Civil Engineering Commons^™

Multidimensional Total Quality Management And Its Effects On Sustainability And Performance In Industrialized Building System Projects, Felix Delmonte

Mechanical and Civil Engineering Faculty Publications

This study develops and tests a multidimensional total quality management (TQM) framework to explain how distinct quality practices influence environmental sustainability, construction quality, cost and schedule performance, waste reduction, energy efficiency, stakeholder satisfaction, and overall project performance in industrialized building system (IBS) projects. Soft and hard TQM dimensions such as leadership commitment, customer focus, employee involvement, training and continuous improvement, process management, supplier quality, and data driven decision making are operationalised and linked to eight outcome constructs. Partial least squares structural equation modelling (PLS SEM) is used to estimate direct effects and to examine mediation by waste reduction and energy …

Fall Hazard Prevention: A Zero-Fatality Goal For Health, Safety, And Well-Being On Construction Sites, Alena Richardson, Chaidaliz Minguela Alicea, Nicola Kaehler, Charlene Weaver

Discovery Day - Daytona Beach

Jobsites face hazards like falls, which threaten the health, safety, and well-being of construction workers. Falls are the leading cause of all accidents and fatalities in construction, accounting for approximately 40% of all worker deaths in 2023. While achieving a zero-accident rate for falls is inherently challenging, prioritizing a zero-fatality objective represents a practical and impactful starting point. The Occupational Safety and Health Administration (OSHA) recommends a six-step action approach for the prevention and control of hazards like falls. Of particular interest, the State of Florida is consistently ranked among the highest for construction fall fatalities, often attributed to insufficient …

Climate Resilient Infrastructure: The Problem Shift, Tyler Lautieri, Isaiah Morrison, Harrison Totten

Discovery Day - Daytona Beach

Climate change is a heavily debated topic, but recent studies and data show that climate change is leading to an increase in the frequency and severity of hazards. Infrastructure systems are subjected to more compound and cascading events that lead to the degradation of the systems. More traditional infrastructure design relies on concern that the system will be subjected to single hazard issues, and the design focuses on preventing structural failure during these isolated events. These approaches often fail to account for long term degradation of the system, as well as the interacting hazards, and system interdependence, which makes resilience …

Functionality Risk Assessment And Risk-Based Management For Critical Infrastructure Systems, Anteneh Zewdu Deriba

Dissertations and Theses

Critical infrastructure systems such as transportation networks serve as the lifelines of modern society, supporting economic activity and ensuring access to critical services. Their disruption under extreme events can produce consequences extending far beyond physical damage to individual assets. In transportation networks for instance, failures of critical assets such as bridges and tunnels can reduce accessibility of communities, limit freight capabilities for commerce, and increase travel distance and travel time of road users. These consequences associated with the system functionality loss are tied not only to the physical vulnerability and failure of individual assets, but also to the system configuration …

Ensemble Learning Framework For Predicting Close Proximity Tire–Pavement Noise On Expressways, Woo Young Cho, Jin Hwan Kim, Guk Gon Song, Kyungnam Kim, Youngguk Seo

Faculty Articles

Traffic noise is a critical public health concern affecting millions of highway users and adjacent residents worldwide. In response, many transportation agencies have adopted functional surface materials to reduce noise at the source on pavement, but assessing their effectiveness remains expensive and logistically challenging. Close Proximity (CPX) testing quantifies tire-pavement noise but requires specialized equipment costing $50,000-$126,000 and is limited to existing pavement, preventing proactive noise assessment during pavement design. This study develops machine learning models to predict CPX noise levels from readily available pavement characteristics, eliminating the need for costly tests during design and planning phases. To train and …

Alternate Method For Determining The Liquid Pressure Recovery Factor, Bryson H. Parker

All Graduate Reports and Creative Projects, Fall 2023 to Present

The term liquid pressure recovery factor aids in determining the flowrate through valves at the maximum flowrate under choking conditions. The pressure recovery factor can be difficult to determine for certain types of valves based on the industry standard procedure. This report looks at the current industry standard procedure and adds a procedure in the event of the industry standard not being feasible. Often it is not feasible for a testing facility to supply enough flow through the valve to reach the industry standard. The industry standard is to test the valve at the maximum flowrate with a constant upstream …

Expected Structural Damage, Residual Capacity, And Repairability Of Light-Frame Timber Houses, Mikayla Caruthers

Master's Theses

Earthquake damage in light-frame timber structures is commonly evaluated using peak inter-story drift. However, drift alone does not fully represent the remaining structural capacity of a building or its ability to be repaired following a seismic event. Although expected structural damage, residual capacity, and repairability have each been studied extensively, these concepts are often considered independently, leaving limited guidance that links them within a unified post-earthquake assessment methodology.

