Engineering Commons^™

Understanding The Microstructure And Tribological Performance Of Cocrfeni-Based High Entropy Alloys, Ali Azarmi

All Theses

Due to their higher wear resistance compared to conventional alloys, high entropy alloys (HEAs) are now being considered as candidates for parts undergoing sliding contact during their lifetimes. While the engineering field has built some knowledge related to the performance of selected high entropy alloys, such as the CoCrFeNi alloy, more research is needed to determine if (how) expansions from four to five principal alloying elements alter the performance compared to the initial alloy. In this study, we started this research effort by investigating the relative performance of CoCrFeNiMn and CoCrFeNiTi with respect to CoCrFeNi. The two primary alloying elements …

Understanding The Challenges To Robotic-Assisted Surgery Adoption From The Perspectives Of The Human-Robot Interaction, Built Environment, And Training, Patrick A. Fuller

All Theses

Introduction: Robotic-assisted surgery (RAS) is a form of minimally invasive surgery that is increasing in both its adoption and development due to many perceived advantages such as tremor reduction and motion scaling. However, RAS is still relatively new and there are a variety of novel barriers and challenges to the adoption of these platforms. Objectives: This study aims to understand how the integration of RAS platforms impacts the interactions and outcomes of interactions between surgical team members to explore the barriers from three aspects critical to facilitating Robotic-assisted-surgery (RAS) adoption: the human-robotic interaction, built environment, and RAS training. Future …

Local Charge Distortion Due To Cr In Ni-Based Concentrated Alloys, Jacob Fischer

All Theses

Due to the presence of multiple elements consisting of a range of atomic radii, local lattice distortion (LLD) is commonly observed in concentrated (and high entropy) alloys. However, since these elements also have diverse electronegativities, recent works show that atoms can have a range of atomic charges. In this work, using density functional theory (DFT), we investigate electronic charge distribution in face centered cubic (FCC) Ni-based alloys and find significant charge-density distortion in HEAs. Specifically, Cr atoms have large charge density distortion that results in a wide range of bond lengths, atomic charges, and electronic density of states in Cr-containing …

Degradation Products And Microbial Communities Associated With The Conversion Of Five Long-Chain Fatty Acids Relevant For Anaerobic Co-Digestion Of Fog With Sludge, Claire Funk

All Theses

Anaerobic digestion is a technology that allows wastewater treatment plants to convert sludge to energy by recovering the biogas produced during the breakdown of proteins, carbohydrates, and lipids. Furthermore, adding fats, oils, and greases (FOG) through co-digestion with wastewater sludge can increase energy production as lipids have a higher methane yield than proteins and carbohydrates. However, adding FOG can also lead to operational problems in the digester due to the potential accumulation of certain long-chain fatty acids (LCFAs). Current research is limiting in the degradation pathways of prominent LCFAs in FOG and the microbial communities responsible for their degradation

The …

Hyperspectral Image Classification Of Bacteria Using A Deep Convolutional Neural Network, Bruce S. Vogelsberg Jr

All Theses

Hyperspectral imaging is a non-invasive imaging method capable of collecting both spatial and spectral information. However, because of the large volume of data collected, much of it is redundant or not useful for classification. Deep learning is a subset of machine learning that uses artificial neurons in a multilayered structure to learn representations from data. One of the main advantages of deep learning is the powerful feature extraction capabilities, which allow the model to learn both high- and low-level features. Convolutional neural networks are a type of deep learning model that have alternating convolutional and pooling layers capable of extracting …

Predicting The Ductility Of Tungsten Based Bcc Refractory High Entropy Alloys: A Computational Science Driven Study, Akshay Korpe

All Theses

Bcc refractory high entropy alloys (HEAs) are a relatively new category of metallic alloys that promise excellent irradiation resistance and strength retention at high temperatures but exhibit brittle behavior at room temperatures limiting their formability. Understanding the deformation mechanisms and predicting their ductility at room temperature is a topic of interest in contemporary research.

