Engineering Commons^™

Envis: A User-Centered Web-Based Tool For Interactive Visualization Of Environmental Geospatial Data, Saima Sanjida Shila

LSU Master's Theses

Data visualization is an essential part of analyzing environmental geospatial data. Despite having the availability of large environmental datasets, there remains a lack of easily accessible, user-friendly, and interactive visualization tools in this field. Therefore, this study aims to develop a user-friendly and easily available web-based visualization tool. Before developing the tool, we conducted a survey of researchers at the LSU Coastal Studies Institute to collect their opinions on currently available visualization tools. In the survey, 55% of participants responded between somewhat satisfied to dissatisfied with their current visualization tools. Most of the participants mentioned two major limitations of existing …

Lithological Modeling And Aquifer Characterization Of The Coastal Lowlands Aquifer System In Texas, Emmanuel Egyin Hayford

LSU Master's Theses

The Texas Coastal Lowlands Aquifer System (CLAS) is a crucial water resource for the Gulf Coast, serving millions through municipal, agricultural, and industrial supplies. However, its sustainability is increasingly threatened by factors such as population growth, saltwater intrusion, land subsidence, and climate change. A significant limitation is the absence of a comprehensive, data-rich, three-dimensional lithologic model that accurately represents the intricate structure and geometry of the aquifer. Existing models are overly simplistic, treating the hydrogeologic unit as laterally uniform and failing to capture its true hydrogeologic complexity. This study addresses this gap by developing the first high-resolution 3D lithologic model …

Seeing What Matters: Safety-Critical Semantic Segmentation Via Transfer Learning On Construction Sites, Obiora J. Odugu

LSU Master's Theses

Autonomous robots are increasingly deployed on construction sites for tasks such as progress monitoring, inspection, and safety assessment. For these robots to operate effectively, they must perceive and interpret complex, dynamic environments populated by workers, machinery, and unstructured terrain. Achieving reliable perception depends on high performing semantic segmentation models trained on large volumes of annotated data—an expensive and logistically challenging requirement in construction due to privacy restrictions, variable site access, and slow digitalization. This research addresses the challenge of limited labeled data by investigating transfer learning as a label-efficient approach for construction-site segmentation. Specifically, it explores whether road construction imagery—abundant …

Effects Of Hydrological Connectivity On Created Marsh Sustainability, Katie Swann

LSU Master's Theses

While efforts are being made to curb the high rate of coastal land loss in Louisiana, and even to restore ecosystem services and functions, it is generally accepted that restoration of these areas and functions is not a one-to-one value. It may take decadal time scales to reach efficient functional processing of nutrients and carbon storage rates, which may never reach true capacity comparable to similar naturally-organized systems. Although it is imperative to preserve these areas, restoration of ecosystem services and biogeochemical processes of coastal wetlands are preferable to future without action scenarios. Effectively directing the use of the limited …

Sustainable Robotic Construction: A Computational Particle Packing Approach For The Development Of Sustainable, Low-Cement 3d Printable Materials, Aranya Aumit Paul

LSU Master's Theses

Construction 3D Printing (C3DP) holds great potential for automated construction but faces key challenges, including the high Portland cement content of its printing materials. The high cement content raises material costs, causes shrinkage and thermal cracking, and increases its carbon footprint. This study introduces a novel hybrid computational pipeline that combines image based automated gradation analysis with 2D stochastic particle packing simulation, to design low-cement printable materials with minimal experimental testing. The image-based gradation system achieved a mean absolute error under 3.64% across six fine and coarse aggregate types. The particle packing simulation demonstrated an average error of less than …

Chplx: The Hpx Solution For Bridging Chapel And C++, Shreyas Swanand Atre

LSU Master's Theses

Historically, domain scientists faced steep learning curves due to low-level programming models and fragmented tooling. Between 2003 and 2008, Cray, now part of HPE, introduced the Chapel language as part of DARPA’s High Productivity Computing Systems (HPCS) program. Today, Chapel remains under active development and is used across research and production projects. In parallel, the STE||AR Group has advanced C++-based parallel programming through HPX, a standards-conforming runtime that provides lightweight tasking, futures, and distributed execution while abstracting much of the algorithmic “heavy lifting.” Yet for many domain scientists, C++ presents a steeper learning curve than Chapel. To close this complexity …

Investigation Of Co-Current And Counter-Current Multiphase Flow In Upstream Drilling And Production Applications, Hazem Fleifel

LSU Doctoral Dissertations

In the domain of upstream Petroleum Engineering, the dynamics of co-current and counter-current multiphase flows present huge challenges, significantly impacting the efficiency of associated processes. This study investigates two specific applications concerning these flow behaviors, involving both laboratory experiments and transient computer simulations. This work investigates two distinct well control and production enhancement processes, involving multiphase flow dynamics: the bullheading kill procedure and liquid-assisted gas lift (LAGL).

