Civil Engineering Commons^™

The Impact Of Surveying, Nicholas A. Cosper

Williams Honors College, Honors Research Projects

My project consists of three parts. The first part will be helping the public. To do this I will be helping the Boy Scouts earn their surveying merit badge. This badge is known to be one of the hardest for scouts to obtain. In the next part of my project, I will be running a 3-wire level on the Davey Tree Seed Campus. This project will be extremely useful to them (the rest of this information is confidential). In the final part of my project, I will be conducting a topographical survey for the Cuyahoga Valley National Park for a …

Impact Of Natural Disasters On Construction And Engineering Solutions, Karima Ao Damson

Williams Honors College, Honors Research Projects

This Honors Research Project seeks to research and explain the impact of natural disasters on the construction and reconstruction of infrastructure in countries with the highest risk of natural disasters and compare them to the requirements in the United States in the states most prone to natural disasters. The objectives are to identify the countries most prone to natural disasters, describe the environmental impacts of the natural disasters, describe the impacts on construction and reconstruction requirements, and research whether construction and civil engineering solutions currently applied to the individual countries could be improved or reproduced in other countries exposed to …

Pile Setup Effects On Driven Piles In Southeastern Coastal States, Peya Sharif

College of Graduate Studies: Theses & Dissertations

The resistance of driven piles typically increases with time after installation, a phenomenon known as pile setup. This behavior is primarily associated with the dissipation of excess porewater pressure and the progressive reconsolidation of soil surrounding the pile shaft, particularly it is observed in cohesive soils. Although several empirical and analytical models have been proposed to estimate pile setup, their practical implementation in foundation design remains limited due to uncertainties associated with soil conditions, pile geometry, resistance variability, and time dependent behavior. To address some of these uncertainties, this study collected 221 pile load test data at the End of …

A Real-Time Autonomous Mobile Robotic System For Crack Detection And 3d Laser Profiling In Construction Using Two-Stage Deep Learning, Emmanuella Ogun

College of Graduate Studies: Theses & Dissertations

This thesis presents an autonomous mobile robotic system that integrates real-time visual crack detection with laser-based three-dimensional profiling for building inspection. The system coordinates SLAM-based navigation, deep learning perception, and manipulator-guided measurement within a unified ROS 2 framework, enabling scan-on-demand workflows where laser profiling occurs selectively at visually detected defect locations. The detection pipeline employs a two-stage architecture combining U-Net semantic segmentation with Pix2Pix residual refinement, achieving 73.9% mean intersection-over-union and 76.4% F1-score on the CrackSeg9k benchmark while maintaining 16 frames-per-second real-time throughput. Real-world validation demonstrated 95% detection success on 80 campus images under challenging conditions. The profiling subsystem utilizes …

Sustainable Nutrient Management Opportunities For Small Communities In The U.S. With Lagoon Wastewater Treatment Systems, Denis Sigei Ruto

Graduate Theses, Dissertations, and Problem Reports (ETD)

Lagoon wastewater treatment systems are among the most widely used secondary treatment technologies serving small and rural communities in the United States due to their low capital and operating costs, minimal energy requirements, and operational simplicity. While effective for removal of organic matter and suspended solids, most lagoon systems were not designed to achieve advanced nutrient removal. As regulatory priorities increasingly emphasize control of total nitrogen and total phosphorus to protect receiving waters and public health, lagoon-dependent communities face growing compliance challenges. These challenges are exacerbated by aging infrastructure, limited technical capacity, financial constraints, and insufficient infrastructure data, highlighting the …

Effects Of Metals On Persulfate Activation For The Decomposition Of Pfas, Malu Deav Devadasan

Civil Engineering Dissertations

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants widely used in industrial and consumer products due to their unique physicochemical properties. Their resistance to degradation, potential for bioaccumulation, and associated adverse health effects have prompted increasing regulatory attention, including the establishment of drinking water standards for six PFAS compounds by the U.S. Environmental Protection Agency in 2024.

Current PFAS treatment technologies are often energy-intensive and costly or generate secondary waste streams requiring further management. Meanwhile, this research investigated transition metal-catalyzed advanced oxidation processes for PFAS decomposition in water under ambient conditions. Previous studies demonstrated effective degradation of perfluorocarboxylic acids …

Anaerobic Digestion Of Food Waste Components: Modeling Biogas Production, Opeyemi E. Adelegan

Civil Engineering Dissertations

Food waste constitutes the single largest component of municipal solid waste landfilled in the United States — approximately 22% of 292.4 million tons generated in 2018 — and its anaerobic decomposition releases methane, a greenhouse gas with global warming potential approximately 27–30 times that of carbon dioxide over a 100-year horizon (IPCC, 2021). Anaerobic digestion (AD) offers an alternative management pathway that recovers energy and produces nutrient-rich digestate, but AD performance varies by as much as five-fold across food waste streams (130–630 m³ CH₄ per Mg VS added), and existing predictive tools either treat food waste as a …