In this work, multiple independent ductility criteria for quantifying the ductility of these HEAs were studied, calculated and compared using Density Functional Theory (DFT) calculations and continuum mechanics frameworks. These ductility parameters were calculated for various W-Ta-Cr-V alloys and the trends were analyzed for each criteria …

Developing An Assessment Tool For Ideation Effectiveness: A Survey-Based Approach For The Shah’S Method Of Design Space Exploration, Venkat Jaya Deep Jakka

All Theses

The research is focused on creativity in engineering design. The goal is to understand if creativity in engineering design can be assessed using a less resource-intensive approach, specifically a survey, compared to design exercises. The survey builds on the metrics established by Shah and colleagues. The four metrics are Novelty, Quality, Variety and Quantity. The metrics are measured with the help of a design activity that is deployed to the participants. These metrics have been used in comparative analysis to assess treatments such as new design methods and personality types. However, the downside of the metrics is that they require …

Expandable Tissue-Engineered Living Surgical Pulmonary Heart Valve For Pediatric Patients, Jacob M. Lautenschlager

All Theses

Cardiovascular disease is the most common cause of mortality in developed countries, with 607.74 million cases globally in 2020.^1,2 Advances in medicine have changed the current demographic suffering from heart valve disease into an aging population suffering from degenerative heart valve disease, creating a growing population treated by surgical or transcatheter intervention.^3-6 Current treatments of valvular heart disease are therefore directed toward valve replacements for the adult population, leaving a treatment gap for pediatric patients suffering from heart valve disease.^7-10

Congenital heart defects are defined as structural abnormalities of the heart or intrathoracic great vessels and are …

Training Uav Teams With Multi-Agent Reinforcement Learning Towards Fully 3d Autonomous Wildfire Response, Bryce Hopkins

All Theses

As climate-exacerbated wildfires increasingly threaten landscapes and communities, there is an urgent and pressing need for sophisticated fire management technologies. Coordinated teams of Unmanned Aerial Vehicles (UAVs) present a promising solution for detection, assessment, and even incipient-stage suppression – especially when integrated into a multi-layered approach with other recent wildfire management technologies such as geostationary/polar-orbiting satellites and CCTV detection networks. However, there remains significant challenges in developing the necessary sensing, navigation, coordination, and communication subsystems that enable intelligent UAV teams. Further, federal regulations governing UAV deployment and autonomy pose constraints on real-world aerial testing, creating a disconnect between theoretical research …

Proportioning And Performance Of Ultra-High Performance Concrete (Uhpc) For High Friction Surface Treatment (Hfst) On Pavement And Bridge Decks, Adam R. Biehl

All Theses

High Friction Surface Treatment (HFST) is a roadway remediation technique used to improve pavement’s coefficient of friction, to enhance roadway safety. The application of HFSTs has repeatedly demonstrated the ability to significantly reduce crashes in both wet and dry conditions. Typically, epoxy-resins and calcined bauxite aggregate are used in HFST treatment. However, the high material costs and scarcity of calcined bauxite render this form of HFST an expensive and limited option for roadway rehabilitation. Therefore, the identification of alternative binders and HFST aggregates is needed for broad scale implementation. One potential alternative binder is Ultra-High-Performance Concrete (UHPC), a specialty cementitious …

Impact Of Nitrogen Species On Algal Carbon Capture, Lauren J. Todd

All Theses

Increasing global carbon emissions from fossil fuel combustion and the resulting detrimental effects of climate change have created a need for atmospheric carbon drawdown. Biological-based carbon capture not only sequesters carbon dioxide (CO₂) but also provides a sustainable source of biomass for biofuels and biomaterials. Thus, the aim of this research was to examine freshwater green algal growth with total ammoniacal nitrogen (TAN) and nitrate nitrogen (NO₃-N) sources at high pH for improving carbon capture potential. The following objectives were accomplished: nitrogen uptake was identified as simultaneous or sequential, the effect of TAN and NO_{3 …}

Extraction Of Neutron-Gamma Irradiated Diffusion Pump Oils, Cooper L. Tillman

All Theses

This work successfully demonstrates solvent extraction methods for separation of oil from the by-products when two commercially available vacuum pump oils were exposed to an intense neutron and gamma-ray radiation environment. Nuclear fusion power at a commercial scale has accelerated the need for radiation resistant vacuum technology, such as oil-based diffusion pumps. Polyphenyl ether and aromatic silicone oils were irradiated at the Rhode Island Nuclear Science Center (RINSC) up to MGy absorbed doses with neutron and gamma-ray radiation. Solvent extractions were performed using hexane and isopropanol to characterize the oil extraction as a function of total absorbed dose. The by-products …

