Digital Commons Network^™

Guiding State-Specific Studies On Highway Disasters: Examining Differences In Postdisaster Funding, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The highway sector is frequently and severely impacted by natural disasters. To mitigate these effects and reduce the need for large relief budgets or emergency funds, it is crucial to study the resilience of the transportation network. As such, defining resilience in absolute terms is not enough; instead, it is equally important to analyze specific case studies and build a lessons-learned rapport. This is critical because it helps identify unique vulnerabilities and strengths that might be overlooked in broader analyses. However, current research on highway resilience often lacks empirical evidence to support the selection of these unique and significant case …

Kentucky Traffic Collision Facts Calendar Year 2024 Report, Paul Ross, Eric Green, Christopher Blackden, Kenneth Agent, Christopher Van Dyke

Kentucky Transportation Center Research Report

No abstract provided.

2025 Safety Belt Usage Survey In Kentucky, Erin Lammers-Staats, Derek Young, Kenneth Agent

Kentucky Transportation Center Research Report

No abstract provided.

Irp Commercial Trailer Data Feasibility Study, Brian Howell, Jennifer Walton

Kentucky Transportation Center Research Report

This study evaluates the feasibility for developing and maintaining a comprehensive tractor truck trailer database. The commercial motor vehicle (CMV) community currently lacks a cross-jurisdictional, centralized repository for commercial trailers registered in United States and Canadian jurisdictions. Existing federal databases provide information on interstate commercial motor carriers, vehicles, and drivers but exclude trailers. Similarly, IRP and IFTA do not collect trailer-level data, and trailer data is displayed inconsistently across its customer base. Approximately one fifth of violations in Kentucky during inspections from 2020 to 2022 were attributed to trailers, including worn tires, inadequate brakes or improper registration. The rise of …

Efficient Inference Of Performance Models In Openmp Applications, Gaurav Punjabi

Computer Science and Engineering Master's Theses

Choosing the best OpenMP parameters such as thread count, scheduling type, and chunk size is essential for optimizing parallel program performance. One of the promising approaches is to infer a (pre-trained) performance model at runtime to determine the parameters to run OpenMP parallel regions. Such a performance prediction model can require programs’ code information such as intermediate representation (IR) and other at-runtime information (e.g., input sizes) to make a performance prediction. In such a scenario, extracting or querying the IR information at runtime can create a significant runtime overhead. This thesis proposes a compiler-asssited tuning framework that shifts IR extraction …

Text-Based Propaganda Detection, Vivek Sharma

Dissertations, Theses, and Capstone Projects

In the digital age, the swift consumption of news and the widespread dissemination of propaganda significantly threaten democratic principles and informed decision-making. News organizations, often aligned politically, tailor their content to appeal to specific audiences, thereby perpetuating biases. Despite advancements in detecting propaganda through various computational techniques, including Large Language Models(LLM) and BERT-based approaches, significant challenges persist concerning data availability and the effectiveness of detection tools. This thesis explores the landscape of text-based propaganda and reviews related research in textual analysis. It introduces a novel method for collecting a social-media based dataset, which includes analysis of journalists' tweets to discern …

Additively Constructed Plain Concrete Pipes: Structural Performance And Site Implementation, Alireza Hasani, Boshra Besharatian, Sattar Dorafshan

Civil Engineering Faculty Publications

Worldwide, extrusion-based additive construction of cementitious materials or 3D Concrete Printing (3DCP) has gained significant momentum for large-scale construction in recent years. This technology has advanced building construction across the world; however, it is rather underdeveloped in transportation infrastructure construction. This paper addresses major hurdles hindering the wider adoption of 3DCP for unreinforced/plain pipe culvert construction. More specifically, the authors investigated the load-bearing capacity of large-scale pipes under the three-edge bearing (TEB) test. Additionally, the effects of printing discontinuities or seam sections on the structural behavior of 3DCP pipes, and their site implementation considerations as culvert structures were studied in …

