Engineering Commons^™

Cu/Bnx Catalysts For Electrocatalytic Reduction Of Nitrogen And Nitrate Waste, Siming Huo

Dissertations

Ammonia (NH₃) is one of the most important chemicals to the whole human society. The invention of the Haber-Bosch process enabled the industrial production of NH₃. However, owing to the high capital costs of the centralized plant and the equipment and the negative environmental impact, it is no longer suitable for today's needs of human development. As a result, there is an urgent need to investigate sustainable approaches for ammonia production. Among those reported studies, nitrogen reduction (NRR) and nitrate reduction reaction (NO₃RR) are considered applicable in the future. However, after decades of studying …

Importance Of Vegetation In Tsunami Mitigation: Evidence From Large Eddy Simulations With Fluid-Structure Interactions, Abhishek Mukherjee

Dissertations

Communities worldwide are increasingly interested in nature-based solutions like coastal forests for the mitigation of coastal risks. Still, it remains unclear how much protective benefit vegetation provides, particularly in the limit of highly energetic flows after tsunami impact. The present thesis, using a three-dimensional incompressible computational fluid dynamics model with a fluid-structure interaction approach, aims to quantify how energy reflection and dissipation vary with different degrees of rigidity and vegetation density of a coastal forest.

In this study, tree trunks are represented as cylinders, and the elastic modulus of hardwood trees such as pine or oak is used to characterize …

Influence Of Material Properties On Granules Prepared By Dry Co-Rotating Twin Screw Extrusion And Counterrotating Batch Mixing, Afstathios Steve Pafiakis

Dissertations

Recently, the pharmaceutical industry has shown interest in continuous granulating technology because of the flexibility it offers as an option that bypasses the costly scale-up process associated with batch manufacturing. However, the granulation mechanism(s) using twin screw co-rotating hot melt extrusion (HME) has not been fully explored, and it is not yet well understood. This leads to costly experiments during development and process reliability problem in commercial manufacturing. The main objective of this dissertation is to increase the mechanistic understanding of the twin screw granulation process of systems containing an active pharmaceutical ingredient (API) and a polymer excipient. This is …

Pbm And Dem Simulations Of Large-Scale Closed-Circuit Continuous Ball Mill Of Cement Clinker, Nontawat Muanpaopong

Dissertations

Cement milling is known to be inefficient and energy-intensive. Thus, even small improvements in cement milling's performance could significantly reduce operation costs. This dissertation aims to develop a simulation tool for dry milling and generate a fundamental process understanding, which enables process optimization. To this end, a true unsteady-state simulator (TUSSIM) for continuous dry milling is developed and applied to model various processes: (a) open circuit continuous mills, (b) closed-circuit continuous mills, and (c) vertical roller mills. TUSSIM is based on the solution of the cell-based population balance model (PBM) for continuous milling, which consists of a set of differential …

Design, Simulation, Modeling, And Implementation Of Triboelectric Nanogenerator (Teng) Sensors For Automotive Applications, Sam Ali

Dissertations

Triboelectricity is a promising technique for energy harvesting in which mechanical energy converts to electricity for powering small electronic devices. This method of energy harvesting serves as an alternative to traditional battery power sources and can significantly benefit low-power sensing applications by generating unlimited electrical energy. This study focuses on the development of flexible triboelectric nanogenerators (TENG) and energy harvesting devices for various applications in the automotive industry.

The study is organized into four projects. In the first project, various polymeric materials were used to investigate the performance of different TENGs. Four designs (D1, D2, D3, and D4) of flexible …

Approximate Computing Based Processing Of Mea Signals On Fpga, Mohammad Emad Hassan

Dissertations

The Microelectrode Array (MEA) is a collection of parallel electrodes that may measure the extracellular potential of nearby neurons. It is a crucial tool in neuroscience for researching the structure, operation, and behavior of neural networks. Using sophisticated signal processing techniques and architectural templates, the task of processing and evaluating the data streams obtained from MEAs is a computationally demanding one that needs time and parallel processing.