Hydrogen Isotope Exchange On Diffusion Pump Oils, Carson G. Allen

All Theses

The extent of isotopic exchange of deuterium and tritium with protium atoms in hydrocarbon pump oil was investigated as a means to quantify the chemical stability of a mineral oil, a silicone oil, and a polyphenyl ether oil as candidates for implementation in a diffusion pump. In its target application at a fusion power plant, a chemically stable and radiation hard oil offers substantial reductions in tritium inventory, electrical consumption, and operational pump expenses over alternate solutions for vacuum induction. Select oils were introduced to deuterium and tritium isotopes in a high temperature environment, analogous to an operating vacuum pump. …

Using Efficient Vision Transformers To Improve Perception Systems In Autonomous Off-Road Vehicles, Adam S. Pickeral

All Theses

The development of autonomous vehicles has become one of the greatest research endeavors in recent years. These vehicles rely on many complex systems working in tandem to make decisions. For practical use and safety reasons, these systems must not only be accurate, but also be quick to make decisions. In Autonomous Vehicle research, the environment perception system is one of the key com- ponents of development. The environment perception system allows the vehicle to understand its surroundings using cameras, light detection and ranging (LiDAR), and other sensor systems or modalities. Deep learning computer vision algorithms have shown to be the …

Advancing Unmanned Ground Vehicle Path Planning With Quantified Map Uncertainty, Israel Afriyie

All Theses

This thesis addresses the complex challenge of path planning for Unmanned Ground Vehicles (UGVs) in areas where traditional navigation systems are inadequate, such as unstructured or off-road military zones. Recognizing the limitations of current path planning algorithms, which primarily focus on optimizing for the shortest path and often fail to account for variability and risks, this research proposes an enhanced Hyperstar algorithm. This approach not only considers the fastest route but also integrates maximum delays and visibility risks into its computation, ensuring a balance between swift mission completion and concealment from adversaries.

Utilizing terrain maps and incorporating uncertainties in map …

Path-Choice-Constrained Bus Bridging Design Under Urban Rail Transit Disruptions, Yiyang Zhu, Jian Gang Jin, Hai Wang

Research Collection School Of Computing and Information Systems

Although urban rail transit systems play a crucial role in urban mobility, they frequently suffer from unexpected disruptions due to power loss, severe weather, equipment failure, and other factors that cause significant disruptions in passenger travel and, in turn, socioeconomic losses. To alleviate the inconvenience of affected passengers, bus bridging services are often provided when rail service has been suspended. Prior research has yielded various methodologies for effective bus bridging services; however, they are mainly based on the strong assumption that passengers must follow predetermined bus bridging routes. Less attention is paid to passengers’ path choice behaviors, which could affect …

Divergence Measures And Aggregation Operators For Single-Valued Neutrosophic Sets With Applications In Decision-Making Problems, Surender Singh, Sonam Sharma

Neutrosophic Systems with Applications

Single-valued neutrosophic sets (SVNSs) facilitate the representation of uncertain information more extensively than conventional methods. The study of divergence measures of SVNSs is important due to their applications in different areas like multi-criteria decision-making (MCDM), pattern recognition, cluster analysis, machine learning, etc., In this paper, we introduce a divergence measure for SVNSs. The suggested divergence measure is applied to cluster analysis for the classification of imprecise data. For establishing the reasonability and advantage of the suggested divergence measure in a clustering problem over the existing measures, a comparative assessment is also presented. Furthermore, we introduce, an inferior ratio method for …

Smart Zoning Control For Air Conditioning Systems, Octavio Gomes Diaz

Mechanical Engineering Theses

Nearly 45% of the energy consumed in residential buildings goes for Heating, Ventilation, and Air Conditioning (HVAC). Typical HVAC systems are mostly controlled by one thermostat that is usually located in the living room. This means that the HVAC system is running without consideration of the thermal conditions in the other rooms (zones), which might be colder (or warmer). Colder zones in the summer indicate that a lot of energy is wasted, and warmer zones mean that the HVAC system can’t produce a good comfort level. Therefore, zoning was introduced into relatively recent HVAC systems. Zoning in HVAC systems uses …

Real-Time Gun Detection In Video Streams Using Yolo V8, Harish Kumar Reddy Kunchala

Electronic Theses, Projects, and Dissertations

In this research, we advance the domain of public safety by developing a machine learning model that utilizes the YOLO v8 architecture for real-time detection of firearms in video streams. A diverse and extensive dataset, capturing a range of firearms in varying lighting and backgrounds, was meticulously assembled and preprocessed to enhance the model's adaptability to real-world scenarios. Leveraging the YOLO v8 framework, known for its real-time object detection accuracy, the model was fine-tuned to accurately identify firearms across different shapes and orientations.

