Engineering Commons^™

Vanet Applications Under Loss Scenarios & Evolving Wireless Technology, Adil Alsuhaim

All Dissertations

In this work we study the impact of wireless network impairment on the performance of VANET applications such as Cooperative Adaptive Cruise Control (CACC), and other VANET applications that periodically broadcast messages. We also study the future of VANET application in light of the evolution of radio access technologies (RAT) that are used to exchange messages. Previous work in the literature proposed fallback strategies that utilizes on-board sensors to recover in case of wireless network impairment, those methods assume a fixed time headway value, and do not achieve string stability. In this work, we study the string stability of a …

Enhanced Mobile Networking Using Multi-Connectivity And Packet Duplication In Next-Generation Cellular Networks, Prabodh Mishra

All Dissertations

Modern cellular communication systems need to handle an enormous number of users and large amounts of data, including both users as well as system-oriented data. 5G is the fifth-generation mobile network and a new global wireless standard that follows 4G/LTE networks. The uptake of 5G is expected to be faster than any previous cellular generation, with high expectations of its future impact on the global economy. The next-generation 5G networks are designed to be flexible enough to adapt to modern use cases and be highly modular such that operators would have the flexibility to provide selective features based on user …

A Study On Asymmetric Perfect Vortex: Fractional Orbital Angular Momentum And Nonlinear Interaction, Kunjian Dai

All Dissertations

In this work, the manipulation including generation and detection of the asymmetric perfect vortex (APV) carrying fractional orbital angular momentum (OAM) was demonstrated and discussed. All the manipulation of the modes is in real-time which provides a perfect tool for sensing the dynamic properties of complex media. The OAM-involved nonlinear conversion, specifically the second-harmonic generation (SHG) using the APV and asymmetric Bessel-Gaussian (BG) beams was studied in detail.

The generation and detection of the APV are based on the HOBBIT concept which includes acoustic optical deflector (AOD) and log-polar coordinate transformation optics. The RF signal driving the AOD allows the …

Bridging The Gap Between Phase Behavior And Processing For Renewable And Refinable Carbonaceous Precursors, Graham Tindall

All Dissertations

As a category of materials, engineered carbons, specifically carbon fibers, are first-in-class for properties such as modulus, specific strength, and thermal resilience; however, the inability to directly process atomic carbon necessitates the development and optimization of carbonaceous precursors. Because the structure and properties of carbon are highly dependent on the precursors and requisite processing, numerous materials have been investigated as feedstocks for large-scale production. Although cellulose and rayon were among the first investigated, polyacrylonitrile (PAN) is the current hegemon of carbon fiber precursors. PAN feeds 90% of this market, but it is neither inexpensive nor renewable. Because a significant fraction …

Computational Modeling Of Patterned Membranes And Spacers For Improved Hydrodynamics And Fouling Reduction In Reverse Osmosis Water Treatment Processes, Zuo Zhou

All Dissertations

My research goal is to discover ways to improve the hydrodynamics of reverse osmosis (RO) membrane systems through creative membrane surface patterning and spacer designs. Since concentration polarization (CP) usually promotes membrane fouling, improving hydrodynamics would result in reduced fouling and better membrane performance. With computational fluid dynamics (CFD), we can explore dozens or even hundreds of models with different geometries and boundary conditions. Through plotting their velocity profile, streamlines, shear stress, pressure profile, concentration profile, and so on, we can determine which design would lead to the best performance.

At first, patterned membranes were evaluated and compared with flat …

Molecular Dynamics Simulation On Molybdenum Disulfide: Thermal-Mechanical Properties And Phase Transitions Under External Loading, Mahabubur Rahman

All Dissertations

Due to their remarkable properties, transition metal dichalcogenides (TMDs) have received much scientific interest throughout the past decade. Two layers of chalcogen atoms (S, Se, Te) sandwich a layer of transition metal atoms (Mo, W, Ta) to form the three-atom thick unit cell in TMDs. The interaction between TMD "single layers" is mediated by neighboring chalcogen planes and bonded by Van der Waals forces. Due to this weak out-of-plane interaction, bulk samples can be thinned down to a single layer by exfoliation. Among the TMDs, Molybdenum Disulfide (MoS₂) shows promise in the field of electronics, optics, and sensing …

