Identification Of Thruster Faults In Underwater Vehicles By Using Custom Encodings In Spiking Neural Networks, Donovan Gegg

LSU Master's Theses

Autonomous Underwater Vehicles (AUVs) are untethered robotic platforms used for tasks such as seafloor mapping, infrastructure inspection, and environmental monitoring. Recent technological advances have produced smaller, more affordable platforms, broadening access to research teams and small companies alike. This miniaturization comes at the cost of them handling drawbacks associated with a more compact machine such as reduced battery capacity as well as limited processing and sensing capabilities. These constraints make small-sized marine vehicle’s reliability critical as they can cause malfunctions, making the loss of a vehicle more likely. Actuator faults are particularly consequential as unintended and unstable control in an …

Innovative Design Methodology For Durable Open-Graded Friction Course Asphalt Mixtures, Anas Abualia

LSU Doctoral Dissertations

Open-graded friction course (OGFC) is a thin asphalt mixture surface layer with a high percentage of coarse aggregates and high interconnected air voids, which provides improved skid resistance, visibility, and decreased pavement-tire noise. However, construction personnel at DOTD reported that conventional OGFC mixtures have short service life (raveling distress). Further, their structural contribution to the pavement structure is commonly neglected and designed only for functionality purposes.

The objective of this study was to develop a rational mix design methodology to improve the durability of OGFC asphalt mixtures. Specific objectives are to: (1) conduct a rheological and chemical characterization of polymer-, …

Development Of Machine Learning-Based Tool For Prediction Of Long-Term Field Performance Of Asphalt Concrete Overlays In A Hot And Humid Climate, Elise Mansour

LSU Doctoral Dissertations

The performance of pavement plays a critical role in Maintenance, Rehabilitation and Reconstruction (MR&R) for highway agencies. Reliable and accurate estimation of pavement performance can be instrumental in prioritization of the limited resources and funding for highway agencies. The latter requires robust prediction models that can handle large-scale, real-world data and can forecast pavement performance in the long run. Unfortunately, the traditional performance prediction models have raised concerns regarding their efficiency and accuracy. It is because these models were based on a limited number of explanatory variables, were not up-to-date and were designed for forecasting short-term (up to five years) …

A Feasibility Study Of Drilling Fluid Slippage For Wellbore Displacement, John Johnson

LSU Master's Theses

In the ideal plug-flow mode viscoplastic drilling fluids display uniform frontal velocity due to wall slippage (at very low flowrate limited by the fluid’s yield strength). The flow rate could be increased by raising the yield strength that would make the fluid best candidate for frontal displacement. Based on this concept the study qualifies wall slippage effect for wellbore displacement. Using a conceptual model of fluid motion between two parallel plates defines maximum velocity as a function of shearing rate and yield stress. Conversion to coaxial geometry gives practical formulas for fluid testing with rotational viscometer. A new analysis of …

A Study On High-Frequency Bending Fatigue, Microhardness, Tensile Strength, And Microstructure Of Parts Made Using Atomic Diffusion Additive Manufacturing (Adam) And Additive Friction Stir Deposition (Afsd), Hamed Ghadimi

LSU Doctoral Dissertations

This dissertation reports the findings of several studies on the mechanical and microstructural properties of parts made using atomic diffusion additive manufacturing (ADAM) and additive friction stir deposition (AFSD). The design of a small-sized bending-fatigue test specimen for an ultrasonic fatigue testing system is reported in Chapter 1. The design was optimized based on the finite element analysis and analytical solution. The stress–life (S–N) curve is obtained for Inconel alloy 718. Chapter 2 presents the findings of ultrasonic bending-fatigue and tensile tests carried out on the ADAM test specimens. The S-N curves were created in the very high-cycle fatigue regime. …

Augmenting External Surface Pressures’ Predictions On Isolated Low-Rise Buildings Using Cfd Simulations, Md Faiaz Khaled, Aly Mousaad Aly