Physics-Based Machine Learning Framework For Predicting Structure-Property Relationships In Ded-Fabricated Low-Alloy Steels †, Atiqur Rahman, Md Hazrat Ali, Asad Waqar Malik, Muhammad Arif Mahmood, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The Directed Energy Deposition (DED) process has demonstrated high efficiency in manufacturing steel parts with complex geometries and superior capabilities. Understanding the complex interplays of alloy compositions, cooling rates, grain sizes, thermal histories, and mechanical properties remains a significant challenge during DED processing. Interpretable and data-driven modeling has proven effective in tackling this challenge, as machine learning (ML) algorithms continue to advance in capturing complex property structural relationships. However, accurately predicting the prime mechanical properties, including ultimate tensile strength (UTS), yield strength (YS), and hardness value (HV), remains a challenging task due to the complex and non-linear relationships among process …

Wind Turbine Rotor Design Using High-Fidelity Aerostructural Optimization, Marco Mangano, Sicheng He, Yingqian Liao, Denis-Gabriel Caprace, Andrew Ning, Joaquim R. R. A. Martins

Faculty Publications

Large wind turbines yield more energy but demand careful aeroelastic blade design. Coupled multiphysics design strategies can reduce wind energy costs exploiting fluid-structure interactions. This work presents the first high-fidelity aerostructural optimization study of a large wind turbine rotor.We use blade-resolved fluid dynamics and structural solvers in a monolithic gradient-based optimization framework to explore steady-state torque and blade mass trade-offs. The coupled-adjoint approach computes gradients efficiently, enabling the optimization of over 100 structural and geometric parameters simultaneously. Our optimization study modifies a DTU 10 MW benchmark with a simplified structure and isotropic material properties. The tightly coupled optimizations increase torque …

Data-Driven Shear Capacity Prediction Of Studs Embedded In Uhpc For Steel-Uhpc Composite Structures, Yanping Zhu, Woubishet Zewdu Taffese, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study employs ensemble learning algorithms to accurately predict the shear capacity of studs embedded in ultrahigh performance concrete (UHPC), a critical aspect of structural engineering. Using a comprehensive data set featuring six UHPC slab features, seven stud features, and one shear pocket feature, 35 ensemble models are developed across five cases and seven algorithms (bagging, random forest, AdaBoost, gradient boosting, XGBoost, CatBoost, and LightGBM). The Shapley additive explanations (SHAP) analysis is conducted on the top-performing models to gain insights into their decision-making mechanisms. Results indicate that transforming UHPC slab geometry parameters into a volume, alongside different diameter ratios, proves …

Temporal Evolution Of Workforce Fatality-Linked Factors In The Transportation Construction Sector, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Despite advancements in safety measures, fatalities in the transportation sector remain disproportionately higher than in other industries. Transportation sector fatalities arise from a combination of demographic, environmental, and occupational factors that amplify the overall risk. While strides have been made in understanding the factors contributing to fatalities, there remains a critical gap in research focused on their temporal evolution. The goal of this study is to investigate the temporal evolution of fatality-linked association factors in the transportation construction sector. The methodology encompassed three stages. Stage 1 was preprocessing the data: the US Census of Fatal Occupational Injuries, covering 3,792 fatality …

Labor Productivity Losses Across Construction Trades: A Machine Learning Approach, Tamima Elbashbishy, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Labor productivity is a major concern in the construction industry. Existing research on construction labor productivity (CLP) within specific trades has produced inconsistent findings due to differences in the factors analyzed. This lack of consistency makes it difficult to identify the most critical drivers of productivity losses across trades. To address this gap, this study adopts a cross-trade analytical approach to systematically identify and evaluate the inefficiencies impacting labor productivity in multiple construction trades. Specifically, the study (1) identified common organizational and project-level inefficiencies that influence labor performance; (2) conducted an expert-based survey to measure the frequency and perceived impact …

Failure Analysis Of Prestressed Concrete Girder Bridges Under Over-Height Truck Impacts, Mohamed T. Elshazli, Mohamed Elgawady, Tao Xing, Ahmed Ibrahim