The first topic (Topic 1) explores the bullheading process, a type of well control methods, by challenging the traditional understanding that gas removal efficiency increases monotonically with injection pump flow rate. Through 1D …

Learning Neural Point Processes For Long Event Sequences, Zhuoqun Li

LSU Doctoral Dissertations

This research presents a comprehensive series of studies aimed at advancing learning neural point processes for long event sequences, with applications spanning disaster resilience, crime forecasting, and healthcare. Structured around three interconnected studies, this work addresses core challenges in temporal point process (TPP) modeling, efficient handling of long event sequences, and improving accuracy over extended forecasting horizons by reinforcement learning.

The first study proposes the Sparse Transformer Hawkes Process (STHP) to model long asynchronous event sequences. Traditional neural network-based TPPs struggle with long event sequences due to computational inefficiencies. To address this, the STHP model combines two components: a temporal …

Exploring Longitudinal Stability Of Spatiotemporal Sequential Patterns By Means Of Autoencoder Schemes For Eeg Based Personal Identification, Muhammed E. Oztemel

LSU Doctoral Dissertations

Robust personal identification remains a critical and challenging task in the digital era. Electroencephalography (EEG) offers a unique biometric modality that captures individual brain dynamics through complex neural signals. This dissertation proposes autoencoder (AE) based feature extraction and subject identification through these features. EEG recordings are first transformed into topographic maps to represent spatial brain activity. Consecutive topomaps are then concatenated to capture temporal transitions across frames. Convolutional autoencoders (CAEs) are used to learn spatial and temporal patterns, while domain-adaptive AEs are designed to model evoked potential based responses. Additionally, self-attention mechanism is incorporated to enhance feature representation. To analyze …

Ai-Based Object Detection And Risk Identification For Enhanced Construction Site Safety, Mahdi Bonyaniakbarabadi

LSU Master's Theses

Recent advancements in computer vision for construction site safety have encountered significant hurdles, especially in the nuanced tasks of object detection and the identification of unsafe worker behaviors. These challenges are often exacerbated by complex and cluttered backgrounds, wide variations in object scale, and inconsistent image quality. While existing methodologies have utilized attention mechanisms to analyze spatial and temporal features, they frequently neglect the benefits of adaptive sampling and channel-wise feature adjustments, thereby failing to exploit potential spatiotemporal redundancies. This thesis introduces a two-pronged approach to address these limitations. First, we propose the Optimized-Position Network (OP-Net), a novel architecture for …

A Multi-Scale Numerical Analysis Of Wave Propagation Through Coastal Vegetation Using Proteus & Xbeach, Cole M. Statler

LSU Master's Theses

Coastal vegetation attenuates waves in the nearshore zone and protects shorelines from storm surge and wave action. It also traps nutrients and sediment, and participates in the formation of land over longer time scales. These features of vegetation make it a common component of nature-based engineering projects. Interaction of water waves and flow with vegetation, however, can involve unsteady and turbulent flow, non-hyrdostatic pressure effects, and air entrainment that can hinder the use of simple parametric representations of vegetation drag. XBeach, a one- and two-dimensional production model applies reduced-order methods, prioritizing computational efficiency. Vegetation is represented in XBeach as a …

The Operational Performance Of Buildings In A Humid Subtropical Climate: Insights From Empirical Data And Assessment Models, Oluwafemi Awolesi

LSU Master's Theses

This thesis evaluates the operational performance of residential and non-residential buildings in a humid subtropical climate, emphasizing Indoor Environmental Quality (IEQ) and energy performance through empirical data and assessment models. Motivated by the increasing need for integrated sustainability evaluations, this study combines a systematic review with multi-method field investigations to advance understanding in this domain. The systematic review critically analyzed 99 case study articles, identifying dominant IEQ assessment methodologies and highlighting methodological inconsistencies that hinder cross-study comparability. Emerging computational approaches, although promising, remain underutilized. The review advocates for standardized, climate-responsive, and feedback-oriented evaluation frameworks. Field investigations assessed IEQ and energy …