Faculty Publications

The aim of this paper is to enhance the accuracy of predicting time-averaged external surface pressures on low-rise buildings by utilizing Computational Fluid Dynamics (CFD) simulations. To achieve this, benchmark studies of the Silsoe cube and the Texas Tech University (TTU) experimental building are employed for comparison with simulation results. The paper is structured into three main sections. In the initial part, an appropriate domain size is selected based on the precision of mean pressure coefficients on the windward face of the cube, utilizing Reynolds Averaged Navier-Stokes (RANS) turbulence models. Subsequently, recommendations regarding the optimal computational domain size for an …

Shape Memory Polymer-Based Multifunctional Syntactic Foams, Siavash Sarrafan

LSU Doctoral Dissertations

With the increase in popularity of shape memory polymers (SMPs), especially in applications such as aerospace, textile, biomedical engineering, and even structures, the weight of the material and the devices made with it has always been a crucial factor. Using the shape memory polymer as a matrix to make a syntactic foam is one of the best and most affordable approaches to creating a lighter material that still has the shape memory effect. The addition of particles of different stiffness, strength, and size, with variable fractions, creates a composite that enables engineering the mechanical, as well as other physical and …

Development Of Novel Electrodes And Electrolytes For Safer Aqueous Ammonium Ion Batteries With Enhanced Performance., Shelton Farai Kuchena

LSU Doctoral Dissertations

The Lithium-ion battery (LIBs) system has dominated the battery market because of its superior energy and power density. Problems related to LIBs such as safety, scarcity of cobalt and lithium have led researchers to explore alternative battery systems. NH₄⁺ ion is a nonmetal charge carrier with lower molar mass (18 mol g^-1) and smaller hydrated ionic size (3.31 Å) which results in excellent electrochemical properties. Furthermore, NH₄⁺ ion has a tetrahedral structure that has no preferred orientation as compared to spherical metal ions giving a different intercalation chemistry based on hydrogen bonding. These properties …

Physics-Based Crystal Plasticity Model For Predicting Microstructure Evolution And Dislocation Densities, Juyoung Jeong

LSU Doctoral Dissertations

This work presents three different studies investigating plastic deformation mechanisms in metals and alloys using crystal plasticity finite element (CPFE) modeling. The first study presents a new nonlocal crystal plasticity model for face-centered cubic single crystals under heterogeneous inelastic deformation. The model incorporates generalized constitutive relations that incorporate the thermally activated and drag mechanisms to cover different kinetics of viscoplastic flow in metals and describes the plastic flow and yielding of single-crystals using dislocation densities. The model is compared to micropillar compression experiments for copper single crystals and clarifies the complex microstructural evolution of dislocation densities in metals. The second …

First-Principles Molecular Dynamics Study Of Liquid Iron-Rich Alloys Under Conditions Of The Earth’S Core, Dipendra Banjara

LSU Doctoral Dissertations

In this dissertation, we report the results of the first-principles molecular dynamics (FPMD) simulations and data analysis on the thermodynamic, structural, and transport properties of iron-rich metallic liquids considering several light and heavy elements under wide ranges of pressure and temperature that are relevant to the earth’s core. Our simulations of pure liquid iron cover the pressure range from 0 GPa at 2000 K to 380 GPa at 7000 K perhaps representing the most extensive computational study to date. We studied four molten iron-rich alloys corresponding to 2.67 atom% of Ni, Co, Mo, and W at pressures up to 380 …

Characterization Of Electrophoretic Deposited Zinc Oxide Nanopartices For The Fabrication Of Next-Generation Nanoscale Electronic Applications, Fawwaz Abduh A. Hazzazi

LSU Doctoral Dissertations

Several reports state that it is crucial to analyze nanoscale semiconductor materials and devices with potential benefits to meet the need for next-generation nanoelectronics, bio, and nanosensors. The progress in the electronics field is as significant now, with modern technology constantly evolving and a greater focus on more efficient robust optoelectronic applications. This dissertation focuses on the study and examination of the practicality of Electrophoretic Deposition (EPD) of zinc oxide (ZnO) nanoparticles (NPs) for use in semiconductor applications.

The feasibility of several synthesized electrolytes, with and without surfactants and APTES surface functionalization, is discussed. The primary objective of this study …

A Deep Reinforcement Learning Approach With Prioritized Experience Replay And Importance Factor For Makespan Minimization In Manufacturing, Jose Napoleon Martinez

LSU Doctoral Dissertations

In this research, we investigated the application of deep reinforcement learning (DRL) to a common manufacturing scheduling optimization problem, max makespan minimization. In this application, tasks are scheduled to undergo processing in identical processing units (for instance, identical machines, machining centers, or cells). The optimization goal is to assign the jobs to be scheduled to units to minimize the maximum processing time (i.e., makespan) on any unit.

