Digital Commons Network^™

Estimating The Possible Qpos Of M87* From The Parameters Of A Hairy Kerr Black Hole, Orhan Donmez, Fatih Dogan

Materials Science and Engineering Faculty Research & Creative Works

In this paper, we study the dynamics of the shock cone formed around a hairy Kerr black hole due to Bondi– Hoyle–Lyttleton (BHL) accretion and investigate the quasi-periodic oscillations (QPO) behaviors resulting from the black hole-cone interaction, aiming to predict the QPO frequencies that may occur around the M87∗ black hole. To achieve this, we use the hairy Kerr black hole parameters consistent with the observed shadow parameters of M87∗ as initial conditions in numerical simulations, revealing the structure of the resulting shock cone and QPOs in a strong gravitational field. Numerical calculations show that the deviation of …

Hafnium Oxide Coating To Improve The Oxidation Behavior Of Zirconium Diboride, Jan E. Förster, William G. Fahrenholtz, Gregory E. Hilmas, Ravisankar Naraparaju

Materials Science and Engineering Faculty Research & Creative Works

Hafnium dioxide (HfO₂) coatings were successfully deposited on zirconium diboride (ZrB₂) using reactive magnetron sputtering. After the oxidation at 1500°C or 1600°C, the mutual dissolution of HfO₂ and thermally grown ZrO₂ was observed which has resulted in the formation of a mixed oxide zone. As the enrichment of the mixed oxide zone by ZrO₂ progresses, monoclinic/tetragonal phase transition temperature of ∼1790°C for nominally pure HfO₂ moves towards ∼1500 °C. Finally, the inevitable phase transition from monoclinic to tetragonal structure results in the development of cracks, pores, and gaps within the mixed oxide …

Machine Learned Interatomic Potentials For Ternary Carbides Trained On The Aflow Database, Josiah Roberts, Biswas Rijal, Simon Divilov, Jon Paul Maria, William G. Fahrenholtz, Douglas E. Wolfe, Donald W. Brenner, Stefano Curtarolo, Eva Zurek

Materials Science and Engineering Faculty Research & Creative Works

Large-density functional theory (DFT) databases are a treasure trove of energies, forces, and stresses that can be used to train machine-learned interatomic potentials for atomistic modeling. Herein, we employ structural relaxations from the AFLOW database to train moment tensor potentials (MTPs) for four carbide systems: CHfTa, CHfZr, CMoW, and CTaTi. The resulting MTPs are used to relax ~6300 random symmetric structures and are subsequently improved via active learning to generate robust potentials (RP) that can relax a wide variety of structures, and accurate potentials (AP) designed for the relaxation of low-energy systems. This protocol is shown to yield convex hulls …

A General Model For The Ductility Of Intermetallics Applied To Fe-Co Alloys, Wesley Everhart, Joseph Newkirk

Materials Science and Engineering Faculty Research & Creative Works

The mechanical properties, specifically ductility, of high performing soft magnets such as Fe-Co alloys are a limiting factor to their broader use in a number of systems. The understanding of the mechanical robustness in these materials is currently insufficient to be able to support the growing interest in applications such as magnetic shielding or electric motors. Fe-Co alloys provide the highest commercially available magnetic saturation and high magnetic permeability but have very poor ductility. The addition of vanadium to these alloys has allowed for significant commercialization and some ductility improvements, but the fundamental reasons for the observed improvements are not …

Optimisation Of Open Pit Slope Design Considering Groundwater Effects Using Particle Swarm Optimisation And Scaled Boundary Finite Element Method, Dakshith Ruvin Wijesinghe, Ethmadalage Perera, Ean Hin Ooi, Sundararajan Natarajan, Taghi Sherizadeh, Ean Tat Ooi