Adaptive Multi-Agent Reinforcement Learning For Electric Vehicle Charging Optimization Under Dynamic Traffic Conditions, Shaghayegh Rabbanian

LSU Master's Theses

Electric vehicle (EV) charging optimization is a critical challenge in sustainable transportation. This study focuses on three fundamental questions: (1) when is the best time to charge an EV, (2) where is the optimal charging location, and (3) how should charging be planned considering navigation and routing decisions. Our primary objective is to determine the optimal time and location for EV charging while accounting for key factors such as real-time traffic conditions, spatial distribution of charging stations, and EV-specific attributes such as state of charge (SOC), driving range, and efficiency. To develop a robust and adaptive EV charging recommendation system, …

Efficient Small Tool Detection In Construction Via Lightweight Deep Neural Networks, Maryam Soleymani

LSU Master's Theses

Construction sites are dynamic and inherently hazardous environments, where small hand tools—although essential—pose serious safety risks due to their frequent use, portability, and tendency to be misplaced or dropped. This study introduces a novel and lightweight deep learning-based architecture, Lightweight Small Tool Detection (LSTD), specifically designed for fast detection of small tools in unstructured and challenging construction environments. Recognizing that small object detection remains a persistent limitation in existing computer vision models, particularly under poor lighting or cluttered backgrounds, LSTD integrates advanced modules for enhanced feature extraction, fusion, and classification. It achieves notable improvements in accuracy, recall, and computational efficiency …

Shock Induced Droplet Aerobreakup For Newtonian And Non-Newtonian Fluids, James Leung

LSU Doctoral Dissertations

This research investigates shock-induced aerodynamic breakup (aerobreakup) of fluids with different stress-strain behaviors. The central hypothesis is that shear stress from highspeed gas flow manifests differently depending on a fluid’s strain response, influencing droplet breakup morphology, fragment size distribution, and drag-induced acceleration. To test this, experiments and simulations were performed on μm–mm sized droplets of Newtonian (water) and shear-thinning fluids (nanofluids or xanthan gum). Two experimental setups were used: an open-ended shock tube and a closed conventional shock tube. In the openended setup, a normal shock impacts a stationary droplet held by an acoustic levitator. Droplet breakup and gas dynamics …

From Devices To The Cloud: Digital Forensics In The Changing Social Media Landscape, Joseph Brown

LSU Master's Theses

This thesis presents a comprehensive digital forensic analysis of emerging and alternative social media platforms, including Truth Social, Threads, Bluesky, Nextdoor, and Neighbors. These platforms, which range from politically aligned alt-tech networks to hyperlocal neighborhood apps, present unique forensic challenges and security vulnerabilities. Across all case studies, established forensic techniques were applied using a hybrid methodology combining mobile device analysis, network traffic monitoring, and API interrogation. Findings include the discovery of plaintext credentials, session tokens, and other sensitive artifacts, particularly in platforms with weaker security postures such as Truth Social, Bluesky, Nextdoor, and Neighbors. Threads, by contrast, demonstrated greater resilience …

Rethinking Green Building Development Through Policy And Operational Metrics: Insights From Baton Rouge And Beyond, Oluwafemi Awolesi

LSU Doctoral Dissertations

This dissertation explores the challenges and opportunities associated with the development, adoption, and performance of green buildings in regions with relatively low certification uptake, drawing insights from Baton Rouge and its parish system as a case study. It addresses three primary research questions: (1) How can the adoption rate of green buildings be enhanced? (2) How do certified buildings perform compared to their non-certified counterparts? (3) What operational metrics can be applied to better evaluate building performance in the future?

Using a mixed-methods approach, the study examines stakeholder perceptions in East Baton Rouge, Louisiana, investigates energy performance, indoor environmental quality, …

Empirical Analysis Of Incentivized Energy Assessment Recommendations And Iiot Cost-Effectiveness In U.S. Smes, Fatemeh Ghafari

LSU Master's Theses

The industrial sector in the United States accounted for 33% of total energy consumption in 2022. Small and medium-sized enterprises (SMEs), which comprise 99.9% of U.S. businesses present a critical opportunity for energy efficiency improvements. Although energy audits provide actionable Assessment Recommendations (ARs) to reduce consumption, high implementation costs remain a key barrier to adoption.