This thesis establishes an integrated framework that relates expected structural damage, residual capacity, and repairability for light-frame timber residential structures. Existing literature was synthesized to develop drift-based damage-state classifications, identify methods for …

Effect Of Rheology Modification On Fiber Orientation And Dispersion In 3d-Printed Ultra-High-Performance Concrete, Haodao Li, Alfred Addai-Nimoh, Seongho Han, Kamal H. Khayat

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The extrusion process in 3D concrete printing (3DCP) facilitates horizontal alignment of steel fibers along the printing direction, thus enhancing the load-bearing capacity of printed elements. However, such shear-induced fiber alignment is highly sensitive to rheological properties. This study investigates how variations in dynamic yield stress (τd) and plastic viscosity (μ), influence the extrudability, fiber orientation and dispersion, and anisotropic mechanical behavior of ultra-high-performance concrete (UHPC). Five viscosity-modifying agent (VMA) types were incorporated at two content levels to modify the rheology of printable UHPC. Results showed that moderate VMA additions improved printability, whereas excessive contents markedly increased τd and μ; …

Human-Centered Electric Vehicle Adoption Framework For Smart Mobility: Modeling Perceived Range And Charging Anxiety As A Psychological Barrier, Fatemeh Nazari, Abolfazl (Kouros) Mohammadian, Thomas Stephens

Civil Engineering Faculty Publications

Electric vehicles (EVs) offer a transformative pathway toward reducing the environmental, economic, and health-related externalities of internal combustion engine vehicles in urban settings. Despite substantial advances in battery technology, charging infrastructure expansion, and supportive policy incentives, EV penetration remains limited which poses challenges for smart and sustainable mobility planning. A critical yet insufficiently modeled barrier to adoption lies in the psychological perceptions surrounding electric driving range and charging reliability, which is commonly framed as “range anxiety,” but more broadly reflecting perceived range and charging anxiety. To address this gap, this study introduces a latent psychological construct capturing individuals’ perceived range …

Five-State Seismic Damage Classification Of Steel-Girder Bridges On Soft Soil Using Directional Intensity Measures And Multi-Parameter Damage Indices, Ibrahim Alomari, Woubishet Zewdu Taffese, Mohammad Hossein Afsharmovahed, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Rapid yet accurate post-earthquake damage assessment of highway bridges is essential to ensure transportation network resilience. Traditional inspection, fragility analysis, and finite element modeling are time-consuming or inaccurate for real-time decision-making. This study compares ten machine-learning classifiers for the seismic damage states of highway steel-girder bridges that incorporate directional intensity measures to represent the variance of ground motions. Based on the nonlinear time-history analyses of two Missouri bridges, one Michigan bridge, and one Wisconsin bridge, multi-parameter structural damage indices were proposed and mapped to five damage states from none to collapse. Among ten supervised algorithms studied, the artificial neural network …

Building Services Engineering July/August 2026

Building Services Engineering

This issue of Building Services Engineering features heat pumps, propane usage, solar power, and ventilation for indoor air quality. Features include district heating, HVACR optimisation, lift retrofitting, EU water policy, and an interview with WiBSE Ireland Chair Heather Holt.

Probabilistic Modeling Of Hurricane Hazards And Structural Reliability Of Offshore Wind Turbines Under Climate Change, Susmita Bhowmik

All Dissertations

Hurricanes are among the most destructive natural hazards in the United States, especially along the Atlantic and Gulf coasts. Climate change is expected to affect hurricane activity by changing important environmental conditions. At the same time, offshore wind energy is expanding, creating a need to understand hurricane risks to offshore wind turbines.

This dissertation develops a stochastic hurricane simulation framework to estimate hurricane wind hazards for coastal and offshore regions along the U.S. East Coast and Gulf Coast. The framework generates synthetic hurricane tracks using updated storm-frequency data and is validated against historical records from HURDAT2, NOAA buoy wind observations, …

Theory-Informed Generative Agents For Human Behavioral Modeling In Disasters, Liming Lu

All Dissertations

This dissertation develops a theory-informed generative-agent framework for modeling human behavioral decisions in disasters. Existing flood and disaster preparedness models often emphasize physical hazards, infrastructure exposure, or statistical correlations, but they struggle to capture the heterogeneous and evolving choices households make. This limitation is especially important for climate-related hazards, where future damage depends not only on changes in rainfall, inundation, and urban development, but also on decentralized protective actions such as house elevation, flood insurance, evacuation, and early preparedness. The dissertation integrates two empirical studies: a flood-risk study in Charleston, South Carolina, and a household disaster-preparedness study across hurricane contexts. …

Leveraging Deep Learning Recurrence And Attention Mechanisms For Flood Forecasting And Assessment, Elnaz Heidari