Mining Engineering Faculty Research & Creative Works

Slopes are a crucial structure in open pit mines. Their design has implications on the economic, safety and environmental operation of the mining industry. Designing stable slopes can be challenging due to the complexities introduced by the stratigraphy and hydrology of the strata. With rising commodity costs and inflation rates, mining operating costs are increasing. Reducing operational costs is necessary for mining industries to remain competitive. While steepening the pit slope can decrease stripping materials and save money, it also increases the risk associated with slope surges. Therefore, optimizing slopes is crucial for both financial and safety reasons. Numerical models …

Work-Stealing Scheduler For Parallel Cache-Adaptive Algorithms, Chuqi Jiang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Modern computing systems with hierarchical memory structures, such as multiple cache levels, main memory, and external storage, pose significant challenges in optimizing memory usage for algorithm efficiency. Traditional models like the Disk Access Model (DAM) and advancements such as cache-oblivious algorithms have focused on minimizing memory transfers without requiring explicit knowledge of memory hierarchy parameters. However, these approaches assume fixed memory sizes and exclusive cache access, limiting their applicability in real-world, shared-memory environments where memory allocations fluctuate. To address these limitations, cache-adaptive algorithms were developed to dynamically adjust to changing memory profiles, enabling near-optimal performance even in multi-process systems. While …

A Data-Driven Approach For Automated Multi-Site Competitive Facility Location, Ming Hui Tan, Kar Way Tan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This paper addresses the challenge of optimal retail expansion in competitive urban environments through a novel approach to the Competitive Facility Location (CFL) problem. Traditional methods for solving CFL problems often struggle with large-scale scenarios, relying on manual pre-selection of candidate sites and imposing limitations on the number of new locations. Our approach leverages Adaptive Large Neighborhood Search (ALNS) enhanced with data enrichment techniques, including community detection on road networks and population weighting based on mobility data. We developed two ALNS variants: Community Geometric Centroid (CGC-ALNS) and Population Weighted Centroid (PWC-ALNS). These methods automate site selection, eliminating manual pre-selection while …

Introducing The Second-Order Features Adjoint Sensitivity Analysis Methodology For Neural Ordinary Differential Equations—Ii: Illustrative Application To Heat And Energy Transfer In The Nordheim–Fuchs Phenomenological Model For Reactor Safety, Dan Gabriel Cacuci

Faculty Publications

This work presents an illustrative application of the newly developed “Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-FASAM-NODE)” methodology to determine most efficiently the exact expressions of the first- and second-order sensitivities of NODE decoder responses to the neural net’s underlying parameters (weights and initial conditions). The application of the 2nd-FASAM-NODE methodology will be illustrated using the Nordheim–Fuchs phenomenological model for reactor safety, which describes a short-time self-limiting power transient in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted. The representative model responses that will …

Towards Verified Vision-Based Neural Network Controllers For Autonomous Lane-Following, Xinhang Ma

McKelvey School of Engineering Graduate Student Theses & Dissertations

Vision-based neural network controllers have shown promising results in autonomous lane-following tasks, but verifying their safety properties remains a significant challenge due to the high dimensionality of image inputs. This thesis designs an approach to enable formal verification of vision-based lane-following controllers by first developing an end-to-end autonomous system combining deep learning-based lane detection with reinforcement learning control. To enable formal verification, we introduce a generator-based framework that bridges the gap between high-dimensional image space and low-dimensional vehicle states, allowing us to leverage existing verification tools while maintaining the vision-based nature of the controller.

We further enhance our verification framework …

A Low-Cost Microvascular Phantom For Photoacoustic Imaging Using Loofah, Jinhua Xu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Existing photoacoustic phantoms are inadequate for mimicking the complex microvascular structures found in human tissue due to their inability to replicate varying sizes and distri- butions of vasculature. This limitation underscores the need for a new material capable of replicating intricate microvascular networks. In this thesis, we introduce loofah as a novel natural phantom material with complex fiber networks ranging from 50 to 400 μm, enabling the fabrication of phantoms with controlled optical properties comparable to those of human microvasculature.