The training phase capitalized on GPU computing and transfer learning to expedite the learning process while preserving …

Crime Data Prediction Based On Geographical Location Using Machine Learning, Sai Bharath Yarlagadda

Electronic Theses, Projects, and Dissertations

This project employs machine learning methods like K Nearest Neighbors (KNN), Random Forest, Logistic Regression, and Decision Tree algorithms to monitor crime data based on location and pinpoint areas with risks. The project implements and tunes the four models to improve the precision of predicting crime levels. These models collaborate to offer a trustworthy evaluation of crime patterns. K Nearest Neighbors (KNN) categorizes locations by examining the proximity of data points considering coordinates and other factors to identify trends linked to increased crime data. Logistic Regression gauges the likelihood of crime incidents by studying the connection, between factors (like location …

Development Of Recyclable Materials For Industry Using Non-Petroleum Feedstocks, Terra M. Miller-Cassman

Boise State University Theses and Dissertations

Plastics have been an essential material for over 80 years, yet we have been unable to manage the accumulation of plastic waste. The available solutions for recycling or replacing plastics are complex and costly, and thus have not kept pace with the increasing quantity of plastic waste. This dissertation describes a comprehensive, materials design approach to solving the current and future challenges of plastic waste. Recycled and recyclable materials are developed using commercial feedstocks to reduce barriers for industry adoption. In one approach, unsorted municipal solid waste is compressed at a low temperature and pressure to form rigid composite boards …

Harnessing Nlp And Large Language Models For Pattern Discovery And Information Extraction In Electric Health Reports, Mina Esmail Zadeh Nojoo Kambar

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this work, we report on a series of natural language processing tools and models to improve the efficiency and accuracy of information discovery from clinical trials and pharmacological studies. Our main contributions are: 1. The development of an open-source platform Tri-AL that • Enables dynamic tracking of clinical trials information over time, • Excels in data visualization and user interaction with a particular emphasis on enhancing the analysis and representation of race and ethnicity data to foster equity in clinical research, and • Includes a predictive model utilizing machine learning to decipher drug mechanisms of action. 2. Heterogeneous Graph …

Investigating Productivity Of Modular Buildings, Sibgat Mehedi Hasan

UNLV Theses, Dissertations, Professional Papers, and Capstones

The modular construction industry has grown substantially, yet understanding of the relationships between project categories, sizes, and productivity remains limited. This study investigates these relationships in both permanent and relocatable modular construction projects across different sectors, including multifamily housing, dormitories, healthcare, education, retail, office, and workforce housing. Data from 303 permanent and 188 relocatable projects in the Modular Building Institute database were analyzed using Kendall's tau-b correlation and linear regression analyses. Key findings reveal that permanent projects outnumber and are generally larger than relocatable ones, with education being the most common project type. Significant positive correlations between project size and …

Development Of A Passive Drag Reduction Modification For The 25° Ahmed Body Using Large Eddy Simulation, Skylar Polek

UNLV Theses, Dissertations, Professional Papers, and Capstones

In the field of automotive aerodynamics, the Ahmed body is a generic vehicle-shaped bluff body which is meant to generalize the rear end of fastback and hatchback vehicles. Specifically, an Ahmed body with a rear slant angle of 25° has seen common use due to its resemblance of common rear windshield shapes as well as its notoriously complex wake structure. This research focuses on simulating the flow over a 25° in various situations with an ultimate goal of drag reduction. First, a simple benchmark of the k-ω shear stress transport (SST), large eddy simulation (LES) with the Smagorinsky-Lilly subgrid scale …

Dynamic Model Of An Overhead Crane, Leonard Ruesga

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis a novel spatial model of an overhead crane was developed. The model includes: bridge, trolley, driving and follower wheels for the bridge and trolley, drum, cable, and the payload. The model accounts for the winding/unwinding of the cable around the drum as the payload is raised/lowered. The cable and the payload were considered as rigid bodies with uniformly distributed mass. First, the kinematic equations of the model were developed by using constraint equations. Second, the dynamic equations were derived through use of Newton’s Laws. Developing the rotational dynamic equations required the determination of the angular momentum vectors …