Machine learning methods have the potential to "learn" structures in the distribution of job times that could lead to improved optimization performance and time over traditional optimization methods, as well as to adapt …

Machine Learning Assisted Discovery Of Shape Memory Polymers And Their Thermomechanical Modeling, Cheng Yan

LSU Doctoral Dissertations

As a new class of smart materials, shape memory polymer (SMP) is gaining great attention in both academia and industry. One challenge is that the chemical space is huge, while the human intelligence is limited, so that discovery of new SMPs becomes more and more difficult. In this dissertation, by adopting a series of machine learning (ML) methods, two frameworks are established for discovering new thermoset shape memory polymers (TSMPs). Specifically, one of them is performed by a combination of four methods, i.e., the most recently proposed linear notation BigSMILES, supplementing existing dataset by reasonable approximation, a mixed dimension (1D …

Fatigue Damage Quantification And Life Estimation With Provision For Microstructure, Arash Pourbagheri Jirandehi

LSU Doctoral Dissertations

This dissertation provides methodologies for the quantification of different forms of fatigue damage by considering the role of microstructure. The laws of thermodynamics in conjunction with Finite Element Method (FEM) are utilized to devise thermodynamically-base frameworks for the estimation of cyclic damage in polycrystalline metals. Accordingly, a microstructure-sensitive platform for fatigue life estimation is introduced. The proposed framework is assessed for 3D printed metallic alloys at room and elevated temperatures. Further, it is used to analyze the fatigue performance difference between additively manufactured Inconel 718 in three print orientations. This research is of fundamental vital interest because it ensures that …

Degumming Of Hemp Fibers Using Combined Microwave Energy And Deep Eutectic Solvent, Bulbul Ahmed

LSU Master's Theses

Hemp is considered as one of the sustainable agricultural fiber materials. Degumming or surface modification of hemp bast is needed to produce single fibers for ensuing textile and industrial applications. The traditional degumming process necessitates a high amount of alkali, which causes detrimental environmental pollution. This study offers a new method to degum hemp fibers with reduced use of harmful alkali and precious water resources. In this work, hemp bast fibers were degummed by using combined microwave energy and deep eutectic solvent (DES). The properties of hemp fibers manufactured by this method were investigated and compared with the traditional alkali …

An Improved Earned Value Management Method Integrating Quality And Safety, Brian Briggs

LSU Doctoral Dissertations

The construction industry invests significant time and money to improve quality and safety while reducing cost and schedule impacts. The industry has a sincere desire to improve construction project management methods to improve efficiency. Historically, quality and safety underperformances result from undermanaged quality control and safety activities. The cost and schedule impacts associated with poor quality work have always had an impact on construction operations. The unprecedented challenges and uncertainties of COVID-19 highlighted the need to improve the Earned Value Management (EVM) method within construction to reflect these quality and safety activities. The central goal of this dissertation is to …

Performance Evaluation Of Gas Lift Valves Using Numerical Simulation, Felipe Simoes Maciel

LSU Master's Theses

This work aimed to assess the performance of two numerical simulation methods to replicate flow capacity test (FCT) results and predict the flow coefficient (Cv) and critical pressure ratio (Rcp) of gas lift valves (GLVs). FCT's use a modified GLV with an adjustable stem positioning system to obtain pressure as a function of flow rate for different stem positions to calculate Cv and Rcp. Therefore, this study used both a one-dimensional (1D) mechanistic model and computational fluid dynamics (CFD) to predict the same variable from the FCT without tests using modified GLVs. This methodology demonstrates accurate results, which were compared …

Atomistic Thermo-Mechanical Description Of The Deformation Behavior, Scaling Laws, And Constitutive Modeling Of Nanoporous Gold, Mohammed Hassan Yousef Saffarini