By incorporating a controllable chromophore into the loofah material, we adjusted its ab- sorption properties to match desired specifications. The …

Real-Time Predictive Analytics For Healthcare Monitoring And Terrain Classification Using Data Streaming And Online Learning, Ayemon Baraka

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis develops a scalable, real-time predictive framework aimed at improving outcomes in healthcare monitoring and gait classification. Specifically, it addresses two primary applications: early detection of cardiovascular events, myocardial infarction (MI) and arrhythmia, through continuous analysis of ECG data streams; and adaptive terrain classification from gait data. Utilizing data streaming technologies such as Apache Kafka and Apache Spark, coupled with machine learning models, this framework enables near real-time and precise predictions from high-throughput, real-time data. Furthermore, the integration of online learning frameworks, including the River API and TensorFlow I/O, allows for continuous model adaptation, enhancing the system’s responsiveness and …

Biological Reduction Of Mixed Oxyanions In Wastewater Brine, Katherine J. Earp

UNLV Theses, Dissertations, Professional Papers, and Capstones

Treatment of contaminated brine water is an area of active research spurred by the use of advanced treatment technologies, such as membrane separation, reverse osmosis, ion exchange, etc. for water reuse and recycling, which has become critical due to the impact of climate change on water resources throughout the globe. Biological reduction of harmful organic and inorganic pollutants in water has been demonstrated as an effective method for water and wastewater treatment and would be a potential technology for brine treatment. However, biodegradation of contaminants in high salinity waters is challenging because most microbial communities cannot survive brine environments. The …

Understanding Failure Mechanisms For Two Colorectal Anastomosis Techniques, Youssef Sherif Sadek Fahmy

UNLV Theses, Dissertations, Professional Papers, and Capstones

Colorectal Surgery continues to be one of the most common gastrointestinal surgeries performed in the US. A common complication known as Anastomotic Leakage (AL) that threatens up to 30% of patients with this surgery. Many cases of AL can decrease the quality of life for patients or extensively extend hospital stays, and in many cases, lead to death. Researchers have studied this complication in clinical trials, yet few studied the mechanics of stapled anastomosis in controlled environments. The purpose of this research was to understand the mechanical interaction between the staples and the tissue, and to eventually apply it in …

Uptake Of Contaminants Of Emerging Concerns (Cecs) By Plants Irrigated With Recycled Waters, Abid Hussain

UNLV Theses, Dissertations, Professional Papers, and Capstones

The increasing demand for water in arid and semi-arid regions necessitates the use of recycled water (RW) for irrigation. RW is a viable alternative to conventional irrigation water at most locations, but it can be a major route for contaminants of emerging concerns (CECs) to be taken up by the tissues of food crops, thereby leading to their subsequent entry into the food chain. CECs include pharmaceuticals, personal care products, and industrial chemicals that are generally present at low concentrations in environmental waters, hence their common designation as trace organic compounds (TOrCs), and CECs also include microbiological constituents such as …

Non-Contact Acoustic Emission Detection Of Rail Defects Using Air-Coupled Sensors, Lei Jia

UNLV Theses, Dissertations, Professional Papers, and Capstones

Rail defects, whether internal or external, present significant safety risks. Acoustic Emission (AE) technology has emerged as a promising technique for monitoring damage progression and detecting these rail defects. This project addresses this critical concern by testing air-coupled optical microphones for non-contact AE detection. The goal of this research is to investigate AE signal characteristics using both rail-mounted and vehicle-mounted methods, establishing the understanding of AE signals in relation to defects and their effectiveness in identifying them.

This research focused on investigating air-conduct sensors in the lab-controlled pencil lead break (PLB) test. The objective was to evaluate the propagation characteristics …

Control Of X-Delta Arm And Self-Leveling Robot Systems For Uav Applications, Prathibha Sobha

UNLV Theses, Dissertations, Professional Papers, and Capstones

The water droplet penetration test (WDPT) is an environmental assessment method for analyzing soil properties by measuring the penetration of water droplets into soil. This test provides insights into soil moisture retention and resilience, especially valuable in fire-prone or arid regions where soil recovery and erosion control are essential. Although this project does not conduct an actual WDPT, it investigates two key robotic systems designed to support such applications: an X-delta robot arm, which simulates precise droplet delivery patterns, and a self-leveling platform that ensures stability on uneven terrain, where the X-delta robot is mounted. Together, these systems examine the …