This thesis proposes enhancing the capability of MEA signal processing systems by using approximate computing-based algorithms. These algorithms can be implemented in systems that process parallel MEA channels using the Field Programmable Gate …

Carrier Transport Engineering In Wide Bandgap Semiconductors For Photonic And Memory Device Applications, Ravi Teja Velpula

Dissertations

Wide bandgap (WBG) semiconductors play a crucial role in the current solid-state lighting technology. The AlGaN compound semiconductor is widely used for ultraviolet (UV) light-emitting diodes (LEDs), however, the efficiency of these LEDs is largely in a single-digit percentage range due to several factors. Until recently, AlInN alloy has been relatively unexplored, though it holds potential for light-emitters operating in the visible and UV regions. In this dissertation, the first axial AlInN core-shell nanowire UV LEDs operating in the UV-A and UV-B regions with an internal quantum efficiency (IQE) of 52% are demonstrated. Moreover, the light extraction efficiency of this …

Improving The Stimulation Selectivity In The Human Cochlea By Strategic Selection Of The Current Return Electrode, Ozan Cakmak

Dissertations

The hearing quality provided by cochlear implants are poorly predicted by computer simulations. A realistic cochlear anatomy is crucial for the accuracy of predictions. In this study, the standard multipolar stimulation paradigms are revisited and Rattay’s Activating Function is evaluated in a finite element model of a realistic cochlear geometry that is based on µ-CT images and a commercial lead. The stimulation thresholds across the cochlear fibers were investigated for monopolar, bipolar, tripolar, and a novel (distant) bipolar electrode configuration using an active compartmental nerve model based on Schwartz-Eikhof-Frijns membrane dynamics. The results suggest that skipping of the stimulation point …

Integrated Machine Learning And Optimization Approaches, Dogacan Yilmaz

Dissertations

This dissertation focuses on the integration of machine learning and optimization. Specifically, novel machine learning-based frameworks are proposed to help solve a broad range of well-known operations research problems to reduce the solution times. The first study presents a bidirectional Long Short-Term Memory framework to learn optimal solutions to sequential decision-making problems. Computational results show that the framework significantly reduces the solution time of benchmark capacitated lot-sizing problems without much loss in feasibility and optimality. Also, models trained using shorter planning horizons can successfully predict the optimal solution of the instances with longer planning horizons. For the hardest data set, …

Faceted Nanomaterial Synthesis, Characterizations And Applications In Reactive Electrochemical Membrane Filtration, Qingquan Ma

Dissertations

Facet engineering of nanomaterials, especially metals and metal oxides has become an important strategy for tuning catalytic properties and functions from heterogeneous catalysis to electrochemical catalysis, photocatalysis, biomedicine, fuel cells, and gas sensors. The catalytic properties are highly related to the surface electronic structures, surface electron transport characteristics, and active center structures of catalysts, which can be tailored by surface facet control. The aim of this doctoral dissertation research is to study the facet-dependent properties of metal or metal oxide nanoparticles using multiple advanced characterization techniques. Specifically, the novel atomic force microscope-scanning electrochemical microscope (AFM-SECM) and density functional theory (DFT) …

Hydrodynamic Investigation Of The Discharge Of Complex Fluids From Dispensing Bottles Using Experimental And Computational Approaches, Baran Teoman

Dissertations

The discharge of non-Newtonian, complex fluids through orifices of industrial tanks, pipes, dispensers, or packaging containers is a ubiquitous but often problematic process because of the complex rheology of such fluids and the geometry of the containers. This, in turn, reduces the discharge rate and results in residual fluid left in the container, often referred to as heel. Heel formation is undesired in general, since it causes loss of valuable material, container fouling, and cross-contamination between batches. Heel may be of significant concern not only in industrial vessels but also in consumer packaging. Despite its relevance, the research in this …

Microhydrodynamic, Kinetic And Thermal Modeling Of Wet Media Milling For Process Optimization And Intensification, Gulenay Guner

