Engineering Commons^™

Investigation Into The Effect Of Mixture Composition On Setting Time Of Magnesium Phosphate Cement, Autumn Broglen

Civil Engineering Undergraduate Honors Theses

Magnesium phosphate cement (MPC) is a cementitious material that is formed through an acid-base reaction between magnesia and phosphate. This reaction occurs rapidly, making MPC an appealing choice for rapid repair applications. The purpose of this project is to investigate the impact of different proportions of class F fly ash, set retarder consisting of a mixture of boric acid and dextrose, magnesium to phosphate ratio, and water/cement ratio on the initial setting time of MPC paste. Different mixtures of MPC paste were developed to vary the proportions of each constituent, and setting time of each mixture was determined using the …

Deep Learning Using Vision And Lidar For Global Robot Localization, Brett E. Gowling

Master's Theses

As the field of mobile robotics rapidly expands, precise understanding of a robot’s position and orientation becomes critical for autonomous navigation and efficient task performance. In this thesis, we present a snapshot-based global localization machine learning model for a mobile robot, the e-puck, in a simulated environment. Our model uses multimodal data to predict both position and orientation using the robot’s on-board cameras and LiDAR sensor. In an effort to minimize localization error, we explore different sensor configurations by varying the number of cameras and LiDAR layers used. Additionally, we investigate the performance benefits of different multimodal fusion strategies while …

A Smart Hybrid Enhanced Recommendation And Personalization Algorithm Using Machine Learning, Aswin Kumar Nalluri

Electronic Theses, Projects, and Dissertations

In today’s age of streaming services, the effectiveness and precision of recommendation systems are crucial in improving user satisfaction. This project introduces the Smart Hybrid Enhanced Recommendation and Personalization Algorithm (SHERPA) a cutting-edge machine learning approach aimed at transforming how movie suggestions are made. By combining Term Frequency Inverse Document Frequency (TF-IDF) for content based filtering and Alternating Squares (ALS) with Weighted Regularization for filtering SHERPA offers a sophisticated method for delivering tailored recommendations.

The algorithm underwent evaluation using a dataset that included over 50 million ratings from 480,000 Netflix users encompassing 17,000 movie titles. The performance of SHERPA was …

Cultural Awareness Application, Bharat Gupta

Electronic Theses, Projects, and Dissertations

In an increasingly interconnected global landscape, cultural awareness and competency have become indispensable skills for individuals and organizations alike. This paper introduces a pioneering cultural awareness application, grounded in the Cultural Orientation Model—a comprehensive framework devised by Dr. Walker [8]to guide individuals in understanding, appreciating, and effectively engaging with diverse cultures. The application encompasses ten primary dimensions, each representing fundamental aspects of social life shared by members of any socio-cultural environment. Through a combination of cultural education, interactive learning, guidance on cultural etiquette, and integration of cultural events, the application aims to foster empathy, tolerance, and effective cross-cultural communication skills. …

Automated Brain Tumor Classifier With Deep Learning, Venkata Sai Krishna Chaitanya Kandula

Electronic Theses, Projects, and Dissertations

Brain Tumors are abnormal growth of cells within the brain that can be categorized as benign (non-cancerous) or malignant (cancerous). Accurate and timely classification of brain tumors is crucial for effective treatment planning and patient care. Medical imaging techniques like Magnetic Resonance Imaging (MRI) provide detailed visualizations of brain structures, aiding in diagnosis and tumor classification^[8].

In this project, we propose a brain tumor classifier applying deep learning methodologies to automatically classify brain tumor images without any manual intervention. The classifier uses deep learning architectures to extract and classify brain MRI images. Specifically, a Convolutional Neural Network (CNN) …

Effectiveness Of Cnn-Lstm Models Used For Apple Stock Forecasting, Ethan White

Electronic Theses, Projects, and Dissertations

This culminating experience project investigates the effectiveness of convolutional neural networks mixed with long short-term memory (CNN-LSTM) models, and an ensemble method, extreme gradient boosting (XGBoost), in predicting closing stock prices. This quantitative analysis utilizes recent AAPL stock data from the NASDAQ index. The chosen research questions (RQs) are: RQ1. What are the optimal hyperparameters for CNN-LSTM models in stock price forecasting? RQ2. What is the best architecture for CNN-LSTM models in this context? RQ3. How can ensemble techniques like XGBoost effectively enhance the predictions of CNN-LSTM models for stock price forecasting?

