Engineering Commons^™

Modeling And Design Optimization For Membrane Filters, Yixuan Sun

Dissertations

Membrane filtration is widely used in many applications, ranging from industrial processes to everyday living activities. With growing interest from both industrial and academic sectors in understanding the various types of filtration processes in use, and in improving filter performance, the past few decades have seen significant research activity in this area. Experimental studies can be very valuable, but are expensive and time-consuming, therefore theoretical studies offer potential as a cost-effective and predictive way to improve on current filter designs. In this work, mathematical models, derived from first principles and simplified using asymptotic analysis, are proposed for: (1) pleated membrane …

Shale Softening Based On Pore Network And Laboratory Investigations, Di Zhang

Dissertations

This dissertation consists of two major parts: Firstly, experimental investigation of four major shale softening mechanisms and quantifications of structural parameters. Secondly, numerical simulations of nano-scale flow behaviors using the previous experiments determined parameters based on modified pore network modeling.

Hydraulic fracturing is widely applied to economical gas production from shale reservoirs. Still, the gradual swelling of the clay micro/nano-pores due to retained fluid from hydraulic fracturing causes a gradual reduction of gas production. Four different gas-bearing shale samples are investigated to quantify the expected shale swelling due to hydraulic fracturing. These shale samples are subject to heated deionized (DI) …

Data-Driven Learning For Robot Physical Intelligence, Leidi Zhao

Dissertations

The physical intelligence, which emphasizes physical capabilities such as dexterous manipulation and dynamic mobility, is essential for robots to physically coexist with humans. Much research on robot physical intelligence has achieved success on hyper robot motor capabilities, but mostly through heavily case-specific engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous manner, robot learning from human demonstration (LfD) has achieved great progress, but still has limitations handling dynamic skills and compound actions. In this dissertation, a composite learning scheme which goes beyond LfD and integrates robot learning from human definition, demonstration, and evaluation is proposed. This method tackles …

Feedstock Powders For Reactive Structural Materials, Daniel Hastings

Dissertations

Metals as fuels have higher energy density per unit mass or volume compared to any hydrocarbon. At the same time, metals are common structural materials. Exploring metals as reactive structural materials may combine their high energy density with attractive mechanical properties. Preparing such materials, however, is challenging. Requirements that need to be met for applications include density, strength, and stability enabling the component to sustain the structure during its desired operation; added requirements are the amount and rate of the energy release upon impact or shock. Powder technology and additive manufacturing are approaches considered for design of reactive structural materials. …

Analysis Of Container Throughput: Demand Forecast And Seaport Competitiveness Assessment, Hussain Talat Sulaimani

Dissertations

Seaports play a crucial role in the container industry, where they act as important nodes in the transport chain to facilitate international trade. In a competitive market, port capacity plays a significant role in defining its competitive position to attract demand and avoid congestion. Failing to provide suitable capacity results in the loss of market share. Therefore, port decision-makers face the challenge of maintaining and developing suitable port facilities to provide efficient services to port users. One of the aspects that decision-makers consider in the planning and development process is analyzing container demand. The analysis of container demand can be …

Towards Understanding The Role Of Central Processing In Release From Masking, Nima Alamatsaz

Dissertations

People with normal hearing have the ability to listen to a desired target sound while filtering out unwanted sounds in the background. However, most patients with hearing impairment struggle in noisy environments, a perceptual deficit which current hearing aids and cochlear implants cannot resolve. Even though peripheral dysfunction of the ears undoubtedly contribute to this deficit, surmounting evidence has implicated central processing in the inability to detect sounds in background noise. Therefore, it is essential to better understand the underlying neural mechanisms by which target sounds are dissociated from competing maskers. This research focuses on two phenomena that help suppress …

Constructive Solution Methodologies To The Capacitated Newsvendor Problem And Surrogate Extension, Pinyuan Shan

