Digital Commons Network^™

Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization, Gerald Kelechi Ekechukwu

LSU Doctoral Dissertations

In the oil and gas industry, distributed fiber optics sensing (DFOS) has the potential to revolutionize well and reservoir surveillance applications. Using fiber optic sensors is becoming increasingly common because of its chemically passive and non-magnetic interference properties, the possibility of flexible installations that could be behind the casing, on the tubing, or run on wireline, as well as the potential for densely distributed measurements along the entire length of the fiber. The main objectives of my research are to develop and demonstrate novel signal processing and machine learning computational techniques and workflows on DFOS data for a variety of …

Numerical Investigation Of Heat Generation And Accumulation Contributing To Elevated Temperature In Msw Landfills, Alborz Fathinezhad

LSU Doctoral Dissertations

Landfills are complex geostructures which contains organic and inorganic municipal, and in some cases industrial, wastes and are expected to remain operational for long times. Due to the complex nature of physical, chemical, biological, and thermal reactions that carry on within the depths of a landfill, unexpected incidents such as elevated temperatures could become inevitable. While uncommon to happen, elevated temperatures cause health and environmental issues such as odors, rapid settlements, slope instabilities. In addition, elevated temperatures can negatively impact engineered components in composite bottom liners, cover systems, leachate collection, and gas extraction and recovery systems.

Air intrusion into municipal …

Sers Platform For Single Fiber Endoscopic Probes, Debsmita Biswas

LSU Doctoral Dissertations

Molecular detection techniques have huge potential in clinical environments. In addition to many other molecular detection techniques, endoscopic Raman spectroscopy has great ability in terms of minimal invasiveness and real-time spectra acquisition. However, Raman Effect is low in sensitivity, limiting the application. Surface-Enhanced Raman Scattering (SERS), addresses this limitation. SERS brings rough nano-metallic surfaces in contact with specimen molecules which enormously enhances Raman signals. This provides Raman spectroscopy with immense capabilities for diverse fields of applications.

Generally, in clinical probe applications, the spectrometer is brought near the target molecules for detection. Typically, optical fibers are used to couple spectrometers to …

Toward A Safer Transportation System For Senior Road Users, Saba Doulabi

LSU Doctoral Dissertations

Senior pedestrians and drivers (65 years and older) are among the most vulnerable road users. As the population of seniors rise, concerns regarding older adults' traffic safety are growing. The advantages of using autonomous vehicles, innovative vehicle technologies, and active transportation are becoming more widely recognized to improve seniors' mobility and safety. This behooves researchers to further investigate senior road users’ safety challenges and countermeasures. This study contributes to the literature by achieving two main goals. First, to explore contributing factors affecting the safety of older pedestrians and drivers in the current transportation system. Second, to examine seniors’ perceptions, preferences, …

Compilation Optimizations To Enhance Resilience Of Big Data Programs And Quantum Processors, Travis D. Lecompte

LSU Doctoral Dissertations

Modern computers can experience a variety of transient errors due to the surrounding environment, known as soft faults. Although the frequency of these faults is low enough to not be noticeable on personal computers, they become a considerable concern during large-scale distributed computations or systems in more vulnerable environments like satellites. These faults occur as a bit flip of some value in a register, operation, or memory during execution. They surface as either program crashes, hangs, or silent data corruption (SDC), each of which can waste time, money, and resources. Hardware methods, such as shielding or error correcting memory (ECM), …

Spam Detection Using Machine Learning And Deep Learning, Olubodunde Agboola

LSU Doctoral Dissertations

Text messages are essential these days; however, spam texts have contributed negatively to the success of this communication mode. The compromised authenticity of such messages has given rise to several security breaches. Using spam messages, malicious links have been sent to either harm the system or obtain information detrimental to the user. Spam SMS messages as well as emails have been used as media for attacks such as masquerading and smishing ( a phishing attack through text messaging), and this has threatened both the user and service providers. Therefore, given the waves of attacks, the need to identify and remove …

A Field-Deployable Quartz Crystal Microbalance System For Gas Detection, Jongyoon Park

LSU Doctoral Dissertations

Quartz crystal microbalance (QCM) has been widely studied as a mass sensing technique in laboratory environments and has shown a wide range of industrial applications such as food quality control, various forms of chemical detection, and biomolecular recognition under gas phase as well as liquid phase media. The construction of multi-sensor arrays combined with special sensor coatings enables multiple analyte detections and discrimination of multi-analyte along with statistical analysis. Despite the great sensing capabilities of QCM and growing interest in practical applications beyond the laboratory setup, most QCM studies are still performed in laboratory settings with benchtop QCM instruments. Therefore, …