Dissertations

Nanoparticle production by wet stirred media milling (WSMM) is a common method for the formulation of poorly water-soluble drugs. While most of the studies in the WSMM literature focus on the formulation aspects to overcome the stability challenges, a thorough mechanistic understanding of the process is lacking, and the process is slow, costly, and energy-intensive. This dissertation presents experimental and modeling work with the ultimate goals of (i) gaining a deeper and more mechanistic understanding of the WSMM process and breakage kinetics of the particles using a microhydrodynamic model with various improvements and advancements, (ii) examining the heat dissipation during …

Bioremediation Of Petroleum Hydrocarbons In Coastal Sediments, Charbel Abou Khalil

Dissertations

The biodegradation of dispersed crude oil in the ocean is relatively rapid (a half-life of a few weeks). However, it is often much slower on shorelines, usually attributed to low moisture content, nutrient limitation, and higher oil concentrations in beaches than in dispersed plumes. Another factor may be the increased salinity of the upper intertidal and supratidal zones since these parts of the beach are potentially subject to prolonged evaporation and only intermittent inundation. Therefore, two laboratory experiments are conducted to investigate whether such an increase in porewater salinity results in additional inhibitory effects on oil biodegradation in seashores.

In …

Angiogenic Supports For Microvascular Engineering, Zain Siddiqui

Dissertations

Ischemic tissue disease is caused by a lack of circulation / blood supply to tissue. This can be treated by introducing a number of angiogenic (pro-blood vessel forming) factors into the tissue. This work presents strategies for ischemic tissue treatment utilizing a novel proangiogenic self-assembling peptide hydrogel platform. To demonstrate the utility of this platform, its use alone as an angiogenic therapeutic (both alone as a self-assembling hydrogel and with two-component systems), and its ability to vascularize implants is explored. Due to these angiogenic scaffolds demonstrating efficacy to regenerate microvasculature, this work evaluates diseases that can be treated by the …

Developing Distributed Real-Time Hybrid Simulation For Dynamic Response Evaluation Of Floating Wind Turbine, Hezha Lutfalla Sadraddin

Dissertations

Floating wind turbine (FWT) has a significant role in producing clean and sustainable energy in unlimited spaces with more steady wind and less cost. The design, construction, and safe operation of FWTs require a deep understanding of their dynamic responses under combined aerodynamic and hydrodynamic loads. Conventional FWT model experiments utilize wave tanks and wind tunnels. However, laboratory size and capacity and the scaling conflicts between the Froude and the Reynold numbers in these coupled wind-wave loading tests impose challenges to replicate dynamic responses of FWT. Alternatively, real-time hybrid simulation (RTHS), which combines numerical simulation and physical experiment of FWT …

Instance Segmentation-Based Depth Completion Using Sensor Fusion And Adaptive Clustering For Autonomous Vehicle Perception, Mohammad Z. El-Yabroudi

Dissertations

Depth sensing is critical for safe and accurate maneuvering in robotics and self-driving car (SDC) applications. Most recent LiDAR sensors, such as Ouster and Velodyne, offer 360 degrees of scanning at the rate of ten frames per second, making them very appropriate for autonomous driving applications. However, LiDAR point cloud data show many shortcomings, especially its data sparsity and unassigned nature, making it very challenging to utilize in applications such as perception, 3D object detection, 3D scene reconstruction, and simultaneous localization and mapping.

In this study, a novel framework using instance image segmentation and the raw LiDAR data for the …

Study Of Sustainable Development In Paper, Printing And Packaging Material Applications To Support Circular Economy, Prashant Ramesh Kotkar

Dissertations

To support circular economy and sustainability, the use of suitable material in paper, printing, and packaging industries, for several types of industrial printing material and printed product applications, plays a significant role for end user applications. Several types of packaging printing materials, specifically those finished with different printing technologies and exposed to different environmental conditions are targeted.