Removal Capabilities Of Zeolite And Zero Valent Iron With High-Level Waste Tank Radionuclides And Metals: Cesium, Strontium And Chromium, Colette R. Towles

UNLV Theses, Dissertations, Professional Papers, and Capstones

High level nuclear waste (HLW) has been disposed for temporary storage in underground steel tanks at the Department of Energy Nuclear sites. For example, at the Hanford Site, WA, and Savannah River Site (SRS), SC, HLW account for eighty-eight million gallons (Mgal) and 450 million Curies (MCi) of radioactivity. In the early nuclear activity at Hanford, the waste was discharged to single-shell steel tanks, and the lack of secondary containment allowed leaks, contaminating soil and groundwater. Despite tremendous efforts to stabilize the liquid waste at nuclear sites, treatment is complex, costly, and time-consuming; therefore, HLW may have to be stored …

Integrating Deep Traffic Prediction And Environmental Impact Assessment Using Noisy Real-World Data In Las Vegas, Tarek Bin Zahid

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis introduces an integrated framework for advanced traffic prediction and real-time emission estimation, designed to aid urban planning and environmental monitoring. Utilizing a graph-based transformer model, it predicts traffic conditions across the Las Vegas road network, drawing on spatial and temporal data from a large-scale sensor network. The study significantly expands the dataset from 26 to approximately 900 sensors, enhancing predictive accuracy and regional coverage. Inspired by masking techniques and strategies tailored to incomplete datasets, the model effectively handles real-world, noisy data without relying on resource-intensive imputation. Innovative training approaches enable robust traffic flow predictions despite missing or imperfect …

Tracking Joint Movement Using Optical Flow, Isabella Paperno

UNLV Theses, Dissertations, Professional Papers, and Capstones

We developed an algorithm that aims to move us closer to detecting early signs of arthritis. The program processes and analyzes X-ray videos using coyote and dog cadavers as models to examine the range of motion around the hip and connecting joints using optical flow techniques that track motion and velocity. We focus on how optical flow techniques track embedded metal markers and verify accuracy through comparisons with XMALab (X-ray motion analysis lab). Once proven as an accurate alternative, the focus will switch to markerless tracking and become a proof-of-concept for optical flow to be used in place of XMALab, …

Mechanically Cost-Effective Approach For Bipedal Walking In Robots Using Instantaneous Collision Angle, Smit R. Patel

UNLV Theses, Dissertations, Professional Papers, and Capstones

Humans, as bipedal locomotors, are effective at reducing the mechanical cost of transport (CoTmech) by adopting movement strategies and gaits that minimize energy expenditure for a given distance. By using different gaits at different speeds, leveraging their long spring-like tendons and muscle elasticity which store and release energy during movement, humans reduce the mechanical effort required for locomotion. Current locomotion solutions offered in bipedal robots, based on legacy walking and running gait models, are not great at energy efficiency unless walking at very low speeds. Additionally, the control system of robots, designed to ensure stability and adaptability, requires substantial resources, …

Reproducible Research Data Pipelines – Case Study Of Bubble Collapse In Subcooled Nucleate Pool Boiling, Blake Naccarato

UNLV Theses, Dissertations, Professional Papers, and Capstones

Vapor bubble collapse is relevant to the study of subcooled nucleate boiling, as can occur in power plants and missile systems, in studies of wear due to cavitation, and even in the study of hydrothermal vents in the Earth sciences. Empirical correlations relate the rate of bubble collapse to thermal conditions of the subcooled fluid, and one may choose to produce a purpose built correlation for any process. However, they are time and resource intensive due to the data and process requirements for automated bubble tracking. A reproducible research data pipeline has been developed to discriminate between existing correlations for …