A Heuristic Approach To Operations And Control Of Btm-Ders For Bill Management And Grid Services, Md Arshad Rashid Shaon

UNLV Theses, Dissertations, Professional Papers, and Capstones

Behind-The-Meter (BTM) distributed energy resources (DERs) have emerged as a critical and transformative force within the energy sector. These decentralized energy assets, which include solar photovoltaic (PV) systems, battery energy storage systems (BESS), and thermostatically controlled loads (TCLs), are increasingly essential for empowering customers by granting them greater control over their energy production and consumption, thereby reducing reliance on centralized power sources. Additionally, they have the potential to play a pivotal role in enhancing grid resilience by providing grid services. This study investigates the management of customer electricity bills and grid services through the integration of various BTM-DERs, particularly solar …

Image Processing Techniques For Water Droplet Penetration Time And Contact Angle Estimation, Sai Balaji Jai Kumar

UNLV Theses, Dissertations, Professional Papers, and Capstones

Water droplet behavior on soil surfaces plays a critical role in numerous environmental processes, including soil erosion, hydrological dynamics, and ecosystem health. Accurate characterization of soil water repellency, quantified by parameters such as water droplet penetration time (WDPT) and contact angles (WDCA), is essential for informed decision-making in agricultural management, forestry practices, and land-use planning. Despite the significance of these parameters, challenges exist in reliably estimating them due to the complex and dynamic nature of soil-water interactions. This thesis address challenges in estimating WDPT and WDCA, by leveraging state-of-the-art image processing techniques and machine learning algorithms. The research focuses on …

Comparing Gas Composition From Fast Pyrolysis Of Live Foliage Measured In Bench-Scale And Fire-Scale Experiments, David R. Weise, Thomas H. Fletcher, Timothy J. Johnson, Wei Min Hao, Mark Dietenberger, Marko Princevac, Bret W. Butler, Sara S. Mcallister, Joseph J. O'Brien, E Louise Loudermilk, Roger D. Ottmar, Andrew T. Hudak, Akira Kato, Babak Shotorban, Shankar Mahalingham, Tanya L. Myers, Javier Palarea-Albaladejo, Stephen P. Baker

Faculty Publications

Background. Fire models have used pyrolysis data from oxidising and non-oxidising environments for flaming combustion. In wildland fires pyrolysis, flaming and smouldering combustion typically occur in an oxidising environment (the atmosphere). Aims. Using compositional data analysis methods, determine if the composition of pyrolysis gases measured in non-oxidising and ambient (oxidising) atmospheric conditions were similar. Methods. Permanent gases and tars were measured in a fuel-rich (non-oxidising) environment in a flat flame burner (FFB). Permanent and light hydrocarbon gases were measured for the same fuels heated by a fire flame in ambient atmospheric conditions (oxidising environment). Log-ratio balances of the measured gases …

Transient Heat Transfer To Rolling Or Sliding Drops On Inclined Heated Superhydrophobic Surfaces, Joseph Furner, Daniel Maynes, Brian D. Iverson, Julie Crockett

Faculty Publications

The thermal transport to drops that roll or slide down heated superhydrophobic surfaces is explored. High-speed infrared imaging is performed to provide time-resolved measurement of the heat transfer to the drop. Data are obtained for drops moving along smooth hydrophobic and structured superhydrophobic surfaces. Both post and rib style structures with surface solid fractions ranging from 0.06 to 1.0 are considered. The inclination angle of the surfaces was varied from 10 deg to 25 deg, and the drop volume was varied from 12 to 40 µL. The measurements reveal that the drop speed is a strong function of both the …

Magnetic Sensor Compensation Utilizing Factor Graph Estimation, Frederic W. Lathrop, Clark N. Taylor, Aaron Nielsen

Faculty Publications

Recently, there has been significant interest in the ability to navigate without GPS using the magnetic anomaly field of the Earth (magnav). One of the key technical bottlenecks to achieving magnav is obtaining an accurate magnetic sensor calibration, taking into account own-ship and sensor effects. The Tolles-Lawson magnetic calibration method continues to be the industry standard and was developed when airborne magnetic survey aircraft were first employed over 70 years ago. In this paper, we present a magnetic calibration algorithm based on a factor graph optimization using inertial measurements as well as inputs from both a vector and scalar magnetometer. …