a general increase in the …

A Comprehensive Review Of Advancements In Materials And Manufacturing For 3d Knee Implants, Huda Ali Hashim, Ghaidaa A. Khalid

AUIQ Technical Engineering Science

Over the past three decades, knee implant design has significantly advanced to address the challenges of replacing damaged knee joint bone with durable and efficient prosthetics. The aim of this review explore key developments in materials and manufacturing processes, focusing on biocompatible options such as zirconium, titanium alloys, UHMWP, and smart materials, as well as coatings designed for metal-sensitive patients. The study examines the mechanical forces acting on implants during daily activities, highlighting wear and infection risks, and evaluates the role of innovative manufacturing techniques in improving implant precision, cost-efficiency, and durability. Simulation methods, including Finite Element Analysis (FEA), are …

Investigating The Differential Effects Of Smote Variants On Class Imbalance And Exploring Their Applicability To A Thalassemia Prediction Model, Hussam Mezher Merdas, Ayad Hameed Mousa

AUIQ Technical Engineering Science

Researchers work around the clock on many datasets provided by various institutions. These researchers strive to come up with highly efficient Artificial Intelligence models. Often, researchers face the problem of imbalance in the distribution of classes in a particular feature in the selected dataset, which creates an Artificial Intelligence model biased towards one class at the expense of another class that is no less important than the first. On the other hand, thalassemia is a disease that affects people of different ages. The degree of disease varies according to the thalassemia class. This study proposes an improved Machine Learning model …

Wide Band Single-Mode Optical Fiber Design For Decreasing Bending Loss, Zahraa M. Kassem Alasady, Ahmed Al-Amiery

AUIQ Technical Engineering Science

Radiation loss due to fiber curving or bending is a major challenge in advanced technical applications like fiber-optic sensing or biomedical applications. This study focuses on the basic features that characterize a single-mode fiber (SMF) and its critical parameters in view of the recent improvements made. The planned design of SMF is, however, intended to resolve these problems by proposing minimizing bend loss by adopting a five-layer fiber structure designed to keep the optical field within the fiber core. The proposed SMF design exhibit ultra-low bending sensitivity, with estimated bending loss of 2×10-3 dB/turn for bending radius of 5 mm. …

Nuclear Energy: The Key To Sustainable Power For Ai And Emerging Technologies, Joshua Luke Ponsell, James Zurawski, Eli Musgrave, Johnny Demont, Eduardo B. Farfan

Symposium of Student Scholars

Skeptics question whether Artificial Intelligence (AI) can be powered sustainably. Nuclear may just be the best option. AI is transforming various spaces, from cybersecurity to accessibility, by enhancing the detection and prevention of fraud and phishing attacks to improving real-time services like subtitle generation, and supporting language translation. AI's impact also extends to applications like handwriting and speech recognition, streamlining processes and increasing accessibility for individuals with disabilities. As AI becomes more integrated into everyday life, the increasing demand for its computational power raises concerns about energy consumption. By researching datacenter power demands empirically and comparing nuclear options as opposed …

Preparing Students For The Quantum Era: Qml Training And Applications, Triveni Kandimalla, Valentina Nino

Symposium of Student Scholars

Quantum Machine Learning (QML) emerges as a transformative approach to addressing the growing complexities of modern data processing and computational challenges. Classical machine learning (CML) techniques, while powerful, face limitations in handling vast amounts of high-dimensional data and solving complex optimization problems efficiently. Despite its potential, QML remains underrepresented in academia, highlighting the need for accessible, hands-on learning experiences and knowledgeable faculty. This project seeks to advance QML education by incorporating it into diverse curricula, creating practical learning materials, and fostering workforce readiness. Using Google Colab, an open source labware has been designed to provide interactive learning modules (M0 to …

Human-Ai Teaming For Academic Performance Analysis, Kendarius Ward, Elise Hernandez, Tom Antony, Md Abdullah Al Hafiz Khan, Kazi Aminul Islam, Abm Adnan Azmee

Symposium of Student Scholars

Educators today often work with students who are struggling academically, but limited time and resources make it difficult to uncover the root causes and provide timely assistance. Artificial intelligence (AI) is a growing, viable tool for analyzing large datasets and solving problems in different domains; however, human expertise is required to enhance the AI model’s performance. This study will utilize human-AI teaming to assess student performance based on factors such as their academic involvement, hours spent studying, and grade-point-average, among others. These findings will help instructors better grasp each student's academic needs. By incorporating humans into the AI pipeline, we …