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Accidental collisions between over-height trucks and bridge superstructures are a common threat to existing bridge infrastructure. These incidents often stem from illegal over-height vehicles or truck operators' unawareness of clearance limits, posing serious safety risks and causing substantial structural damage. This study presents a comprehensive numerical investigation of the dynamic response of prestressed concrete girder bridges subjected to over-height truck impacts. Large-scale finite element models were developed in LS-DYNA, with validation conducted against experimental results. The parametric study explored impact speeds ranging from 16 to 113 km/h (10 to 70 mph), impactor masses between 2 and 6 tons, impact locations, …

Switching Performance Optimization Of Sic Mosfets With Digital Active Gate Drivers, Liyang Du

Graduate Theses and Dissertations

Silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFETs) have extensive applications in high-power density devices, but they exhibit quick switching transients that are problematic, including electromagnetic interference (EMI), voltage overshoot, and current imbalance between paralleled devices. The purpose of this dissertation is to maximize the switching performance of SiC MOSFETs using digital active gate drivers (AGDs). A three-level gate driving approach is presented to improve current sharing in paralleled SiC MOSFETs through turn-on voltage and gate signal delay adjustment. Closed-loop control with real-time feedback ensures high-reliability operation. For better practicability, a compact AGD structure of a single-path Class-B amplifier-based topology is …

Analysis Of Traffic Crash Data In Kentucky 2020-2024, Paul Ross, Eric Green, Christopher Blackden, Christopher Van Dyke

Kentucky Transportation Center Research Report

No abstract provided.

Navigating Barriers: Examining Social Equality Through Transportation Disadvantages And Perceived Healthcare Accessibility In South Carolina, Yihong Ning, Songyuan Deng, Yuche Chen

Faculty Publications

Transportation inequities significantly contribute to health disparities, particularly in socially and geographically diverse regions like South Carolina. Prior research predominantly relied on objective measurements, like travel time or distance, to assess healthcare accessibility. However, limited attention has been given to the subjective perceptions of transportation barriers. To address this gap, we designed a comprehensive survey consisting of 61 questions (including 32 five-point Likert-scale items) capturing demographic, socioeconomic, and travel behavior data from a diverse sample of South Carolina residents. Urban and rural contexts were distinguished using county categorization and built environment measures. Exploratory Factor Analysis (EFA) was employed to identify …

Exopg Maturation And Owl Interface, Duncan Michael Louden

Electrical Engineering

The maturation of the ExOPG buoy generator consists of an interface to facilitate remote data acquisition of an existing battery charge controller. This module telemeters battery controller data including voltage, temperature, and state of battery charge. The data is transmitted to a communication system and is able to be viewed by humans on a 24/7 basis for continuous operation and human usage. The module works seamlessly as an addition to the existing ExOPG generator, and it does not interfere with any existing and planned components of the generator. The module is highly efficient and draws minimal power from the existing …

Experimental Study Of Gas-Dynamic Heating In Hartmann-Sprenger Tubes For Rocket Engine Ignition, Jacob T. Huff

Master's Theses

Ignition systems for chemical rocket engines typically rely on hypergolic propellants or auxiliary electrical hardware to supply the energy required to initiate combustion. The resonance igniter is a simple and robust alternative to these conventional methods, capable of inducing autoignition of non-hypergolic propellants without an external ignition source. At the core of this concept is the Hartmann-Sprenger Tube (HST), a device in which a high-velocity jet of gas impinges on a resonance cavity. This interaction establishes self-sustaining gas oscillations within the cavity that heat the propellants to their autoignition temperature. To facilitate the development of a functional resonance igniter at …

Lung Injury Risk Curves From Behind Armor Blunt Trauma Using A Live Swine Model, Narayan Yoganandan, Lewis Somberg, Danielle Wilson, Alok Shah, Jared Michael Koser, Brian D. Stemper, Valeta Carol Chancey, Joseph Mcentire

Biomedical Engineering Faculty Research and Publications

Introduction

From structural, anatomical, and functional perspectives, components of the thoracoabdominal region are heterogeneous and physiologically and functionally different. Although their tolerances to injury are expected to be different, the current Roma Plastilina No. 1 clay penetration criterion for behind armor blunt trauma (BABT) is not specific to the body region. It is important to develop regional injury criteria to ensure its specificity. The objective of the study is to conduct impact tests on the lung region using a live animal model and develop injury risk curves using velocity and deflection metrics via parametric survival analysis.