Feasibility Study Of Concurrent Removal Of Organics And Ammonium Using An Iron Dosed Upflow Anaerobic Sludge-Blanket Bioreactor, Morgan Elizabeth Amos

Graduate Theses, Dissertations, and Problem Reports (ETD)

Aerobic microbial reactions have commonly been utilized in treatment processes to oxidize and remove organics and nitrogen through aeration, using processes such as nitrification that converts ammonium (NH₄⁺) into nitrite (NO₂^-) and nitrate (NO₃^-). Anoxic microbial reactions like denitrification often require organic compounds as an external source to chemically reduce the oxidized nitrogen (NO₃^- and NO₂^-) to nitrogen gas (N₂) for nitrogen removal from the liquid phase. These mainstream processes have a high chemical cost and energy footprint which results in an increased release …

Enhancing Traffic State Estimation At Bottlenecks Through Improved Demand Modeling: A Greenshields-Grounded Approach, Yuyan Annie Pan, Xianbiao Hu, Qing Tang, Yanyan Chen, Xuesong (Simon) Zhou

Civil & Environmental Engineering Faculty Publications

Accurate estimation of traffic state under oversaturated conditions is fundamental to a wide range of transportation applications. While intuitive, volume-to-capacity (q/qc) ratio-based link performance functions (LPF) are challenged by the U-shaped pattern of real-world speed-flow plots, which contradict the monotonic assumptions of link performance models such as the Bureau of Public Roads (BPR) function, particularly when q/q_c ≥ 1. This study addresses this critical gap by proposing an enhanced demand estimation method grounded in the Greenshields model, incorporating a real-time inflow correction factor to more accurately capture traffic demand at bottlenecks. In parallel, a modified LPF is introduced, replacing …

Integrated Corridor Management Framework For Severe Freeway Incidents, Sanjida Afroz Iqra

Graduate Studies Theses and Dissertations 2026

Traffic incidents are a major source of non-recurrent congestion on urban freeways, generating substantial mobility, safety, and economic impacts. Severe incidents that block multiple or all travel lanes are particularly disruptive because they degrade freeway operations and propagate congestion onto surrounding arterials. Effective Integrated Corridor Management (ICM) requires the ability to identify severe incidents, estimate their network-wide impacts, and anticipate the traffic conditions and driver behaviors that contribute to instability. This dissertation develops a data-driven ICM framework to address these challenges using real-world incident, crash, detector, and connected vehicle data from major Central Florida corridors, including I-4 and SR-417. The …

Generating Boundary Conditions For Compound Flood Modeling In A Probabilistic Framework, Pravin Maduwantha Mahanthe Gamage

Graduate Studies Theses and Dissertations 2026

Flooding in coastal riverine environments is often driven by the combined influence of multiple hydrometeorological flood drivers, including storm surge, rainfall, waves, and river discharge, which is referred to as compound flooding. A robust flood hazard assessment requires simulation of a wide range of flood driver conditions through dynamic compound flood models to capture the variability in resultant flooding. However, such assessments remain limited by the short length of observational records and the high computational cost of physics-based methods used to generate temporally varying boundary conditions. This dissertation develops a statistical framework to characterize compound flood drivers and generate large …

Discrete Element Modeling Of Granular Soils: Critical State Behavior Applied To Impact Pile Driving, Esteban Patino Marin

Graduate Studies Theses and Dissertations 2026

This thesis investigates the use of the Discrete Element Method (DEM) to study two complementary aspects of granular soil mechanics: critical state behavior of granular materials and dynamic response of driven piles in sand, both of which are governed by the same particle-scale mechanisms of dilation, contraction, and fabric evolution.

The first examines the critical state behavior and fabric anisotropy of granular soils through DEM simulations of direct shear, direct simple shear, and true triaxial tests. Sphere-cluster particles representative of a uniform sand are used in two assemblages of approximately twenty-five thousand and one hundred twenty-five thousand spheres to evaluate …

Prediction Of Maximum Local Scour Depth Due To Horizontal Jets Of Flushing Gate Using Artificial Neural Network, Adhy Kurniawan, Muhammad Sulaiman, Agus Maryono, Bambang Agus Kironoto, Amalia Ula Hazhiyah