The research questions were answered through a thorough …

Improved Test Fixture For Collecting Microcontact Performance And Reliability Data, Turja Nandy, Ronald A. Coutu Jr., Rafee Mahbub

Electrical and Computer Engineering Faculty Research and Publications

Microelectromechanical systems (MEMS) ohmic contact switches are considered to be a promising candidate for wireless communication applications. The longevity of MEMS switches is directly related to the reliability and performance of microcontacts. In this work, an improved microcontact test fixture with high actuation rates (KHz) and highly precise position control (nm) and force (nN) control was developed. Here, we collected microcontact performance data from initial contact tests (ICT) and microcontact reliability data from cold switched tests (CST). To perform these tests with our test fixture, we fabricated MEMS microcontact test structures with relatively high Young’s modulus electroplated Nickel (Ni)-based, fixed–fixed …

Advances In Nanofiber Technology For Biomedical Application: A Review, Dipasree Bhowmick, Islam Uddin Shipu

Mechanical Engineering Faculty Publications

The application of nanofiber technology in the biomedical field has garnered significant interest due to its potential to revolutionize areas such as tissue engineering, wound healing, and antimicrobial treatments. This paper provides a comprehensive review of the recent advancements in nanofiber technology, particularly focusing on electrospinning and 3D printing methods that enable the fabrication of scaffolds mimicking the native extracellular matrix. These technologies have facilitated the development of nanofibers with high surface-to-volume ratios, adjustable porosity, and enhanced mechanical properties, tailored to meet specific biomedical needs. Despite their promising features, challenges such as the optimization of pore size for effective cell …

Reduction Of The Length Of Stay At The Emergency Department Of The Audie L. Murphy Hospital, Arwa Al Shikrian

Theses

We implemented the DMAIC framework (Define, Measure, Analyze, Improve, and Control) and Lean Six Sigma methods to reduce the length of stay (LOS) in the Emergency Department (ED) at Audie L. Murphy VA Hospital, a crucial issue affecting operational efficiency and patient care quality. This project was conducted in conjunction with an internship at the Hospital; our efforts were an integral part of a Green Belt project being conducted by Mr. Roarke Verkaik-Bushby, Hospital Administration Service, to

whom this author reported.

We employed quantitative research design, meticulously observing, measuring, and analyzing ED processes. We tracked patient flow, identified bottlenecks, and …

Sports Science: An Entrepreneurial Venture, Nicole J. Jones

Senior Honors Projects

In sports science, ensuring maximum athlete safety and optimizing data utilization are pivotal yet leave room for further work. My project, Unbeaten SafeWare, addresses these critical issues by focusing on two primary concerns: preventing heat-related and cardiac illnesses, which are significant causes of athlete fatalities, and enhancing the transparency and utility of sports data. This initiative involves developing a shirt integrated with sensors to monitor vital signs and an athlete management system to handle data input, storage, analysis, and accessibility for athletes.

The project has advanced through the efforts of a multidisciplinary team, which includes biomedical engineering undergraduates, two faculty …

Evaluation, Rating, And Numerical Modeling Of A Shock Mitigation Seat For High-Speed Craft Based On Laboratory Single Impact Testing, Darren Benn

UNLV Theses, Dissertations, Professional Papers, and Capstones

High-speed craft (HSC) are utilized in military and para-military maneuvers that are usually conducted in harsh environments. The Special Warfare Combatant-craft Crewmen (SWCC), a sub-unit of the United States Naval Special Warfare Command (NAVSOC), use an advanced HSC, known as the Combatant Craft Assault, to conduct coastal patrol and interdiction, and for infiltration and exfiltration of Navy SEALs. The United States Coast Guard, and the Drug Enforcement Agency (DEA), employ HSC for maritime patrol and to pursue ‘go-fast’ boats operated by contraband runners. In most of these intense applications, the mode of operation of the HSC results in planing. Planing …

Removal Of Permethrin And Bifenthrin Insecticides From Runoff Water By Activated Carbon Adsorption, Ernesto Hernandez

UNLV Theses, Dissertations, Professional Papers, and Capstones

Among the hundreds of pesticides and insecticides, pyrethroids-particularly permethrin and bifenthrin, have become very popular due to their high toxicity to insects and low toxicity to humans, leading to extensive use in both agriculture and urban areas. Pyrethroids have no discharge limits because of this, leading to a negative impact on surrounding ecosystems due to their high toxicity to fish and aquatic life. Due to their low solubility and long half-lives, they are prominent in the environment long after application with a high potential for getting transported in runoff water to nearby water bodies. In this study, DSR-C reactivated carbon …