Dissertations

The newsvendor problem is a single-period stochastic model used to determine the order quantity of perishable product that maximizes/minimizes the profit/cost of the vendor under uncertain demand. The goal is to fmd an initial order quantity that can offset the impact of backlog or shortage caused by mismatch between the procurement amount and uncertain demand. If there are multiple products and substitution between them is feasible, overstocking and understocking can be further reduced and hence, the vendor's overall profit is improved compared to the standard problem. When there are one or more resource constraints, such as budget, volume or weight, …

Towards Quality By Design (Qbd) Of Pharmaceutical Oral Films Loaded With Poorly Watersoluble Drugs, Eylul Cetindag

Dissertations

Oral films are an emerging drug delivery dosage form with numerous advantages such as ease of handling, the possibility to circumvent the first-pass metabolism, better patient compliance, capability for continuous manufacturing, and as a platform for personalized medicine. As films are different from other final dosages by their dimensions and their matrix form, further research is required to better understand the impact of excipient and drug on product performance to assure a consistent and good quality product. Therefore, this dissertation aims to contribute towards the processability and manufacturability of films by examining the impact of the materials and processes. First, …

Learning Of Radar System For Target Detection, Wei Jiang

Dissertations

In this dissertation, the problem of data-driven joint design of transmitted waveform and detector in a radar system is addressed. Two novel learning-based approaches to waveform and detector design are proposed based on end-to-end training of the radar system. The first approach consists of alternating supervised training of the detector for a fixed waveform and reinforcement learning of the transmitter for a fixed detector. In the second approach, the transmitter and detector are trained simultaneously. Various operational waveform constraints, such as peak-to-average-power ratio (PAR) and spectral compatibility, are incorporated into the design. Unlike traditional radar design methods that rely on …

Exploring Fused Deposition Modeling (Fdm) Three-Dimensional Printing Tablet Design Options For Pharmaceutical Dosage Forms, Guluzar Gorkem Buyukgoz

Dissertations

This dissertation examines the use of Fused Deposition Modeling (FDM) based three-dimensional (3D) printing approach for developing patient-specific dosage forms and addressing related technical challenges in such drug delivery systems. The first main objective is to explore pharmaceutical tablet design options using novel FDM 3D printing technology as the drug delivery platform such that drug form and tablet properties are tailored by considering patient age-specific formulations and dissolution control. Of the five different design options, two proposed options meet the main objective of providing similar drug release, whereas the popular option of fixed drug concentration but differing tablet size could …

Temporal Evolution Of Structure And Function In The Periphery And Central Auditory Systems With Mild Blast Induced Tinnitus In Rat Animal Models, Ningning Shao

Dissertations

Exposure to blast causes debilitating trauma including tinnitus among soldiers and civilians (Cave et al., 2007; Remenschneider et al., 2014; Singh et al., 2016). Tinnitus is a constant ringing noise perception without external acoustic event; it affects sleep, concentration, behavior, leading to suicidal tendencies (Swan et al., 2017). Though blast induced tinnitus has been studied, structural and functional dysfunctions along auditory systems have not been systematically studied. It was hypothesized in this work that blast causes tinnitus even while the ears are mechanically protected, and the damage occurred in both central and peripheral auditory systems, which contributed to increased anxiety …

Alcohol As A Catalyst For Hiv-Associated Neuroinflammation And Tbi-Induced Iron Toxicity, Agnieszka Agas

Dissertations

Alcohol has long been considered an exacerbator of diseases, disorders, and injuries as well as many of the accompanying symptoms. As an alternative approach, this dissertation explores alcohol as a catalyst for two different human disease conditions, human immunodeficiency virus (HIV)-associated neuroinflammation and traumatic brain injury (TBI)-induced iron toxicity. In HIV-1 infection, this dissertation presents a novel anti-viral drug, called Drug-S, for a possible inhibition and treatment of HIV-1 disease progression.

The first aim explores the influence of alcohol with HIV-associated neuroinflammation on macrophage migration across an in vitro model of the blood brain barrier. There is a gap in …

Ensemble Data Fitting For Bathymetric Models Informed By Nominal Data, Samantha Zambo

Dissertations

Due to the difficulty and expense of collecting bathymetric data, modeling is the primary tool to produce detailed maps of the ocean floor. Current modeling practices typically utilize only one interpolator; the industry standard is splines-in-tension.