Novel Texture-Based Probabilistic Object Recognition And Tracking Techniques For Food Intake Analysis And Traffic Monitoring, Robert Jacob Dibiano

LSU Doctoral Dissertations

More complex image understanding algorithms are increasingly practical in a host of emerging applications. Object tracking has value in surveillance and data farming; and object recognition has applications in surveillance, data management, and industrial automation. In this work we introduce an object recognition application in automated nutritional intake analysis and a tracking application intended for surveillance in low quality videos. Automated food recognition is useful for personal health applications as well as nutritional studies used to improve public health or inform lawmakers. We introduce a complete, end-to-end system for automated food intake measurement. Images taken by a digital camera are …

Applications Of Temperature Transient Analysis For Reservoir Surveillance, Refaat Galal Aboelfotoh Hashish

LSU Doctoral Dissertations

Reservoir monitoring is a key factor in the management of oil and gas resources. With the recent developments of permanent downhole temperature monitoring tools such as Fiber-Optic Distributed Temperature Sensing (FO-DTS), temperature transient analysis has evolved as a new alternative for reservoir monitoring. In this work, different techniques of temperature data analysis are presented for monitoring and characterization of hydrocarbon and geologic carbon storage (GCS) reservoirs. The objective of this study is to present new approaches that enable monitoring injection profile through vertical and horizontal injection wells using temperature warmback analysis. Application of temperature warmback analysis is also extended for …

Incorporating Geopolymer Binders To Fully Utilize Recycled Concrete Aggregates, Matthew Upshaw

LSU Doctoral Dissertations

This study aims to develop a geopolymer concrete binder that will yield desirable strength and durability characteristics when applied to recycled aggregate concrete. In order to achieve this, a geopolymer binder consisting of a metakaolin-silica fume aluminosilicate source material blend activated by potassium-based alkaline solutions is developed and used in place of ordinary Portland cement (OPC) with four different levels of recycled aggregate replacement ratios. The properties of these concretes were analyzed and compared with the properties of OPC concretes produced with the same replacement ratio levels. The results showed that the geopolymer recycled aggregate concrete (GRAC) achieved greater than …

Design Tunneling Transistor And Schottky Junction Solar Cell Using Van Der Waals Semiconductor Heterostructure, Md Azmot Ullah Khan

LSU Doctoral Dissertations

Transition metal di-chalcogenide (TMDC) materials, being semiconductor in nature, offer Two-dimensional (2D) materials such as graphene and molybdenum disulfide (MoS₂) possess unique and unusual properties that are particularly applicable to nanoelectronics and photovoltaic devices. In this dissertation, four different projects have been done that encompass the implementation of these materials to improve the performance of future transistors and Schottky junction solar cells. In chapter 2, an analytical current transport model of a dual gate tunnel field-effect transistor (TFET) is developed by utilizing the principle of band-to-band tunneling (BTBT) and MoS₂ as the channel material. Later, using this …

Bioremediation Of Petroleum-Based Contaminants By Alkane-Degrading Bacterium Alcanivorax Borkumensis, Amber Julaine Pete

LSU Doctoral Dissertations

The world’s dependence on petroleum hydrocarbons has led to significant environmental implications. For example, oil spills cause lasting environmental damage, and the increase of plastics in the marine environment has been growing, specifically, microplastics that can be difficult to detect due to their small size. Petroleum hydrocarbons occur naturally in nearly all marine environments, which has allowed hundreds of microorganisms to evolve to utilize these hydrocarbons as their primary energy source. These microbes are classified as hydrocarbonoclastic and are utilized to remove spilled oil biodegradation. Over the last ten years, progress has been made in the biodegradation of oil spills …

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 Drift-Flux Model For Upward Two-Phase In Pipes With High Velocity Flows, Woochan Lee

LSU Doctoral Dissertations

This study proposes the evaluation and development of a drift-flux model for upward two-phase high-velocity flow in large diameter pipes. A case where the proposed model is applicable is WCD (Worst-Case-Discharge) calculations for offshore wells. WCD assumes relatively larger pipe diameters and higher flow rates than the flow experiments at laboratory conditions utilized to validate and develop most of the flow models available in the literature.