Makara Journal of Technology

Local scour is a serious concern for hydraulic engineers. To maintain the reservoir capacity, flushing accumulated sediment is necessary, resulting in a turbulent and scouring jet from the flushing gate. Predicting the maximum scour depth from these water jets is crucial for civil engineers. Despite many proposed equations, one have shown consistent applicability due to the complex nature of the process. Ensuring accurate prediction between hydraulic parameters and the geometry of the scour hole in prototype experiments remains a key issue. To address this issue, this paper examines the use of artificial neural network (ANN) analysis as a computing device …

Compression Forming Of Basic Oxygen Furnace Slag-Gypsum Blocks: Performance Enhancement And Environmental Assessment, Fengyi Zhang

Student Works (2020-2029)

The construction industry plays a crucial role in global development but faces significant environmental challenges, particularly CO2 emissions from cement production. Gypsum blocks provide a sustainable alternative to traditional cement concrete blocks. However, the low mechanical strength and water resistance of gypsum materials limit the widespread adoption of gypsum-based materials in the construction industry. This study initially produced gypsum-based blocks using compression forming, adding supplementary cementitious materials (SCMs), and subjecting accelerated carbonation curing (ACC). It was found that compression forming addressed the shortcomings of traditional block manufacturing (high energy consumption and long production time), and the addition of SCMs generated …

Flood Prediction With Sentinel-1 Synthetic Aperture Radar From Hurricane Helene, Jingyu Xiao, Jessica Li

The Journal of Purdue Undergraduate Research

Floods are the most common natural disaster globally, causing thousands of deaths every year. Timely and accurate flood forecasts are crucial for developing early warning systems, evacuation plans, and effective strategies to enhance community resilience. Soil moisture is an important parameter in flood forecasting. Unfortunately, existing soil moisture sensor networks and optical remote sensing–based techniques for soil moisture estimation lack the spatial resolution needed for accurate flood forecasting. This study presents an approach for flood prediction using Sentinel-1 C-band synthetic aperture radar (SAR) data. SAR offers high spatial resolution and operates day and night under all weather conditions, making it …

An Integrated Multivariate Econometric Modeling Framework For Risky Driving Behavior Related Crashes: Evaluating Crash Risk And Severity Across Zones, Pabitra Kumar Roy

Dissertations and Theses

Rapid advancements in crash modeling have yet to fully integrate multiple behavior-driven crash types and their severity outcomes within a single, scalable framework, specially in a way that captures the sequential nature of these behaviors where one risky action may amplify another. This study proposed an integrated multivariate econometric framework to jointly model crash frequency and severity outcomes for three major behaviorally driven crash types: alcohol-related, distraction-related, and aggressive-driving-related crashes. Specifically, using Oregon's 2022 census block group-level crash data, we propose an Integrated Multivariate Negative Binomial – Generalized Ordered Probit Fractional Split (IMNB–GOPFS) model to analyze these dimensions simultaneously while …

Traffic Study, Kennedy Case, Koryn Harms, Min Kaung, Abel Assefa, Eli Lockert, Dj Church

Student Scholar Symposium

No abstract provided.

Gaylord Opryland Congestion Reduction, Kennedy Case

Student Scholar Symposium

Lipscomb University’s College of Engineering is working collaboratively with Gaylord Opryland Resort and Convention Center to explore potential solutions to its traffic congestion problem, particularly during peak times such as the holiday season. This research aims to identify strategies that can alleviate congestion in the resort area. With over one million visitors during the holiday season each year and limited parking capacity, the traffic congestion poses a significant challenge to both operational efficiency and visitor experience. The primary objective of this research is to identify strategies that optimize parking usage, reduce congestion, and improve the overall visitor experience. Beginning with …

Green Roof, Elizabeth Fulton

Student Scholar Symposium

Green roofs, a concept dating back over 100 years, offer a sustainable solution to urban environmental challenges such as poor air quality, the urban heat island effect, and increased stormwater runoff. This study focuses on green roofs as an effective way to address these issues in cities like Nashville, which are experiencing rapid urbanization. By transforming rooftops into green spaces, green roofs can improve air quality, manage stormwater, and reduce urban heat, while also enhancing the aesthetic value of urban environments. The research explores the integration of green roofs, considering factors like substrate composition, plant selection, and environmental conditions. Key …

Smart Traffic Lights, Roa Ghanem

Student Scholar Symposium

Nashville is quickly growing, and as a result, traffic congestion is becoming a bigger challenge for commuters. Longer travel times and increased vehicle emissions are major concerns. This research examines how smart traffic lights can improve traffic flow and reduce congestion in the city. By analyzing peer-reviewed journal articles, this study explores how AI, IoT, and machine learning can optimize traffic signal timing in real time. In particular, simulation models illustrate how these technologies adapt dynamically to changing traffic patterns in cities similar to Nashville. Furthermore, this research compares the cost-effectiveness of smart traffic lights with other solutions, such as …