In this dissertation we introduce a new nominal-informed ensemble interpolator designed to improve modeling accuracy in regions of sparse data. The method is guided by a priori domain knowledge provided by artificially intelligent classifiers. We recast such geomorphological classifications, such as ‘seamount’ or ‘ridge’, as nominal data which we utilize as foundational shapes in an expanded ordinary least squares regression-based algorithm. To our knowledge …

Intelligent System For Laparoscopic Surgery Suturing Skill Assessment, Mohammed Yasser Al-Gailani

Dissertations

In laparoscopic surgery, which is also referred to as minimally invasive surgery (MIS), surgeons carry out surgical procedures with the assistance of a video camera and several surgical instruments. Laparoscopic surgeons should possess excellent eye-hand coordination capabilities, strong cognitive knowledge, case and problem management, and manual dexterity skills. Such skills can be acquired through simulation using a basic, low-fidelity setup, such as the surgical box-trainer. General surgeons must pass a set of tests on a Fundamentals of Laparoscopic Surgery (FLS) Trainer device.

One pivotal skill for a successful operation is developing a sense of the applied forces on the tissue …

Performance Evaluation Of Transportation Systems For Sustainability And Smart-Growth Of Cities: An Integrated Assessment Of Health Impacts, Ahmad Feizi

Dissertations

The performance of transportation systems is a significant component that influences the quality of life. The performance evaluation refers to a process of determining how well transportation systems perform regarding their intended goals and objectives. The advancement of information and communication technology and the integration between transportation systems and advanced technologies have directed more attention to the concept of smart cities. Smart cities are constituted of several interrelated components. Therefore, this offers comprehensive and integrated frameworks to evaluate the transportation performance and understanding of multifaceted interactions between the components from a transportation engineering perspective in four sections.

In the first …

Epoxy Curing: Paramount Or Trivial? A Cure Path Dependent Inquiry, Jared Bates

Dissertations

The presented research delves into epoxy network formation corroborating reactant concentration profiles and physical property development throughout cure, providing an experimental basis for burgeoning molecular dynamics and coarse-grained simulation methodologies. Herein, three primary subjects were investigated: the first two examine neat and toughened epoxide/amine network formation with respect to various cure profiles aimed at altering reaction pathways, the final chapter intends to augment traditionally utilized activation energy (E_a) methodologies.

Neat and toughened epoxide/amine slurries were monitored in-situ throughout cure via near infrared (NIR) spectroscopy and rheological techniques. Functional group conversion and moduli development were related with specific attention …

Development And Characterization Of Sustainable Novel Aluminum Metal Matrix Composites, John Victor Christy

Dissertations

Low crude oil prices have impacted the economy of the Gulf Cooperation Council (GCC) member countries especially the United Arab Emirates (UAE). Hence it is vital to accelerate the diversification of the economy. Among the many potential diversification avenues, manufacturing is a promising area that could add to the GDP. This work brings out a sustainable and cost-effective method for manufacturing AMCs and expanding their applications.

This work deals with the processing and characterization of recycled AMCs manufactured using a novel approach. With the emphasis on sustainable manufacturing, this work aims to use Scrap Aluminum Alloy Wheels (SAAW) of cars …

Development Of A Decision Support System For Sustainable Water Planning In Abu Dhabi, Uae, Mohamed Ibrahim Kizhisseri

Dissertations

One of the main challenges for water managers is to foresee the future accurately; then, design appropriate policies and infrastructure plans accordingly. The use of decision support systems in the field of water resource management and planning is now widely implemented, but its use in sustainable water planning of a nation or state in arid and semi-arid areas, such as Middle East countries, remains limited. The main objective of this dissertation is to present a graphical software tool that can assist water planners and decision-makers in long-term water management and planning. Sustainable planning for Abu Dhabi’s future water supply is …