While prior studies have explored rebate programs, most are limited to residential and commercial sectors or focus narrowly on specific technologies or geographic areas for the industrial sector. The objective of this study is to empirically investigate the “Incentivized Assessment Recommendation” (IAR) trends and to …

Retrospective Study And Predictive Modeling Of The Impact Of Social Determinants Of Health On Sepsis Outcomes, Mwembezi Aaron Nyelele

LSU Doctoral Dissertations

Sepsis, a life-threatening organ failure caused by the body’s abnormal and harmful response to an infection, remains a major global and national health challenge. In the United States, it contributes significantly to hospital mortality and imposes a substantial economic burden, with billions spent annually on treatment. Early diagnosis is difficult due to the nonspecific nature of sepsis symptoms, often leading to delays in care and poorer outcomes. As the incidence and severity of sepsis rise, identifying factors that influence outcomes is increasingly critical. Emerging research has shown that Social Determinants of Health (SDOH), including economic stability, education, neighborhood and built …

Towards Leveraging Social Media Data For Fostering Collaborations Among Non-Profits, Monazil Chowdhury

LSU Doctoral Dissertations

Nonprofit organizations serve a crucial role in tackling a wide range of significant social, environmental, and economic issues. But it is often hard to get a clear picture of their work because their information is spread out and it is difficult to see how they are collaborating. To address this issue we developed a web-based tool to collect scattered data—from a variety of sources, such as the IRS, social media, and the Census, into one easy-to-use resource. The tool begins by taking IRS records and geocoding each nonprofit’s physical address With its coordinates. It then retrieves census tract information from …

The Design And Effect Of Continuum Robot Compliance On Locomotion, Parsa Molaei

LSU Doctoral Dissertations

Continuum robots, due to their compliant structures and ability to navigate through constrained environments, offer significant advantages in applications requiring safe physical interaction and dexterous motion. However, challenges related to limited structural stiffness, payload capacity, and precise control remain open problems in the field. This dissertation presents novel contributions aimed at addressing these limitations through two main actuation units of continuum robots: tendon-driven continuum robots (TDCRs) and concentric tube robots (CTRs). In the first part, we focus on methods to improve the stability and modify the stiffness of the TDCR. A tendon decoupling strategy is introduced for planar TDCRs. The …

Anion Exchange Membrane Transport And Accelerated Testing Methods For Co2 Electrolyzers With Cu-Based Electrocatalyst, John C. Hendershot

LSU Doctoral Dissertations

Electrocatalytic carbon dioxide (CO₂) reduction to C₂₊ products holds promise for low carbon intensity fuels, chemicals, and food; however, durability challenges, particularly bicarbonate (HCO₃^-)and carbonate (CO₃^2-) salt precipitation, hinder their commercialization. This report considers water (H₂O) and ion transport properties of conventional anion exchange membranes (AEMs) in zero-gap membrane electrode assembly (MEA) configurations using Cu electrocatalysts. Transport characterization includes H₂O diffusion, permeability, potassium (K⁺) diffusion, and transference numbers using three commercial AEMs, including piperidinium-based (Versogen), quaternary ammonium-based (Fumasep), and imidazolium-based (Dioxide Materials) membranes. Accelerated lifetime …

Soft Hexapod Robot With Tendon-Driven Continuum Legs For Internal Infrastructure Inspection, Setayesh Yavari

LSU Master's Theses

The need for robotic systems capable of operating in confined, hazardous, or complex environments has driven interest in soft and legged platforms for industrial inspection and structural integrity assessment. This thesis presents the design and fabrication of a tentacle-like, soft-legged hexapod robot, which uses six cable-stiffened, pre-curved, tendon-driven continuum robot (TDCR) legs. These biologically inspired legs are designed to offer a balance between compliance and control, enabling the robot to navigate unstructured terrains and potentially grasp cylindrical structures such as pipes. The design phase involved the development and comparison of multiple leg geometries using CAD modeling and finite element analysis …

Low Temperature Methane Coupling With Co And Co2, A K M Kazi F.M. Aurnob

LSU Doctoral Dissertations

Methane is the smallest hydrocarbon and the most abundant component in natural gas. Despite its availability, its chemical utilization has remained limited due to the challenges associated with direct methane activation and conversion. Most of the methane oxidation and oxidative carbonylation reactions in literature have been carried out at high-pressure using batch reactors or at ambient pressure using flow reactors. While batch reactors have been shown to have higher product yields, they are limited in their capability to provide real-time kinetic insights and comprehensive mechanistic understanding of the reactions involved due to the long residence time. This limits rationalization of …