LSU Doctoral Dissertations

Metallic foams, or nanoporous (NP) metals as it is widely referred to in literature, with ligament sizes up to a few tens of nm show exceptional mechanical properties such as high strength and stiffness per weight ratio under different loading scenarios due to their high surface area to solid volume ratio. Therefore, they can be utilized in a wide range of applications making them of great interest to researchers. While their elasticity and yield strength have been the subject of several studies, very limited attention was given to the effect of size, strain rate, and temperature on the material plastic …

Modeling Hydraulic Fracturing Initiation And Propagation In Porous Rock Formationsl, Chang Huang

LSU Doctoral Dissertations

Hydraulic fracturing has long been introduced to the oil and gas industry since the early nineteenth century for both reservoir characterization and reservoir stimulation. Despite the progress made in the last two decades, many challenges still have not been tackled regarding not only the propagation problem but also the initiation problem due to its complexity. The dissertation is divided into two stages, i.e., before and after fracture initiation. The first stage of the research aimed at improving the accuracy in solving the poro-mechanical response of wellbore during fluid injection before a tensile fracture occurs, which is crucial to determine the …

An Improved Foam Modeling Technique And Its Application To Petroleum Drilling And Production Practice, Yanfang Wang

LSU Doctoral Dissertations

Foam is one of the most common used multiphase fluid in Underbalanced Drilling (UBD) and Managed Pressure Drilling (MPD). Because of its low density, high capacity of lifting and carrying cuttings, low cost and compatibility with formations, foam has become more superior than the conventional drilling mud when depleted reservoir pressure, severe lost circulation, or unstable borehole are encountered. In general, the success of foam applications rely on the understanding of the fundamentals of foam rheology in downhole conditions.

Foam rheology has been studied for decades. Conventional foam rheological models such as Power Law, Bingham Plastic, Herschel-Bulkley to explain foam …

Development Of Reduced Order Models Using Reservoir Simulation And Physics Informed Machine Learning Techniques, Mark V. Behl Jr

LSU Master's Theses

Reservoir simulation is the industry standard for prediction and characterization of processes in the subsurface. However, simulation is computationally expensive and time consuming. This study explores reduced order models (ROMs) as an appropriate alternative. ROMs that use neural networks effectively capture nonlinear dependencies, and only require available operational data as inputs. Neural networks are a black box and difficult to interpret, however. Physics informed neural networks (PINNs) provide a potential solution to these shortcomings, but have not yet been applied extensively in petroleum engineering.

A mature black-oil simulation model from Volve public data release was used to generate training data …

Adsorption And Reconfiguration Of Amphiphiles At Silica-Water Interfaces: Role Of Electrostatic Interactions, Van Der Waals Forces And Hydrogen Bonds, Yao Wu

LSU Doctoral Dissertations

The ability to explore and predict metastable structures of hybrid self-assemblies is of central importance for the next generation of advanced materials with novel properties. As compared to their thermodynamically stable forms, the kinetically stabilized materials show improved functionality potentially over their stable counterparts. The self-assembly processes usually originate from weak intermolecular interactions, involving a dynamic competition between attractive and repulsive interactions. These weak forces, including van der Waals (vdW), electrostatic interaction and the hydrogen bonding (H-bonding), can be tuned by external stimuli, e.g., confinement, temperature and ionization, and consequently driving hybrid materials into different configurations. It is challenging to …

Centrifugal Microfluidic Platform For Solid-Phase-Extraction (Spe) And Fluorescence Detection Applications, Yong Zhang

LSU Doctoral Dissertations

Solid phase extraction (SPE) is a widely used method to separate and concentrate the target molecules in liquid mixture. Traditional SPE has to be conducted in the laboratory with professional equipment and skilled operators. The microfluidic and 3D printing technology have opened up the opportunity in developing miniaturized automatic instruments. The main contribution of this research is to integrate the SPE process on a novel centrifugal platform. Various valves are applied on the platform to help control the aqueous sample and reagents in the cartridge.