Experimental Investigation And Prediction Of Long-Term Effect Of Sustained Load And Harsh Environment On Fiber-Reinforced Polymer Composites, Amir Hussain Idrisi

Dissertations

In this dissertation the durability of thermoset composites was investigated under sustained load. Two thermoset composites, E-glass/epoxy and E-glass/polyurethane were immersed in seawater under sustained load (10%, 15%, 20%, 25% of failure load) and varying temperature (23°C to 95°C) for the period of 15 months. Mechanical, physical and thermal properties were experimentally investigated. The effects of temperature, moisture, and immersion time on the deterioration of the composite material were studied for both composites. It was observed that the weight of the samples increased with the immersion time and temperature for both the composites. The highest increase in weight of the …

Data Mining Of Unstructured Textual Information In Transportation Safety Domain: Exploring Methods, Opportunities And Limitations, Keneth Morgan Kwayu

Dissertations

The unprecedented increase in volume and influx of structured and unstructured data has overwhelmed conventional data management system capabilities in organizing, analyzing, and procuring useful information in a timely fashion. Structured data sources have a pre-defined pattern that makes data preprocessing and information retrieval tasks relatively easy for the current technologies that have been designed to handle structured and repeatable data. Unlike structured data, unstructured data usually exists in an unorganized format that offers no or little insight unless indexed and stored in an organized fashion. The inherent format of unstructured data exacerbates difficulties in data preprocessing and information extraction. …

Optimized Insulation Design Of Power Transformer Windings Under Fast Voltage Pulses, Juan Manuel Villanueva Ramirez

Dissertations

Power transformers are essential electrical power system devices. Using the principle of electromagnetic induction, they can transfer electric energy between two otherwise isolated circuits, as well as reduce or increase voltage levels without modifying the frequency. This allows reduction of power losses when electric energy is transferred between power plants and consumers. Because of their importance and widespread use, transformers failures can have a severe economic impact due to the temporary interruption of electric service.

The insulation design of power transformers is performed by considering the maximum values of voltage or current to which the device will be exposed during …

Optical Engineering Of Iii-Nitride Nanowire Light-Emitting Diodes And Applications, Ha Quoc Thang Bui

Dissertations

Applications of III-nitride nanowires are intensively explored in different emerging technologies including light-emitting diodes (LEDs), laser diodes, photodiodes, biosensors, and solar cells. The synthesis of the III-nitride nanowires by molecular beam epitaxy (MBE) is investigated with significant achievements. III-nitride nanowires can be grown on dissimilar substrates i.e., silicon with nearly dislocation free due to the effective strain relaxation. III-nitride nanowires, therefore, are perfectly suited for high performance light emitters for cost-effective fabrication of the advanced photonic-electronic integrated platforms. This dissertation addresses the design, fabrication, and characterization of III-nitride nanowire full-color micro-LED (µLED) on silicon substrates for µLED display technologies, high-efficient …

Selective Neural Stimulation By Leveraging Electrophysiological Diversity And Using Alternative Stimulus Waveforms, Bemin Ghobreal

Dissertations

Efforts on finding the principle mechanism for selective neural stimulation have concentrated on segregating the neurons based on their size and other geometric factors. However, neuronal subtypes found in different parts of the nervous system also differ in their electrophysiological properties. The primary objective of this study is to investigate the feasibility of selective activation of neurons by leveraging the diversity seen in passive and active membrane properties.

Using both a local membrane model and an axon model based on the CRRSS, the diversity of electrophysiological properties is simulated by varying four model parameters (membrane leakage-Gleak and capacitance-Cm, temperature coefficient-Ktemp, …

Intermittent Dynamics Of Dense Particulate Matter, Chao Cheng

Dissertations

Granular particle systems are scattered around the universe, and they can behave like solids when there exist strong force-bearing networks, so that the granular system can resist certain stress without deformation. When such a network is not present, particles yield to small stress and behave like a fluid. A wide range of systems exhibit intermittent dynamics as they are slowly loaded, with different dynamical regimes governing many industrial and natural phenomena. While a significant amount of research on exploring intermittent dynamics of granular systems has been carried out, not much is known about the connection between particle-scale response and the …