3d Printing With Photopolymerizable Polyester Resins For Resorbable Medical Device Applications, Mathew Murphy Stanford

All Dissertations

In the past decade, the healthcare industry has seen a significant increase in the use of additive manufacturing (AM or “3D printing”) with subsequent improvement in clinical outcomes.As an exceptional AM technology, vat-photopolymerization (VP), often called stereolithography, can create complex structures and has thus been adopted for a range of biomedical applications including surgical guides, temporary implants, and resorbable tissue scaffolds.However, limitations remain in the availability of photopolymerizable resin materials with appropriate mechanical performance, biodegradability, and biocompatibility for application to resorbable medical devices.

The objective of this work was to employ novel photopolymerizable polyester-based macromers in the development of resorbable …

Mesoscale Modeling Of Controlled Degradation In Polymer Networks And Melts, Vaibhav Palkar

All Dissertations

Controlled degradation of polymers finds various applications in fields ranging from the design of functional soft materials to recycling of polymers. In several of these applications, the characteristic length scale at which relevant processes occur ranges from nanometers to microns, typically referred to as the mesoscale. Although analytical models and continuum approaches inform our current understanding, analysis of degradation at the mesoscale is exceptionally limited. For modeling degradation at the mesoscale, we use the Dissipative Particle Dynamics (DPD) technique and the LAMMPS simulation software. Within the DPD framework, we model controlled degradation or the breaking of covalent bonds within a …

When Less Is More: How Increasing The Complexity Of Machine Learning Strategies For Geothermal Energy Assessments May Not Lead Toward Better Estimates, Stanley P. Mordensky, John Lipor, Jacob Deangelo, Erick R. Burns, Cary R. Lindsey

Electrical and Computer Engineering Faculty Publications and Presentations

Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates.

Our study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. We present and compare nine favorability maps for geothermal resources in the …

Near-Optimal Control Of A Quadcopter Using Reinforcement Learning, Alberto Velazquez-Estrada

Theses and Dissertations

This paper presents a novel control method for quadcopters that achieves near-optimal tracking control for input-affine nonlinear quadcopter dynamics. The method uses a reinforcement learning algorithm called Single Network Adaptive Critics (SNAC), which approximates a solution to the discrete-time Hamilton-Jacobi-Bellman (DT-HJB) equation using a single neural network trained offline. The control method involves two SNAC controllers, with the outer loop controlling the linear position and velocities (position control) and the inner loop controlling the angular position and velocities (attitude control). The resulting quadcopter controller provides optimal feedback control and tracks a trajectory for an infinite-horizon, and it is compared with …

Trajectory Analysis For Driving Safety Quantification, Michael I. Chang

UNLV Theses, Dissertations, Professional Papers, and Capstones

In order to evaluate the efficacy of the skid recovery exercise in the Driver’s Edge teenage driving program, a process is established to determine the trajectories of vehicles from recorded videos, compare them in terms of similarity through dynamic time warping (DTW), and then analyze the similarity measurements to assess whether the program has a significant effect on driving ability by repeated measures analysis of variance (rANOVA). The video is analyzed by Harris corner detection and Lucas-Kanade optical flow method to ascertain the vehicle trajectories. A homography is then estimated to translate coordinates from video into real-world. The instructor and …

Reducing Infiltration And Inflow In Small Collection Systems: Environmental, Economic, And Other Impacts, Andrew Hansen

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Wastewater treatment facilities (WWTFs) and the collection systems (CSs) which feed them provide essential services to society by collecting sewage (aka wastewater), biologically treating it, and minimizing risks to human health as well as the impact of waste on the environment. However, as collection systems age, increasing infiltration and inflow (I/I) from groundwater and stormwater can negatively affect the system. I/I is often mitigated to reduce flow and eliminate other negative impacts to the system.