All Dissertations

Predicting how much water will flow in rivers and streams is important for managing floods, water supply, and the environment. Traditionally, government agencies have used complex models, such as the National Water Model (NWM), which simulate how much water moves through landscapes using physical laws and real-world data. However, recent advances in Artificial Intelligence (AI) have enabled new ways to make these predictions. This research explored whether AI-based models could predict river discharge more accurately. These AI models learn patterns from past data instead of relying only on physical rules. To find out how well they work, the AI models …

Evaluation Of Dredged Sediments As A Partial Replacement For Fine Aggregate In Mortar And Concrete, Ashish Gautam

Graduate Theses and Dissertations (2019 - present)

The feasibility of using dredged sediment from the Mobile River as a partial replacement for fine aggregate in mortar and concrete was investigated through a series of laboratory characterization and performance evaluation. Three dredged sediment samples (A, B and C) were initially examined, and Sample A was selected for further evaluation due to its closer resemblance to natural fine aggregate. This sample exhibited lower moisture content, higher sand equivalent values, higher specific gravity, and lower absorption. Mortar mixtures with 0, 10, 20, 30, 50, 75 and 100% dredged sediment replacement showed decreasing workability as the replacement level increased. The 20% …

An Integrated Model For Post-Hurricane Displacement, Shelter Demand And Shelter Allocation, Nirmal Adhikari

All Theses

This thesis develops an integrated tract-level framework for estimating post-hurricane displacement, short-term shelter demand, long-term shelter demand, and shelter allocation under hurricane wind hazards. The framework combines parametric wind-field modeling based on HURDAT2 and EBTRK hurricane data with HAZUS-based fragility and loss functions, uninhabitability relationships, demographic factors, and an insurance-sensitive recovery model. Tract-level insurance adequacy is estimated using American Community Survey data, National Association of Insurance Commissioners premium data, and the National Risk Index, using five scenario-based models; the combined home-value and hazard-risk model is adopted for final analyses. To evaluate post-disaster housing capacity, the study estimates the number of …

Characterization, Transport Modeling, And Image Analysis Of Rover-Terrain Interaction For Lunar Regolith In-Situ Resource Utilization, Luke A. Manolescu

All Theses

NASA has declared a return to the lunar surface and the need and demand for sophisticated In-situ Resource Utilization (ISRU) is the highest in history. ISRU will require regolith excavation, transport, and processing in order to harvest the valuable resources available, support surface operations, and keep astronauts alive. Characterizing the lunar regolith is essential to understanding the mechanical and physical behavior of the material that will be used to construct berms and structurally support astronaut habitats and landers. Any construction on Earth requires an in-depth geotechnical site assessment prior to any construction to rule out any potential site issues that …

The Influence Of Rainfall And Land Cover Change On Streamflow Variability In Eastern Florida Watersheds, Brynn Romberger

Theses and Dissertations

Streamflow in Florida watersheds is influenced by both land cover change and rainfall variability, but separating their contributions is difficult because both have changed over recent decades. This study evaluated rainfall trends and land cover change to determine which better explains flood and drought threshold exceedance across 27 USGS streamflow gauges within the St. Johns River Water Management District (SJRWMD) from 1985 to 2025. Streamflow was characterized using change-point, trend, and variability analyses with a six-threshold exceedance framework. Land cover was quantified using the National Land Cover Database (NLCD), rainfall characteristics were derived from the Analysis of Records for Calibration …

Wildfire Impacts On Fluvial Hydrology From Watershed To National Scales, Paige G. Tunby

Civil Engineering ETDs

Wildfires alter the water quantity and quality in downstream river networks. Fires promote biodiversity, maintain habitat, and provide many ecosystem services in a fire-adapted landscape. However, changes in the natural fire regimes can alter ecosystem function and threaten the water security of impacted downstream communities. The magnitude, timing, and persistence of these impacts are difficult to predict due to the lack of high-resolution datasets with adequate coverage to evaluate spatiotemporal trends after a fire. This dissertation moves us beyond the status quo to evaluate post-fire fluvial responses across scales, from the event-scale impacts after the Hermit’s Peak-Calf Canyon wildfire in …

A Machine Learning Approach For Water Quality Assessment In The Lower Rio Grande Valley Watershed, Saika Nowshin Nowrin, Chu-Lin Cheng, Jungseok Ho, Jinwoo An, Fatemeh Nazari

Civil Engineering Faculty Publications

Water quality analysis plays an essential role in maintaining the health and sustainability of river ecosystems, especially in semi-arid regions like the Arroyo Colorado Watershed in South Texas. Since the river is a vital source of water supply for local communities, agriculture, and wildlife, it faces significant challenges and pollution from land use changes, climate variation, and agricultural runoff. Continuous monitoring and assessment of water quality parameters and their temporal variability are essential to ensure the drinking water supply and aquatic ecosystem health. However, comprehensive laboratory-based water quality investigations are often constrained by higher costs, logistical complexity, and limited manpower. …