Materials and Methods

Live …

Case Article—Optimizing Transportation And Equity In A District Zoning Problem For Orville Public Schools, Kelly M. Sullivan, Ashlea Bennett Milburn

Industrial Engineering Faculty Publications and Presentations

“Optimizing transportation and equity in a district zoning problem for ORville public schools” is a case developed to expose students to an optimization decision problem with ethical considerations incorporated. Specifically, students are asked to solve a school district zoning problem in which all residential addresses in a school district must be assigned to middle schools having capacity limits on the numbers of students that they can accommodate.

Validation And Proposed Expansion Of The Data-Driven D Region Model, Kevin M. Watson

Theses and Dissertations

Predicting ionosphere effects on radio wave propagation is critical for communications and over-the-horizon radar systems. The D region is challenging to model for several reasons, one of which is chemical complexity. Ion density changes during sunrise/sunset introduce substantial uncertainty in electron density profiles (EDPs). The Data Driven D Region (D3R) model solves electron densities through an ion chemistry model and assimilates relevant space weather inputs. This study evaluates D3R against the Faraday International Reference Ionosphere (FIRI) and measurements using Very Low Frequency (VLF) propagation paths. Space weather event impacts on D3R EDPs are evaluated during the disturbed period from 8-12 …

Repair/Preservation Of Concrete Compression Members In Bridges Using Ultra-High-Performance Concrete (Uhpc), Mohammed Hedia, George Morcous

Nebraska Department of Transportation: Research Reports

As of 2024, approximately 36% of bridges across the United States require repair or replacement, with 7% classified as structurally deficient. The estimated cost to address these deficiencies exceeds $260 billion. In recent years, Ultra-High-Performance Concrete (UHPC) has emerged as a repair material for infrastructure preservation, drawing increased attention from transportation agencies and researchers worldwide. The Federal Highway Administration (FHWA) has notably advocated for UHPC’s adoption in bridge preservation initiatives, recognizing its exceptional mechanical properties and durability.

This report presents a comprehensive literature review on the application of UHPC as a repair and strengthening material for bridge compression members. While …

Adversaguard: A Distributed Data-Poisoning Benchmark For Parallel Ai, Yulia Kumar, Solomon Thomas, Dejaun Gayle, J. Jenny Li, Dov Kruger

Center for Cybersecurity

As organizations scale model training across large clusters and clouds, data poisoning has emerged as a significant practical threat. Most existing research focuses on data poisoning in single-node environments. Far fewer studies have compared the effectiveness of attacks across parallel training strategies, where factors like gradient aggregation and distributed memory ceilings fundamentally alter attack detectability and its impacts. To address this gap, we introduce AdversaGuard, a reproducible benchmark and accompanying application designed specifically for distributed settings to protect AI training pipelines. This research makes the following key contributions: (1) A comprehensive Distributed Data Poisoning (DDP) benchmark spanning seven distributed systems …

Enhancing Non-Player Character Dialogue In Video Gages: An Evaluation Of Large Language Model-Generated Responses, Lam P. Quach

Master's Theses

As video games increasingly emphasize narrative depth and player immersion, the quality of Non-Player Character (NPC) dialogue has become crucial for creating engaging gaming experiences. This thesis investigates the potential of Large Language Models (LLMs) to generate high-quality NPC dialogue by comprehensively evaluating four state-of-the-art models: Gemma 3 27B, Mistral 7B, QWEN 2.5, and LLAMA 3.1. The study employs a mixed-methods approach, combining human evaluation (N=50 participants) with AI-based assessment across five key benchmarks: coherence, personality expression, engagement, style/tone appropriateness, and overall quality. Participants evaluated 32 dialogue samples (8 per model) generated for a fantasy game context featuring two distinct …