The purpose of this research study is to improve design and evaluation for paper, printing, and packaging material sustainability in end-user applications, to deal with the addressed sustainability issues brought by the paper, printing and packaging products end user groups. As the impacts …

Integrating Kano Model With Data Mining Techniques To Enhance Customer Satisfaction, Khaled Abdulla Ali Al Rabaiei

Dissertations

The business world is becoming more competitive from time to time; therefore, businesses are forced to improve their strategies in every single aspect. So, determining the elements that contribute to the clients' contentment is one of the critical needs of businesses to develop successful products in the market. The Kano model is one of the models that help determine which features must be included in a product or service to improve customer satisfaction. The model focuses on highlighting the most relevant attributes of a product or service along with customers’ estimation of how these attributes can be used to predict …

A Comprehensive Evaluation Of Satellite-Based Precipitation Products And Their Performance In Arid And Temperate Climates, Mohammed Tarig Mahmoud

Dissertations

Accurate and continuous precipitation monitoring is critical to enable effective water resources management; the challenge arises from the spatial and temporal variability of precipitation. The recently launched Global Precipitation Measurement (GPM) satellite has the capability to detect and measure all types of precipitation using advanced instruments. Being at its early stages of development, the products of the GPM IMERG (early, late, and final-run-products) need to be validated using multiple spatial and temporal assessment techniques. Several studies have emerged over the past few years evaluating GPM IMERG results over areas of limited size. These areas were set by hydrologic interest (e.g., …

Software Protection And Secure Authentication For Autonomous Vehicular Cloud Computing, Muhammad Hataba

Dissertations

Artificial Intelligence (AI) is changing every technology we deal with. Autonomy has been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected coined as Autonomous Vehicles (AVs). Moreover, researchers found a way to make more use of these enormous capabilities and introduced Autonomous Vehicles Cloud Computing (AVCC). In these platforms, vehicles can lend their unused resources and sensory data to join AVCC.

In this dissertation, we investigate security and privacy issues in AVCC. As background, we built our …

Computation Of Risk Measures In Finance And Parallel Real-Time Scheduling, Yajuan Li

Dissertations

Many application areas employ various risk measures, such as a quantile, to assess risks. For example, in finance, risk managers employ a quantile to help determine appropriate levels of capital needed to be able to absorb (with high probability) large unexpected losses in credit portfolios comprising loans, bonds, and other financial instruments subject to default. This dissertation discusses the computation of risk measures in finance and parallel real-time scheduling.

Firstly, two estimation approaches are compared for one risk measure, a quantile, via randomized quasi-Monte Carlo (RQMC) in an asymptotic setting where the number of randomizations for RQMC grows large, but …

Optimizing Incentives For Systems With Heterogeneous Agents, Chen Chen

Dissertations

This dissertation explores new models and applications based on the game theory of incentives. This exploration starts with controlling an invasive insect problem to address one of the most significant challenges facing our forests, the invasion of the Emerald ash borer (EAB), a non-native, wood-boring insect that threatens to kill most ash trees in North America, through designing two new cost-sharing programs between the landowners and local governments. Ash trees are one of North America’s most widely distributed tree genera and a vital part of the green infrastructure of cities, where they provide residents with numerous social, economic, and ecological …

Performance Analysis Of The Dominant Mode Rejection Beamformer, Enlong Hu

Dissertations

In array signal processing over challenging environments, due to the non-stationarity nature of data, it is difficult to obtain enough number of data snapshots to construct an adaptive beamformer (ABF) for detecting weak signal embedded in strong interferences. One type of adaptive method targeting for such applications is the dominant mode rejection (DMR) method, which uses a reshaped eigen-decomposition of sample covariance matrix (SCM) to define a subspace containing the dominant interferers to be rejected, thereby allowing it to detect weak signal in the presence of strong interferences. The DMR weight vector takes a form similar to the adaptive minimum …

Low-Reynolds-Number Locomotion Via Reinforcement Learning, Yuexin Liu

Dissertations

This dissertation summarizes computational results from applying reinforcement learning and deep neural network to the designs of artificial microswimmers in the inertialess regime, where the viscous dissipation in the surrounding fluid environment dominates and the swimmer’s inertia is completely negligible. In particular, works in this dissertation consist of four interrelated studies of the design of microswimmers for different tasks: (1) a one-dimensional microswimmer in free-space that moves towards the target via translation, (2) a one-dimensional microswimmer in a periodic domain that rotates to reach the target, (3) a two-dimensional microswimmer that switches gaits to navigate to the designated targets in …