Boron-Doped Diamond As A Resilient Electrode Material In Molten Salts, Hannah Katherine Patenaude

UNLV Theses, Dissertations, Professional Papers, and Capstones

Molten salt chemistry has a range of applications within nuclear technology, including for the Molten Salt Reactors (MSRs) and pyroprocessing to recover valuable actinides for energy and national security needs. However, the high-temperature, corrosive nature of molten salts makes them particularly challenging to deploy on an industrial scale and study in benchtop measurements. Material accountability and corrosion monitoring of MSR fuels are essential components to the successful deployment of MSRs, and electroanalytical techniques like cyclic voltammetry (CV) and spectroelectrochemistry (SEC) can provide a wealth of information to describe salt systems in situ. To perform such measurements, it is imperative to …

Final Design Of Legion Hall Revitalization In Potter, Nebraska, Madison Brennfoerder

Honors Program: Senior Projects (Public)

This project was conducted to renovate and revitalize the Legion Hall community center in the Village of Potter located in western Nebraska north of the Interstate. The work completed for this project can be separated into five disciplines: Hydrologic & Hydraulic Design, Geotechnical Analysis, Structural Analysis, Environmental Analysis, and Transportation Design. Legion Hall is a historical building within The Village of Potter which was built in 1917. The Village of Potter has recently acquired the rights to the hall and is seeking to revitalize the historical community center to increase tourism in the village.

Detection Of Deficiencies And Data Analysis Of Bridge Members With Deep Convolutional Neural Networks, Bennett Jackson

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

Concrete cracks and structural steel corrosion are two of the most common defects in bridges. Quantifying and classifying these defects provide bridge inspectors and engineers with valuable data for assessing deterioration levels. However, the bridge inspection process is typically a subjective, time intensive, and tedious task, as defects can be overlooked or in locations not easily accessible. Previous studies have investigated deep learning-based inspection methods, implementing popular models such as Mask R-CNN and U-Net. The architectures of these models offer certain advantages depending on the required task. This thesis aims to evaluate and compare Mask R-CNN and U-Net regarding their …

Breakaway Luminaire Pole Research, Jacob Conway

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

This document reports the efforts conducted to determine critical parameters and configurations for Manual for Assessing Safety Hardware 2016 (MASH) Test Level 3 (TL-3) compliant breakaway luminaire poles supported by slip bases, including identifying pole configurations with the potential to meet MASH TL-3 as well as recommending critical configurations for full-scale crash testing. A thorough literature review was conducted which included survey results collected from Midwest Pooled Fund state departments of transportation (DOTs), standard plans from state DOT’s, and past luminaire pole testing.

Numerical LS-DYNA models were developed for luminaire poles with 4-bolt slip base utilized by the Utah Department …

Sliding Markov Decision Processes For Dynamic Task Planning On Uncrewed Aerial Vehicles, Trent Wiens

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

Mission and flight planning problems for uncrewed aircraft systems (UASs) are typically large and complex in space and computational requirements. With enough time and computing resources, some of these problems may be solvable offline and then executed during flight. In dynamic or uncertain environments, however, the mission may require online adaptation and replanning. In this work, we will discuss methods of creating MDPs for online applications, and a method of using a sliding resolution and receding horizon approach to build and solve Markov Decision Processes (MDPs) in practical planing applications for UASs. In this strategy, called a Sliding Markov Decision …

Dynamic Impact Testing And Numerical Analysis Of Non-Proprietary Astm F2656-20 M50 Anti-Ram Barrier Components, Weston Kelley

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

In a post-9/11 world, hostile actors are using vehicles as weapons to inflict civilian casualties. Pedestrians, vulnerable road users, military personnel, and police may be targeted using a vehicle as a weapon. The United States Department of Defense (DoD) also utilizes Entry Control Facilities (ECFs) which are carefully designed transportation corridors to manage how threat vehicles are able to access military facilities. In 2004, DoD started to upgrade all ECFs using both passive and active barriers. Many anti-ram vehicle barriers were evaluated according to the criteria established in ASTM F2656, but to date few options are available which are (1) …