Ten total case studies, seven mechanical water resource recovery facilities (WRRFs) and three lagoon facilities, were examined for the environmental, economic, and other impacts/benefits from …

Sustainable Revitalization Of Asphalt Pavements: An In-Depth Analysis Of Enhancing The Performance Of Asphalt Binder Through The Application Of Rheological And Molecular Dynamics Simulation Techniques, Muhammad Ahmad

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Vegetable-based oils such as corn and soybean oil have triglycerides and fatty acids that allow them to be considered sustainable and effective recycling agents (RAs) for aged asphalt binder. However, there are concerns about their effect on the recycled asphalt binder's long-term performance, moisture damage resistance, and self-healing characteristics restoration. In this study, crude corn oil (CO) and crude soybean oil (SO) were used as RAs to restore the performance of a reclaimed asphalt binder (RAB) extracted from reclaimed asphalt pavement. The binder extracted from RAB was modified with a neat binder PG64-28 and RAs to restore the high-end performance …

Assessing The Performance Of High-Rap Mixtures Incorporating Crude Vegetable Oils And An Antioxidant From Mechanical, Environmental, And Economic Perspectives, Nitish R. Bastola

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Utilization of mixtures with high amounts of reclaimed asphalt pavement (RAP) in the pavement industry is limited because of the adverse effects of aged materials in recycled asphalt materials. To date, numerous approaches have been used to reduce the adversity of RAP in mixtures. One such approach is the use of recycling agents (RAs) from various sources, such as petroleum and bio-oil. However, the current need is to maximize the use of RAP by adopting a sustainable source of RAs. Therefore, this study uses two RAs based on vegetable oils (crude soybean oil and crude corn oil) with high-RAP mixtures …

Design Of A Miniature Robotic Surgery Technology Demonstration Payload For Orbital Spaceflight, Rachael A. Wagner

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

This thesis describes the design of a technology demonstration payload that will test robotic surgery while aboard a 2024 expedition of the International Space Station (ISS). The payload utilizes a new miniature surgical robot to complete simulated surgical tasks on orbit, both autonomously and while remotely controlled by an Earth-based user. The experiment investigates the effects of microgravity and latency on robotic surgery, with the following goals:

1. Demonstrate the use of a miniature robotic surgical system in microgravity through performing simulated surgical tasks.

2. Quantify the effects of microgravity on robotic surgical techniques including forces, torques, and kinematic accuracy. …

Blood Flow Regulates Atherosclerosis Progression And Regression, Morgan A. Schake

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Atherosclerosis is the most prevalent pathology of cardiovascular disease with no known cure. Despite the many systemic risk factors for atherosclerosis, plaques do not form randomly in the vasculature. Instead, they form around bifurcations and the inner curvature of highly curving arterial segments that contain so-called disturbed blood flow that is low in magnitude and multidirectional over the cardiac cycle. Conversely, straight, non-bifurcated arterial segments that contain moderate-to-high and unidirectional (i.e., normal) blood flow are protected from plaque development. Thus, blood flow is a key regulator of atherosclerosis that may be able to be leveraged to develop new therapeutics. Towards …

Studying Pedestrian’S Unmarked Midblock Crossing Behavior On A Multilane Road When Interacting With Autonomous Vehicles Using Virtual Reality, Fengjiao Zou

All Dissertations

This dissertation focuses on the challenge of pedestrian interaction with autonomous vehicles (AVs) at unmarked midblock locations where the right-of-way is unspecified. A virtual reality (VR) simulation was developed to replicate an urban unmarked midblock environment where pedestrians cross a four-lane arterial roadway and interact with AVs. One research goal is to investigate the impact of roadway centerline features (undivided, two-way left-turn lane, and median) and AV operational schemes portrayed through on-vehicle signals (no signal, yellow negotiating indication, and yellow/blue negotiating/no-yield indications) on pedestrian crossing behavior. Results demonstrate that both roadway centerline design features and AV operations and signaling show …

Explainable Physics-Informed Deep Learning For Rainfall-Runoff Modeling And Uncertainty Assessment Across The Continental United States, Sadegh Sadeghi Tabas

All Dissertations

Hydrologic models provide a comprehensive tool to calibrate streamflow response to environmental variables. Various hydrologic modeling approaches, ranging from physically based to conceptual to entirely data-driven models, have been widely used for hydrologic simulation. During the recent years, however, Deep Learning (DL), a new generation of Machine Learning (ML), has transformed hydrologic simulation research to a new direction. DL methods have recently proposed for rainfall-runoff modeling that complement both distributed and conceptual hydrologic models, particularly in a catchment where data to support a process-based model is scared and limited.