Artificial Neural Networks And Their Applications To Intelligent Fault Diagnosis Of Power Transmission Lines, Fatemeh Mohammadi Shakiba

Dissertations

Over the past thirty years, the idea of computing based on models inspired by human brains and biological neural networks emerged. Artificial neural networks play an important role in the field of machine learning and hold the key to the success of performing many intelligent tasks by machines. They are used in various applications such as pattern recognition, data classification, stock market prediction, aerospace, weather forecasting, control systems, intelligent automation, robotics, and healthcare. Their architectures generally consist of an input layer, multiple hidden layers, and one output layer. They can be implemented on software or hardware. Nowadays, various structures with …

Behavior Of Novel Cementitious Composites For Use In Sustainable Construction And Rehabilitation, Noah A. Thibodeaux

Dissertations

Cementitious composites are a class of cement-based materials that incorporate a cement paste and other constituents to form a composite material. Cementitious composites may include coarse and/or fine aggregate, admixtures, supplementary cementitious materials (SCMs), or fibers in order to achieve a desired workability, strength, or durability property.

Recently, material scientists and engineers have developed a variety of novel cementitious composites for the purpose of new construction, rehabilitation, and reconstruction applications. Such materials can be used to improve the sustainability of civil infrastructure through the use of recycled, repurposed, or low-embodied carbon materials. Since many of the qualification standards and tests …

Digital Image Forensics Via Meta-Learning And Few-Shot Learning, Yuxi Shi

Dissertations

Digital images are a substantial portion of the information conveyed by social media, the Internet, and television in our daily life. In recent years, digital images have become not only one of the public information carriers, but also a crucial piece of evidence. The widespread availability of low-cost, user-friendly, and potent image editing software and mobile phone applications facilitates altering images without professional expertise. Consequently, safeguarding the originality and integrity of digital images has become a difficulty. Forgers commonly use digital image manipulation to transmit misleading information. Digital image forensics investigates the irregular patterns that might result from image alteration. …

Effect Of Current Density Ramping On The Anodic Reaction And Morphology Of Aerospace Aluminum Alloys, Peter Totaro Jr.

Dissertations

Aluminum anodizing has been experimented with and studied over the last century because of its ability to form uniform, well ordered cellular coatings on aluminum alloys. Anodizing aerospace alloys has been problematic, due to the alloying elements used to add strength and resistance to stress cracking corrosion. These intermetallic compounds, i.e., copper and zinc, promote oxygen evolution and stress as they accumulate in and on the surface of the forming aluminum oxide. These inclusions lead to increased electrical resistance that forms porous and flawed coating, which can lead to industrial and field failures. The amount of voltage placed on the …

Sensorimotor Content Of Multi-Unit Activity In The Paramedian Lobule Of The Cerebellum, Esma Cetinkaya

Dissertations

Based on Center for Disease Control and Prevention report 2016, around 39.5 million people in the United States suffer from motor disabilities. These disabilities are due to traumatic conditions like traumatic brain injury (TBI), neurological diseases such as amyotrophic lateral sclerosis (ALS), or congenital conditions. One of the approaches for restoring the lost motor function is to extract the volitional information from the central nervous system (CNS) and control a mechanical device that can replace the function of a paralyzed limb through systems called Brain-Computer Interfaces (BCI).

One of the major challenges being faced in BCIs and also in general …

Resource Allocation, User Association And Placement For Uav-Assisted Communications, Shuai Zhang

Dissertations

In the past few years, unmanned aerial vehicle (UAV)-assisted heterogeneous network has attracted significant attention due to its wide range of applications, such as disaster rescue and recovery, ground macro base station (MBS) traffic offloading, communications for temporary events, and data collection for further processing in Internet of Things (IoT). A UAV can act as a flying base station (BS) to quickly recover the communication coverage in the disaster area when the regular terrestrial infrastructure is malfunctioned. The UAV-assisted heterogeneous network can effectively provision line of sight (LoS) communication links and therefore can mitigate potential signal shadowing and blockage. The …