Designing The Protocol For An Experimental Flight Simulation Study Encouraging Fuel Efficient Behavior, Thomas S. Reardon

Theses and Dissertations

This study designed and tested an experimental instrument to examine how pilots respond to fuel efficiency feedback in a flight simulator. A standardized flight plan, script, and hardware setup were created using X-Plane 12 software and physical flight simulator hardware. The chosen sortie guided participants from Monterey Regional Airport to Moffett Federal Airfield using instrument flight rules (IFR). The flight script provided step-by-step guidance to ensure consistent behavior across participants. The simulator was mapped to match real cockpit controls and allowed for precise data collection including flight time, altitude, heading, and fuel use. The goal was to support a larger …

Implementing Lean Principles To Enhance Warehouse Operations At King Abdulaziz Air Base(Kaab): A Case Study Of Royal Saudi Air Force (Rsaf), Saleh A. Alghamdi

Theses and Dissertations

The Royal Saudi Air Force (RSAF) relies on efficient logistics to sustain readiness. At King Abdulaziz Air Base, warehouse receiving inefficiencies caused delays and waste. This study used Lean principles and a six-month time–motion analysis, with Pareto and Fishbone tools, to identify 55% waste in dead pile and 75% in palletized shipments. Standard times of 5.98 and 6.55 minutes were set. Key recommendations include SOPs, cross-training, forklift certification, layout redesign, and RFID. Lean adoption could save 100+ labor hours and $4,000 annually, improving safety, accuracy, and mission readiness.

Sainik Vol 1 Issue 1, Sastra Deemed To Be University

SAINIK

No abstract provided.

Enhancing Network Security: Dynamical Intrusion Detection Systems Leveraging Zero Trust Architecture, Ekramul Haque

Tennessee State University Alumni Theses and Dissertations

This thesis discussed two original methodologies for proposing security frameworks incorporating machine learning (ML) and Zero Trust Architecture (ZTA) principles to manage advanced persistent threats faced by Unmanned Aerial Vehicles (UAVs) and Network intrusion detection systems (IDS). The first methodology examined the use of RF signals and deep learning to identify and classify UAVs. The RF signal characteristics used in the method for detecting UAVs improved the ability to determine RF drone protocols. Although the models led to promising findings, their lack of ability to generalize to new drone types identified the need to improve both the data set and …

Hybrid Forecasting Of University Electricity Demand Using Time Series And Deep Learning, Minsoo Baek, Youngguk Seo

Faculty Articles

University buildings are energy-intensive and operate on complex schedules, making electricity demand forecasting particularly challenging. This study develops and evaluates monthly forecasting models for a public university campus in Georgia using six years of data (January 2019–December 2024) that integrate weather variables and academic calendar indicators. Three modeling approaches are compared: Seasonal Autoregressive Integrated Moving Average (SARIMA), SARIMA with exogenous variables (SARIMAX), and a hybrid SARIMAX–Long Short-Term Memory (LSTM) model. Feature selection methods, correlation analysis, Granger causality, Random Forest importance, Recursive Feature Elimination (RFE), and Least Absolute Shrinkage and Selection Operator (LASSO) regression, were applied to optimize input relevance. The …

Low-Resource Ecoacoustic Audio Classification, Enis Berk Coban

Dissertations, Theses, and Capstone Projects

Ecoacoustic monitoring via machine learning enables scalable analysis but is often constrained by labeled data scarcity, particularly in remote regions like the Arctic. This thesis confronts low-resource ecoacoustic audio classification by developing and evaluating complementary machine learning methodologies. We introduce EDANSA, the first publicly available, expert- labeled Arctic dataset of its kind, curated via novel active learning, alongside a baseline CNN. We systematically evaluate transfer learning, showing general audio embeddings effectively bootstrap classifiers for challenging Arctic sounds, significantly outperforming direct label mapping. Optimizing label utility, we investigate standard data augmentation and introduce novel audio data valuation via Shapley values, revealing …