First, a centrifugal microfluidic platform was built for automatically detecting trace oil pollution in water. …

A Modelling Study For Smart Pigging Technique For Pipeline Leak Detection, Caitlyn Judith Thiberville

LSU Master's Theses

Although leak incidents continue, a pipeline remains the most reliable mode of transportation within the oil and gas industry. It becomes even more important today because the projection for new pipelines is expected to increase by 1 billion BOE through 2035. In addition, increasing number and length of subsea tiebacks face new challenges in term of data acquisition, monitoring, analysis, and remedial actions. Passive leak-detection methods commonly used in the industry have been successful with some limitations in that they often cannot detect small leaks and seeps. In addition to a thorough review of related topics, this study investigates how …

Factors Influencing Retirement Decision Making For Louisiana State Government Employees, Osama A. Amous

LSU Doctoral Dissertations

ABSTRACT

Public pension members continually face factors affecting their decision to retire in the changing American society. Workers are living longer and need more medical care with better retirement benefits. For Louisiana public employees specifically, no prior studies have examined the factors affecting workers’ decision to retire nor evaluated the factors impacting workers’ decision.

This multiphase study aimed to identify factors and evaluate the decision-making process that enables Louisianans to retire happily and satisfied with a guaranteed income, and to examine millennials’ decision-making process. In the initial phase, ten active and retired male and female participants answered questions in-person, leading …

Relating Individual Characteristics And Task Complexity To Performance Effectiveness In Individual And Collaborative Problem Solving, Kaveh Sheikhrezaei

LSU Doctoral Dissertations

The objective of this research is to examine the variables that influence performance effectiveness on individual and collaborative problem solving. The last few years have seen renewed interest in how team member personal characteristics and team composition characteristics impact team effectiveness.

Even with a growing quantity of organizations performing jobs by using groups, little is understood how people included in a team impact intragroup interaction and results. Most research investigates group’s performance based on a single characteristic which causes much confusion and contradictory results of the variables that impact overall group performance. Most research typically does not analyze the composition …

Artificial Intelligence Based Wrist Fracture Classification, Dineep Thomas

LSU Master's Theses

The problem of predicting wrist fractures from X-rays using Artificial Intelligence (AI) methods is addressed. Wrist fractures are the most commonly misdiagnosed fractures because of the complex anatomical structure of the wrist bone which includes several different bones. This research provides a predictive solution to automate the process of wrist fracture classifications and outlines a visualization technique to identify the probable location of the fractured region on the X-rays. This thesis describes a deep learning based approach for wrist fracture classification. Deep convolutional neural network (CNN) based models have been used for wrist fracture classification by combining different optimization techniques. …

Costs And Benefits Of Flood Mitigation In Louisiana, Arash Taghi Nezhad Bilandi

LSU Doctoral Dissertations

Assessing the costs and benefits of hazard mitigation efforts is an essential component of disaster management, planning, and resilience assessment. These calculations are particularly important in locations vulnerable to multiple hazards with high frequencies, such as coastal Louisiana. This study aims to provide an improved understanding of the costs and benefits of flood mitigation efforts in Louisiana funded by federal government grants between 2005 and 2015. Project data provided by the Governor’s Office of Homeland Security and Emergency Preparedness (GOHSEP) were summarized and missing values were imputed using robust statistical approaches. Elevation project cost was investigated for prediction by statistical …

Simplified Approach For Structural Evaluation Of Flexible Pavements At The Network Level, Mena Souliman, Stefan Romanoschi, Samer Dessouky

Publications

Currently, there are few available simple procedures to identify structurally weak pavement sections utilizing Falling Weight Deflectometer (FWD) data at the network level (e.g., city, state or province). A simple method is required to determine the structural condition of pavement sections that can be directly implemented and automated in current pavement databases. The objective of this research study is to develop a simple analysis method to determine the structural condition of pavement sections utilizing the currently available non-destructive testing (NDT) deflection measurement devices at the network level that can be directly implemented and automated in the database of a typical …

Modeling Sulfate Attack In Modern Concrete For Building Sustainable And Resilient Infrastructure, Zachary Grasley

Publications

External sulfate attack is a complex phenomenon and is manifested in the form of large expansion, cracking, and spalling depending on the exposure solution and material constituent properties. Several models were developed in the past to demonstrate sulfate attack mechanisms that account for the diffusion of sulfate ions into the porous concrete and the successive deformation triggered by the chemical reaction and precipitation of expansive agents. However, none of these models accounts for the effect of the migration of solvent water from the low solute concentration solution to high solute concentration solution driven by the osmotic pressure. Osmotic pressure is …