Participation Of Battery Energy Storage Systems In Load Frequency Control Of Power Systems, Zakaria Afsharbakeshloo

LSU Doctoral Dissertations

In this research, functionalities and roles of Battery Energy Storage Systems (BESSs) in power systems are extended beyond primary frequency control (PFC). The BESSs, while participating in PFC, are controlled through charge controllers to first maintain their state-of-charge (SOC) within an acceptable range through a primary charge controller, and to recharge the BESS to its maximum SOC through a secondary charge controller. This forms a hierarchical frequency and SOC control of power grids with BESSs. In this regard, multiple BESS case is considered as well, and by employing the SOC balancing principle, it is shown that desired power sharing among …

Ergonomic And Biomechanical Assessment Of Vertical Ladder Climbing For Exoskeleton Integration In Construction Tasks, Ehsan Shourangiz

LSU Master's Theses

Active exoskeletons are increasingly utilized in physically demanding industries such as construction and manufacturing to reduce strain and lower the risk of work-related musculoskeletal disorders, supporting worker safety and long-term health. However, most existing systems are designed for repetitive tasks like lifting or prolonged standing, with limited consideration for dynamic activities such as vertical ladder climbing. Ladder climbing is common and physically demanding in industrial environments, often required to access elevated areas like scaffolding, tanks, or rooftops. Since exoskeletons are intended to remain worn throughout multiple tasks, requiring workers to remove and re-don the device during ladder climbing would reduce …

Magnetic Field Enabled Assembly And Propulsion Of Colloidal Particles In A Magnetic Medium, Hashir M. Gauri

LSU Doctoral Dissertations

Colloidal particles are nano/micro meter-sized particles dispersed in a fluid medium and serve as diverse building blocks for assembling complex structures. The ease of tunability of the shape, size, and interparticle interactions of colloidal particles facilitates their assembly into rich structures and phases that mirror the assembly process of atomic systems. Often regarded as "big atoms" colloidal particles provide an ideal model system for investigating complex phenomena in condensed matter, such as crystallization and nucleation. While the assembly of colloids under thermodynamic equilibrium has been extensively studied, recent interest has shifted toward exploring colloids in non-equilibrium conditions to create dynamic …

Anion Exchange Membrane Durability For Electrochemical Co2 Reduction In Membrane Electrode Assembly Cells, Soundarzo Tasnim

LSU Master's Theses

The electrochemical reduction of CO₂ using membrane electrode assembly (MEA) cells has emerged as a promising approach for carbon capture and conversion into valuable products. This study investigates the degradation mechanisms of anion exchange membranes (AEMs) in CO₂ reduction applications, focusing on Sustainion X37-50, PiperION, and FAA-3-50. The research analyzes the impact of chemical and mechanical degradation on membrane performance, highlighting key stability challenges in long-term operation. Fourier transform infrared spectroscopy (FTIR) and electrochemical impedance spectroscopy (EIS) were employed to monitor functional group stability and ionic conductivity loss over extended operation. The results indicate that hydroxide-induced degradation leads to nucleophilic …

Energy Equity In The Built Environment: Analyzing Building Energy Consumption For American Low-Income Households, Sorena Vosoughkhosravi

LSU Doctoral Dissertations

The built environment consumes a significant amount of energy in the United States, with outdated and inefficient affordable housing increasing financial pressure on low-income households (LIHs) who face high energy burdens. This research aims to assess the energy performance of American households, focusing on LIHs, to promote energy justice by providing data-driven insights and models for energy efficiency improvements. More specifically, this research aims to (1) create a large-scale national residential building energy dataset by integrating the American Housing Survey and the Residential Energy Consumption Survey using machine learning techniques; (2) analyze and model American household occupancy profiles by leveraging …

Evaluation Of The Effects Of Various Types Of Inert And Active Fillers On Asphalt Mixture Performance, Mohammad Hadizadeh Pirbasti

LSU Master's Theses

Abstract:

The performance of asphalt mixtures is significantly influenced by the type and characteristics of fillers used as a replacement for filler part of the aggregates’ batching. According to this research investigation the performance along with durability characteristics of asphalt mixtures are evaluated through different inert and active fillers. The fillers used include Fly Ash, Cement, steel slag powder, and additional filler. These fillers incorporate into two types of asphalt mix design of Stone Matrix Asphalt (SMA) and a surface mix. Fillers are categorized according to their reactive properties alongside their physical attributes leading to active fillers strengthening bond formation …