Mammary Epithelial Cell Derived Extracellular Vesicles Influence Tumorigenic Phenotype Suppression In Her2-Positive Breast Cancer Cells, Brenda Okereke

All Dissertations

On a global scale, breast cancer remains the most commonly diagnosed cancer in the world. In 2020 alone, there were over 2.3 million new cases of breast cancer seen and a total of 685,000 deaths globally, this represents 16% or 1 in every 6 cancer deaths seen in women. By 2040 it is projected that the breast cancer burden will rise by over 40% to exceed 3 million new cases a year. Further understanding of the underlying biology and mechanisms behind tumor progression and breast cancers such as HER2+ breast cancer would allow for new therapeutic treatment targets to emerge. …

“How Are High School Counselors Prioritizing The Information Relevant To Stem Career Preparation In Their Communication With Stem-Interested African American Students?”, Wysheka Austin

All Dissertations

Although African Americans and other minoritized groups have gradually increased in the number of students graduating with a Science, Technology, Engineering, and Mathematics (STEM) degree over the years, these groups remain underrepresented in STEM. Among the many factors contributing to the lack of representation is “college readiness,” which includes academic preparation and awareness of the necessary steps needed for college admission and career preparation [5]. South Carolina policy only considers academic preparation in their assessment of college readiness. To measure academic preparation of any student, the state relies on standardized test scores and advanced course taking without regard to subject. …

Novel Vector Assignment Approach For Inherent Strain Modeling Of Laser Powder Bed Fusion Manufacturing, Lucas M. Morand

All Dissertations

The expansion of the design space due to additive manufacturing (AM) has been a large motivator for the success of this family of processes. Despite the complexity of the physics in metal laser powder bed fusion AM causing significant stresses and strains in finished parts, the design advantages and subsequent performance improvements continue to drive the expansion of AM. Because the trial-and-error approach to AM part development is cost prohibitive, simulation of prints has become crucial. However, full thermo-mechanical simulation is susceptible to the same pitfall of time and computational cost in order to attain part-scale results. The development of …

Development Of Advanced Simulator-Based Metrics For Suturing Skills Assessment And Feedback, Simar Singh

All Dissertations

Vascular surgery demands highly skilled suturing to manipulate and connect delicate vasculature. However, inadequate methods for open suturing skills training necessitate efficient and objective methods to develop skills. To address this need, medical training simulators for objective surgical skills training are gaining popularity for their formative assessment.

This research details the development of a system to classify suturing performance and provide feedback on a suturing skills measurement and feedback platform (called the SutureCoach). The SutureCoach simulator offers a comprehensive assessment of skill through sensors measuring needle driver motions, membrane forces and torques, subcutaneous suture needle movement, and hand motions. We …

Mesenchymal Stromal Cell Response To Degenerated Intervertebral Disc-Like Ph, Kyle Cannon

All Dissertations

Intervertebral disc degeneration (IVDD) has become increasingly prevalent and is a common contributing factor to low back pain. There are currently no clinical treatment options for IVDD that alleviate the symptoms of IVDD while simultaneously promoting repair of IVD tissue. One treatment option being explored is intradiscal administration of mesenchymal stromal cells (MSCs). However, the microenvironment of the degenerating IVD places significant stress on both native IVD cells and implanted cells. There are several questions that need to be addressed which may help further inform the development of efficacious intradiscal MSC therapies for IVDD. These questions include: 1) Do MSCs …

Development Of Earthquake Hazard Prediction Software For South Carolina And Its Applications, Vishnu Saketh Jella

All Dissertations

This dissertation presents the development of earthquake hazard generation software, CarolinaShake and CarolinaADRS, for the state of South Carolina and its applications in the field of earthquake engineering. South Carolina is a seismically active state in the eastern United States, and there is a need to accurately quantify the earthquake hazard and incorporate it into the design of infrastructure systems. To achieve this objective, the South Carolina Department of Transportation (SCDOT) is actively supporting the initiatives to update its seismic design policies and procedures of civil infrastructure systems. As part of those initiatives, first, CarolinaShake, a Windows-based graphical user interface …

Crystalline Colloidal Arrays: Exploring Light-Matter Interactions, Haley W. Jones