Most of the two-phase flow models describe flow regime transitions as discrete processes by assigning the required void fraction or velocity for each flow regime transition. Therefore, for each flow regime, flow-regime-dependent correlations or …

Efficient Low Dimensional Representation Of Vector Gaussian Distributions, Md Mahmudul Hasan

LSU Doctoral Dissertations

This dissertation seeks to find optimal graphical tree model for low dimensional representation of vector Gaussian distributions. For a special case we assumed that the population co-variance matrix $\Sigma_x$ has an additional latent graphical constraint, namely, a latent star topology. We have found the Constrained Minimum Determinant Factor Analysis (CMDFA) and Constrained Minimum Trace Factor Analysis (CMTFA) decompositions of this special $\Sigma_x$ in connection with the operational meanings of the respective solutions. Characterizing the CMDFA solution of special $\Sigma_x$, according to the second interpretation of Wyner's common information, is equivalent to solving the source coding problem of finding the minimum …

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 …

Assembly Of Nanostructures At Solid-Liquid And Liquid-Air Interfaces, Yingzhen Ma

LSU Doctoral Dissertations

Molecular and nanoscale colloids such as surfactant, fatty acid and metallic nanoparticles are widely used in numerous applications such as detergents, biomedicine, and catalyst. The assemblies of these colloids show different morphological behavior in aqueous solution due to the wide range of intermolecular interactions such as hydrogen bonding, van der Waals, and electrostatics. The morphology of these assemblies can be changed by environmental factors including temperature, ionic strength, and salinity. However, the guidance to direct assembled state of colloidal assemblies at heterogenous interfaces under various external stimuli remains poorly understand. In this Ph.D. dissertation, we show the adsorption and reconfiguration …

Numerical Modeling Of Bulk Sediment Deposition And Scour In The Lower Mississippie River Physical Model, Ronald Joseph Rodi

LSU Doctoral Dissertations

Land loss restoration along the southeast Louisiana coast relies on the replenishment of sand from the sediment of the Mississippi River. To further the understanding of sediment transport and hydraulic characteristics of the lowermost segment of the river, the Louisiana Coastal Protection and Restoration Authority (CPRA) funded construction of the Lower Mississippi River Physical Model (LMRPM). This distorted-scale, movable bed model encompasses the lowermost 193-mile reach of the river, including from Donaldsonville, Louisiana to the Gulf of Mexico the Bonnet Carre Spillway and planned river sediment diversions.

Designed to replicate the prototypical river hydraulics and bulk bedload (sand) transport, scaled …

Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector

LSU Doctoral Dissertations

In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical …

Novel Platforms For Large-Scale Adherent Culture Of Mammalian Cells, Ashkan Yekrangsafakar

LSU Doctoral Dissertations

With recent advances in biotechnology, there is a strong and urgent need for robust platforms to culture mammalian cells on a large scale to produce biopharmaceuticals. To this end, various bioreactors have been developed over the past decades, but their capacity and efficiency are often limited by insufficient mass transfer rate and excessive shear stress. In this work, multiple novel bioreactors for the large-scale adherent culture of anchorage-dependent cells were developed.

Hollow MicroCarriers (HMC) was developed as an alternative solution for the microcarrier-based culture system in a stirred-tank bioreactor. In the conventional microcarrier technique, cells are exposed to the harmful …

A New Generation Of Open-Graded Friction Course For Enhanced Durability And Functionality, Hossam Abohamer

LSU Doctoral Dissertations

This study aims at (1) enhancing Open Graded Friction Course (OGFC) mixes durability using additives and other by-products; (2) investigating the impacts of selected factors on OGFC pavements seepage characteristics; (3) developing a quantitative tool to model the deterioration in OGFC pavements functional performance; and (4) developing new guidelines of Air Void (AV) content for OGFC for optimum functionality and durability. For the durability objective, eight mixes were prepared with a PG 76-22 binder and two sources of aggregate (i.e., # 78 limestone and # 67 sandstone). Three Warm Mix Additives (WMA), one by-product (i.e., crumb rubber [CR]), and two …

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 …

Investigation Of Groundwater Depletion And Leveel Underseepage With Unstructured-Grid Modeling Approach, Ye-Hong Chen

LSU Doctoral Dissertations

Unstructured grid is a tessellation of geometric shapes in irregular patterns that provides flexibility in grid design for groundwater modeling. However, groundwater modeling is mostly developed with uniform grid tessellation and layer, which could simplify model structure or cause expensive computational costs in high-resolution simulations. Unstructured grid incorporates non-uniform horizontal and non-uniform vertical discretizations providing the capability to replicate complex hydrostratigraphy, capture geologic features that are crucial for groundwater flow simulation, and reduce computational costs while maintaining a high resolution for areas of interest. This study contains three parts to investigate unstructured-grid approach on constructing high-fidelity groundwater models, comparisons with …

Synthesis Of Thiol-Acrylate Hydrogels For 3d Cell Culture And Microfluidic Applications, Anowar Hossain Khan