Development Of Deep Learning Neural Network For Ecological And Medical Images, Shaobo Liu

Dissertations

Deep learning in computer vision and image processing has attracted attentions from various fields including ecology and medical image. Ecologists are interested in finding an effective model structure to classify different species. Tradition deep learning model use a convolutional neural network, such as LeNet, AlexNet, VGG models, residual neural network, and inception models, are first used on classifying bee wing and butterfly datasets. However, insufficient data sample and unbalanced samples in each class have caused a poor accuracy. To make improvement the test accuracy, data augmentation and transfer learning are applied. Recently developed deep learning framework based on mathematical morphology …

Safe Yield Comparisons For The 1960’S And 2000’S Drought In The Passaic River Basin, Stephanie R. Santos

Dissertations

The Passaic River Basin is a complex system of rivers, tributaries, reservoirs, and some of the largest water purveyors in the State of New Jersey. Located in the northeastern part of the State, it drains approximately 800 square miles of water that is used for distribution to the five major purveyors: North Jersey District Water Supply Commission, Passaic Valley Water Commission, Jersey City, Newark, and New Jersey American Water. These purveyors operate under a safe yield, which is defined by the New Jersey Department of Environmental Protection (NJDEP) as the amount of water that should be continuously available should the …

First-Principles Density Functional Theory Studies On Perovskite Materials, Aneer Lamichhane

Dissertations

Perovskites are a family of materials with a diverse combination of different elements. As a consequence, they exhibit numerous functionalities such as pyroelectric, piezoelectric, ferroelectric, and ferromagnetic with applications in photovoltaic cells, LEDs, superconductivity, colossal magneto-resistance, and topological insulators. After 2009, perovskites have gained notoriety as suitable materials for solar cells and alternative candidates to silicon-based conventional solar cells. Generally, oxide perovskites exhibit good dielectric properties, halide perovskites display good photonic qualities, and chalcogenide perovskites are used in applications in solid-state lighting, sensing, and energy harvesting. In this dissertation, various types of perovskites ranging from oxide to halide are investigated …

Optimizing Work Zone Schedules Considering Traffic Diversion With Artificial Bee Colony Algorithm, Celina Semaan

Dissertations

Highway maintenance activities often decrease roadway capacity and intrude traffic movements. The need to finish the project on time and under a specific budget while minimizing the traffic congestion and complying with the emission standards requires an appropriate work zone schedule optimization. The objective of this research is to improve the efficiency of work zone activities and minimize the total project cost including maintenance, user, and emission cost.

While previous studies investigated the work zone optimization problem, they did not consider the implementation of emission standards nor applied a green diversion strategy. This dissertation analyzes the optimization of work zone …

Intelligent And Secure Fog-Aided Internet Of Drones, Jingjing Yao

Dissertations

Internet of drones (IoD), which utilize drones as Internet of Things (IoT) devices, deploys several drones in the air to collect ground information and send them to the IoD gateway for further processing. Computing tasks are usually offloaded to the cloud data center for intensive processing. However, many IoD applications require real-time processing and event response (e.g., disaster response and virtual reality applications). Hence, data processing by the remote cloud may not satisfy the strict latency requirement. Fog computing attaches fog nodes, which are equipped with computing, storage and networking resources, to IoD gateways to assume a substantial amount of …

Deep Learning On Image Forensics And Anti-Forensics, Zhangyi Shen

Dissertations

Image forensics protect the authenticity and integrity of digital images. On the contrary, as the countermeasures of digital forensics, anti-forensics is applied to expose the vulnerability of forensics tools. Consequently, forensics researchers could develop forensics tools against possible new attacks. This dissertation investigation demonstrates two image forensics methods based on convolutional neural network (CNN) and two image anti-forensics methods based on generative adversarial network (GAN).

Detecting unsharp masking (USM) sharpened image is the first study in this dissertation. A CNN architecture comprises four convolutional layers and a classification module is proposed to discriminate sharpened images and unsharpened images. The results …