This dissertation investigated the applicability of two advanced probabilistic physics-informed DL …

Explaining Spatio-Temporal Evolution Of Extreme Hydro-Climatic Events Using A Complex Network Framework, Somnath Mondal

All Dissertations

Severe hydroclimatic extreme events, such as droughts, heatwaves, and heavy rainfall, are occurring with increasing frequency and causing significant impacts on both people and the environment. These events also compound in space and time, leading to even more significant consequences. Therefore, it is essential to comprehend these phenomena' concurrent and time-delayed progression across different temporal and spatial scales to address adaptation and mitigation effectively. To accurately understand and map the co-evolution of extreme events, it's necessary to have a thorough grasp of their spatiotemporal patterns, how they propagate and interact with one another, and the underlying mechanisms driving their occurrence. …

Characterization Of Lignin And Cellulose Biopolymers Structure – Function Relationships, Zachariah Pittman

All Dissertations

Biomass is vital to ongoing efforts to secure a sustainable future. While many of our efforts focus on finding alternative forms of energy, biomass among them, only biomass has the potential to serve as a sustainable materials feedstock. However, biomass is heterogenous, complicating the upgrading processes needed to manufacture commodity and performance products. For example, plant biomass consists largely of cellulose, a crystalline polysaccharide, and lignin, a highly stable polyaromatic. The specific properties of cellulose and lignin depend greatly on the plant, harvesting conditions, and isolation procedures. Thus, accurate and reliable determination of the fundamental properties of biomass is crucial …

Classification Of Electrical Current Used In Electroplastic Forming, Tyler Grimm

All Dissertations

Electrically assisted manufacturing (EAM) is the direct application of an electric current to a workpiece during manufacturing. This advanced manufacturing process has been shown to produce anomalous effects which extend beyond the current state of modeling of thermal influences. These purported non-thermal effects have collectively been termed electroplastic effects (EPEs).

While there is a distinct difference in results between steady-state (ideal DC) testing and pulsed current testing, the very definition of these two EAM methods has not been well established. A "long" pulse may be considered DC current; a "short" pulse may produce electroplastic effects; and even "steady-state" current shapes …

Machine Learning-Based Data And Model Driven Bayesian Uncertanity Quantification Of Inverse Problems For Suspended Non-Structural System, Zhiyuan Qin

All Dissertations

Inverse problems involve extracting the internal structure of a physical system from noisy measurement data. In many fields, the Bayesian inference is used to address the ill-conditioned nature of the inverse problem by incorporating prior information through an initial distribution. In the nonparametric Bayesian framework, surrogate models such as Gaussian Processes or Deep Neural Networks are used as flexible and effective probabilistic modeling tools to overcome the high-dimensional curse and reduce computational costs. In practical systems and computer models, uncertainties can be addressed through parameter calibration, sensitivity analysis, and uncertainty quantification, leading to improved reliability and robustness of decision and …

A Value-Based Sequential Optimization Framework For Efficient Materials Design Considering Uncertainty And Variability, Maher Alghalayini

All Dissertations

Many problems in engineering and science can be framed as decision problems in which we choose values for decision variables that lead to desired outcomes. Notable examples include maximizing lift in airplane wing design, improving the efficiency of a power plant, or identifying processing protocols resulting in structural materials with desired mechanical properties. These problems typically involve a significant degree of uncertainty about the often-complex underlying relationships between the decision variables and the outcomes. Solving such decision problems involves the use of computational models or physical experimentation to generate data to make predictions and test hypotheses. As a result, both …

Fluorescence Multiplexing With Combination Probes For Biological And Diagnostic Applications, Madeline Mccarthy

All Dissertations

Cancer refers to a group of diseases containing more than 200 different subtypes. Cancer is a heterogeneous disease by nature, meaning that there are differences among tumors of the same type in different patients, and there are differences among cancer cells within a single tumor of one patient. Since cancer is not a single disease, nor does it have a single cause, it proves to be incredibly hard to diagnose and treat. The ability to study cellular markers, cell and tissue spatial arrangement, and gene function are all integral parts of cancer diagnostic and treatment efforts.