All Dissertations

Understanding and manipulating quantum light-matter interactions, especially in the context of nanostructured environments, is highly critical for technological progress and inventive solutions in the fields of telecommunications, energy-efficient lighting, and cutting-edge quantum computing technologies. The fundamental interactions of photons with a surrounding environment directly impact the performance and efficiency of devices such as lasers, light-emitting diodes (LEDs), and quantum computing elements, which leverage the unique properties of confined structured environments. Since the late 1980s, the connection between a structured environment and the decay kinetics of an embedded fluorophore has been a highly debated and unresolved topic in the literature. More …

Identifying Temporomandibular Disorder Morphological Risk Factors Via Explainable Deep Learning And Multiscale Biomechanical Modeling, Shuchun Sun

All Dissertations

Clarifying multifactorial musculoskeletal disorder etiologies supports risk analysis and development of targeted prevention and treatment modalities. Deep learning enables comprehensive risk factor identification through systematic analysis of disease datasets but does not provide sufficient context for mechanistic understanding, limiting clinical applicability for etiological investigations. Conversely, multiscale biomechanical modeling can evaluate mechanistic etiology within the relevant biomechanical and physiological context. We propose a hybrid approach combining 3D explainable deep learning and multiscale biomechanical modeling; we applied this approach to investigate temporomandibular joint (TMJ) disorder etiology by systematically identifying risk factors and elucidating mechanistic relationships between risk factors and TMJ biomechanics and …

Design, Fabrication, And Characterization Of Advanced High-Power Single-Mode 9xxnm Semiconductor Lasers, Xiaolei Zhao

All Dissertations

This thesis presents the comprehensive design, fabrication, and demonstration of advanced high-power, high-efficiency single-mode semiconductor lasers operating at a wavelength of 9xxnm. We begin with the design of the laser epitaxial structure, serving as the cornerstone for achieving high-power high-efficiency lasers. Our methodology integrates a semi-analytical calculation model, which accounts for Longitudinal Spatial Hole Burning (LSHB) and Two-Photon Absorption (TPA) effects, facilitating a thorough exploration of how design parameters influence output power and conversion efficiency. This approach offers an effective and time-efficient epitaxial structure optimization strategy compared to conventional full 3D simulation models.

Subsequently, we demonstrate high-power, high-efficiency ridge waveguide …

Novel Nucleus Pulposus Biomaterial Development And Low Field Mri Assessment For Intervertebral Disc Degeneration, Mario Krussig

All Dissertations

Intervertebral disc degeneration (IVDD) is a prominent pathology in the modern world that causes debilitating pain for many patients. The onset of IVDD occurs in the nucleus pulposus (NP). NP biomaterials will play a vital role in mitigating the progression of IVDD. Within this work, we sought to synthesize a solubilized extracellular matrix (ECM)-based NP biomaterial. Utilizing pepsin or urea extraction, bovine NP ECM was successfully solubilized (SBNPs). SBNP formulations were characterized biochemically, evaluated for cytotoxicity, and down-selected for front-running formulations. Leading candidate SBNPs were incorporated into an alginate bead biomaterial model to determine the potential bioactivity with human adipose-derived …

Development And Application Of Discrete Element Models For Granular Materials - From Rigid Spheres To Complex-Shaped Flexible Particles With Breakage, Zakia Tasnim

All Dissertations

Granular materials, which can range from nanometers to centimeters, are widely encountered as particles or powders in nature and in engineered systems. Some examples of granular materials include sands, gravels, biomass feedstocks, rice grains, pharmaceutical pills, glass beads, and lunar or martian regolith simulants. The attributes of and the interactions between constituent particles dictate the bulk mechanical properties and behavior of granular materials. The discrete element method (DEM), a particle-based modeling technique, has become a useful numerical tool for modeling the bulk behavior (such as mechanical, flow, and breakage behavior) of granular materials, where interactions between the granular materials' individual …

Process-Structure-Property-Performance Modeling For Semicrystalline Thermoplastics And Composites, Tatiana Stepanova

All Dissertations

With a growing focus on reducing the adverse effects of transportation on the environment, industries are seeking fuel-efficient and sustainable solutions. Fuel efficiency can be improved in several ways, but structural lightweighting has demonstrated overall effectiveness. In this regard, thermoplastic composites and additive manufacturing (AM) thermoplastics have become viable candidates for use in the automotive industry, given the need for weight reduction and efficiency improvement.

The advantages of AM include simplifying supply chains, simplifying part geometry, and enabling mass customization. In order to design high-performance AM structures, extensive modeling and simulation are required. AM thermoplastics are similar to conventional manufacturing …