LSU Doctoral Dissertations

Globally cell culture is an $18.98 billion industry as of 2020, with an 11.6 percent annual growth rate. Drug discovery has an estimated worth of $69.8 billion in 2020 and is predicted to grow to $110.4 billion by 2025. Three-dimensional (3D) cell culture of cancer cells is one of the rapidly growing felids since it better recapitulates in vivo conditions compared to two-dimensional (2D) models. However, it is challenging to grow 3D tumor spheroids outside the body, and some of the existing technology can generate these spheroids outside the human body but poorly mimic in vivo tumor models. Therefore, there …

Tuning Electrochemical Interactions And Polymer Electrolyte Interfaces For Enhanced Organic Acid Separations Using Electrodeionization, Matthew Leo Jordan

LSU Doctoral Dissertations

Chemical separations are critical processes for chemical and industrial plants to purify and isolate products however current separation technologies, such as distillation, rely on energy intensive processes. Electrochemical separation processes, such as electrodialysis and electrodeionization, are an energy efficient alternative that are emerging as an alternative for thermal-based separations. Organic acids are weakly ionizable species and susceptible for purification from process streams using electrochemical processes. Recently the fermentation route has garnered greater attention as a means for producing value-added chemicals, such as organic acids, from a renewable feedstock and aiding the circular economy. Some of the challenges electrodialysis faces for …

Phase Noise Analyses And Measurements In The Hybrid Memristor-Cmos Phase-Locked Loop Design And Devices Beyond Bulk Cmos, Naheem Olakunle Adesina

LSU Doctoral Dissertations

Phase-locked loop (PLLs) has been widely used in analog or mixed-signal integrated circuits. Since there is an increasing market for low noise and high speed devices, PLLs are being employed in communications. In this dissertation, we investigated phase noise, tuning range, jitter, and power performances in different architectures of PLL designs. More energy efficient devices such as memristor, graphene, transition metal di-chalcogenide (TMDC) materials and their respective transistors are introduced in the design phase-locked loop.

Subsequently, we modeled phase noise of a CMOS phase-locked loop from the superposition of noises from its building blocks which comprises of a voltage-controlled oscillator, …

Efficient Information Retrieval For Software Bug Localization, Saket Khatiwada

LSU Doctoral Dissertations

Software systems are often shipped with defects. When a bug is reported, developers use the information available in the associated report to locate source code fragments that need to be modified to fix the bug. However, as software systems evolve in size and complexity, bug localization can become a tedious and time-consuming process. Contemporary bug localization tools utilize Information Retrieval (IR) methods for automated support to minimize the manual effort. IR methods exploit the textual content of bug reports to capture and rank relevant buggy source files. However, for an IR-based bug localization tool to be useful, it must achieve …

Computational Study Of The Reactions Of Heteroatomic Compounds On Ceo2, Suman Bhasker Ranganath

LSU Doctoral Dissertations

The mechanisms of ambient-temperature reactions of heteroatomic compounds catalyzed by ceria (CeO₂), an archetypical reducible oxide, for enzyme mimetics, environmental protection, and chemical synthesis are investigated in this dissertation using theoretical methods. CeO₂ is modeled with thermodynamically stable low-index surfaces exposed by commonly studied ceria thin films and nano particles. To understand phosphatase-like dephosphorylation activity, stable adsorption states and surface reactions of model phosphates are examined. Binding of the central P-atom to surface lattice oxygen (O_latt) supplemented by phosphoryl O-Ce interaction is the only stable adsorption state for the un-dissociated molecule. Deprotonation of phosphate monoesters, …

Use Of Halide Radicals In Water Treatment, Madhusudan Kamat

LSU Doctoral Dissertations

The increasing population and a reduction in freshwater resources has made the reuse of water imperative [1-3]. Advanced oxidation processes (AOPs) enable the safe reuse of wastewater through the removal of persistent pollutants. The highly reactive nature of reactive species, like hydroxyl radicals is limited by their reactivity with ubiquitous compounds like dissolved organic matter (DOM)[4, 5]. The use of halide radicals can help improve the efficiency of UV-based AOPs.

This thesis investigates the mechanism of halide radicals in three different systems: a) the use of iodine radicals in functionalized fullerenes b) the use of UV/chlorine as an advanced oxidation …

Interpretable And Anti-Bias Machine Learning Models For Human Event Sequence Data, Zihan Zhou

LSU Doctoral Dissertations

Growing volumes and varieties of human event sequence data are available in many applications such as recommender systems, social network, medical diagnosis, and predictive policing. Human event sequence data is usually clustered and exhibits self-exciting properties. Machine learning models especially deep neural network models have shown great potential in improving the prediction accuracy of future events. However, current approaches still suffer from several drawbacks such as model transparency, unfair prediction and the poor prediction accuracy due to data sparsity and bias. Another issue in modeling human event data is that data collected from real word is usually incomplete, and even …