Here, I first present …

Development Of Medical Device For Volume Status Assessment Using Peripheral Venous Pressure, Audra Beneux

Graduate Theses and Dissertations

The severe side effects of acute dehydration and blood loss may be prevented if assessed and treated quickly. As amplifier technology has improved, small peripheral venous pressure (PVP) signals collected using a transducer on an intravenous catheter can be analyzed to monitor patient volume status. This thesis details the development of an embedded system prototype that quickly and accurately assesses volume status using PVP analysis. The volume prediction algorithm classified 10 seconds of PVP data as “dehydrated” or “resuscitated”. The hardware design consisted of four primary areas: analog signal conditioning, processing, user interaction, and power. After data collection, the signal …

Intelligent And Explainable Solution To Predict Infant Birthweight And Preterm Birth In The United Arab Emirates, Wasif Khan

Dissertations

Adverse pregnancy outcomes such as Low Birth Weight (LBW) and Preterm birth (PTB) are complex pregnancy challenges that can lead to high perinatal mortality and long-term morbidity for infants. Early prediction of such adverse outcomes can be useful for averting catastrophic outcomes for the mother and her baby. With advances in machine learning (ML)-based algorithms, several models have been proposed for both PTB and LBW predictions. However, the risk factors associated with these outcomes are still unknown, particularly in the United Arab Emirates (UAE). Furthermore, existing ML-based prediction models work in a black-box manner and lack proper interpretations for clinicians, …

Cortical Effects Of Wrist Tendon Vibration During An Arm Tracking Task In Chronic Stroke Survivors: An Eeg Study, Dylan B. Snyder, Scott A. Beardsley, Allison S. Hyngstrom, Brian D. Schmit

Biomedical Engineering Faculty Research and Publications

The purpose of this study was to characterize changes in cortical activity and connectivity in stroke survivors when vibration is applied to the wrist flexor tendons during a visuomotor tracking task. Data were collected from 10 chronic stroke participants and 10 neurologically-intact controls while tracking a target through a figure-8 pattern in the horizontal plane. Electroencephalography (EEG) was used to measure cortical activity (beta band desynchronization) and connectivity (beta band task-based coherence) with movement kinematics and performance error also being recorded during the task. All participants came into our lab on two separate days and performed three blocks (16 trials …

Synthesis, Radiolabeling And Evaluation Of A Suite Of Tracers With 44Sc For Detecting Extracellular Dna, Zhiyao Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

Neutrophil extracellular traps involve the rapid translocation of DNA to the outside of the cell under certain stimuli. This structure forms a fibrous network that is able to limit the spread of pathogens and to kill microorganisms. It has also been shown to be present in various pathological processes such as inflammation, autoimmune diseases, and cancer metastasis. Currently, the formation process of NETs in vivo is being extensively studied. However noninvasive detection and quantitation has yet to be achieved. A class of PET tracers are described here that consists of a DNA dye as the backbone that is labeled with …

A Magneto-Rheological Platform To Dynamically Control Afterload In Engineered Micro Heart Muscles, David Schuftan

McKelvey School of Engineering Graduate Student Theses & Dissertations

Cardiovascular disease is the leading cause of death is the United States, accounting for nearly 1 in 5 deaths. Many types of cardiovascular disease are linked to the mechanical forces placed on the heart. However, how these mechanical forces exactly affect the cellular biology of the heart is not well defined. In vitro models using cardiomyocytes derived from human induced pluripotent stem cells enable researchers to develop medium throughput systems to study cardiac mechanobiology at the cellular level. Previous models have been developed to enable the study of mechanical forces such as cardiac afterload. However, most of these models require …

Analytical And Experimental Investigation Of Interphase And Dispersion Effects On The Mechanical Stiffness Of Cellulose Nanocomposites, Will Goldberg

McKelvey School of Engineering Graduate Student Theses & Dissertations

The effect of dispersion and interphase properties on the elastic behavior of cellulose nanocomposites was investigated using a number of composite models, experimental data and a thorough literature review. Cellulose nanocomposites consisting of soy protein isolate (SPI) and cellulose nanocrystals (CNC) or polydopamine coated cellulose nanocrystals (PD-CNC) were prepared via solution casting method and tested for mechanical stiffness. These outcomes were compared to standard composite models as well as novel methods adapted from the literature that incorporate data regarding dispersion quality and interphase properties. The literature review verified that both dispersion and interphase properties are highly dependent on interfacial chemistry …