Building Resilience: Strategies For Sustainable Wildfire Management In California, Jaiden Rennie, Pegah Zamani

Symposium of Student Scholars

Wildfires in California are becoming more intense and destructive, threatening communities, ecosystems, and livelihoods. This project explores how resilience and sustainability can work together to reduce wildfire risks and long-term damage. By reviewing research, case studies, and expert insights, it examines what’s driving these fires, climate change, poor land management, and human activity, and looks at solutions that can make a real difference. From community education programs to AI-driven fire detection and smarter policies, the findings highlight practical ways to better prepare for and manage wildfires. The goal is to contribute to a future where communities and the environment are …

Using Rf Hardware Technologies To Counteract Interference Within Dsrc Caused By Adjacent Unlicensed Bands, Grayson Hatcher, Billy Kihei, Nathan Kirkwood, Marco Tello

Symposium of Student Scholars

In recent years, competition within Radio Frequency (RF) communication bands has led to an overlap between the U-NII-4 band used by low-cost consumer devices, and the Dedicated Short Communication Band (DSRC) used by the Georgia Department of Transportation. Past research con- firmed that this interference leads to drastic reduction in Packet Reception Rate (PRR) for Roadside Units (RSUs) and On- Board Units (OBUs) throughout the country, resulting in a reduction of stability between different components of the Intelligent Transportation System (ITS). Our research team set a goal to prove that a low-cost and simple modification can be made to RSUs …

Bridging The Gap: Care Team’S Perspectives On Technology And Ai Integration In Healthcare, Sarah Fernandes, Pranathi Boyina, Awatef Ergai Dr., Wellstar Health System, Mohammad Yousef Mousa Naser, Sylvia Bhattacharya Dr.

Symposium of Student Scholars

As healthcare systems increasingly integrate digital solutions, understanding the perspectives of frontline healthcare workers on technology adoption is critical. This study explores how Registered Nurses (RNs), Licensed Practical Nurses (LPNs), and Certified Nursing Assistants (CNAs), collectively referred to as the Care Team, interact with existing and emerging healthcare technologies, including artificial intelligence (AI). Given the growing reliance on digital tools for clinical and administrative tasks, this research examines the challenges and benefits perceived by healthcare professionals when incorporating AI-driven solutions into their workflows.

A cross-sectional research design was employed, involving 30 semi-structured interviews with Care Team members from an Intensive …

Sustainable Smart Farming Device With Leafit Adaptive Growth Technology, Saville Atkins, Anthony Iwejuo, Julian Pitts, Luis Mercado, Rachnicha Rojjhanarittikorn, Sandip Das, Hai Ho

Symposium of Student Scholars

For farmers, gardeners, and horticulture enthusiasts worldwide, one immutable reality is that maintaining a consistent physical presence to care for plants is not always feasible. In addition, different plants have unique needs for watering, nutrients, and environmental conditions to thrive. Failing to meet these specific needs can result in poor plant health, reduced yields, and inefficient resource usage. In this research project, we have designed and developed ‘LeaFit’ – a cutting-edge Internet of Things (IoT) device that offers a sophisticated and sustainable smart farming and gardening solution. Equipped with intelligent soil moisture, ambient temperature, humidity, and light sensors, LeaFit autonomously …

Towards Human Modeling For Human-Robot Collaboration And Digital Twins In Industrial Environments: Research Status, Prospects, And Challenges, Guoyi Xia, Zied Gharairi, Thorsten Wuest, Karl Hribernik, Aaron Heuermann, Furui Liu, Hui Liu, Klaus-Dieter Thoben

Faculty Publications

Human-Robot Collaboration (HRC) and Digital Twins (DT) have significantly advanced industrial development and digital transformation. Human representations and models are essential in Industry 5.0, where human-centric is one of the key features. Despite the growing interest in human models for HRC and DT, a comprehensive overview of these models and enabling technologies currently needs to be provided. This paper aims to present the research status, prospects, applications, and challenges of human modeling for HRC and DT in industrial environments. This paper adopts a Systematic Literature Review (SLR) approach. Moreover, a framework is proposed to systematize human modeling aspects, the technologies …