Prediction Of Cost And Schedule Changes In Transportation Projects Through Historical Bid And Change Order Document Analysis – Using Oklahoma Dot Project Cases., Rabin Shrestha

UNLV Theses, Dissertations, Professional Papers, and Capstones

Construction bid documents encompass project specifications, drawings, schedules, and other critical details and are the foundation for project bidding and execution. Accurate bid documents are essential to ensure project bids are competitive, realistic, and aligned with requirements. However, bid documents are susceptible to risks from various sources. Failure to identify and rectify these risks can result in inaccurate cost estimates and higher bids. Therefore, identifying and resolving risks within bidding or contract documents are of utmost importance. While prior research has shed light on potential risk factors within the bid documents, a noticeable gap remains in the literature regarding identifying …

Tac-It An Affective Computing User Interface Design, Andrew Biron

Theses and Dissertations

TAC-IT affective computing user-interface design is an independent computer peripheral that is a tool to be utilized to obtain a user’s self-reported emotional state in real-time. Doctor Rosalind Picard first coined and used the term affective computing in her paper Affective Computing [Picard, R. (1995)]. Affective Computing is defined as the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer science, psychology, and cognitive science. Since that time, areas of research have expanded exponentially, and areas of interest include how to trigger emotions in a test …

Building Safely: How Spanish Specific Safety Can Impact Job Sites, Luis D. Aguilar Montano

Construction Management

This project explores how Spanish Specific Safety Training is being approached in the construction industry, with an attempt to identify some possible issues associated with language barriers and accessibility to these trainings. This research involved data collection through thirty analytical surveys, in addition to conducting three semi-structured interviews with construction workers and supervisors. The focus of the data collection was to gain insights into several key areas, including training accessibility, workplace injuries, language barriers, and worker comfort. The survey results indicated strong support for Spanish-language safety training, with respondents recognizing its potential to improve safety and overall worker comfort. Many …

Harmonizing Vaccine And Infrastructure Development To Tame Cholera Outbreaks Across Africa, Amira Mohamed Taha, Hussam Mahmoud, Emad M. Hassan, Mohamed M. Ghonaim

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Vaccines and clean water shortages continue to give rise to cholera outbreaks in Africa. Coordinated efforts to increase vaccine distribution and improve physical infrastructure are needed while considering future outbreaks and water demands due to conflicts and climate events.

Impact Of Electrical Testing Strategies On The Performance Metrics Of Bio-Organic-Based Resistive Switching Memory, Muhammad Awais, Hao Zhe Leong, Nadras Othman, Mohamad Danial Shafiq, Feng Zhao, Kuan Yew Cheong

Electrical and Computer Engineering Faculty Research & Creative Works

Resistive Random-Access Memory (ReRAM) is considered as one of the most promising non-volatile memory technologies because of its high scalability, fast switching speed, and low power consumption. While many review papers are focused on investigating material types, material properties, device fabrication methods, and device structures, the influence of electrical testing strategies on ReRAM performance has yet been reviewed, particularly for bio-organic-based ReRAM. This review compiled, analyzed, and discussed how compliance current, voltage sweep rate, voltage sweep range, and voltage sweeping direction affect the ON/OFF ratio, read memory window, and both SET and RESET voltages of ReRAM.

Assessing The Critical Factors Influencing Worker Safety In Roadway Work Zones, Bahaa Chammout, Muaz O. Ahmed, Islam El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Ongoing roadway construction and maintenance activities are essential for sustaining and improving infrastructure. Nonetheless, work zones in the United States continue to experience concerning frequencies of occupational and traffic accidents. Previous research highlighted multiple factors influencing work zone safety, yet their relative impact and importance remain unclear. This study addresses this gap following a multistep methodology. First, 32 safety factors were identified through an extensive literature review in a previous study. Second, a survey was administered among 298 professionals from diverse backgrounds, with an average of 17.75 years of construction experience and 13.78 years of work zone experience, to assess …

Manifold Learning And Undersampling Approaches For Imbalanced Class Sentiment Classification, L.M. Risman Dwi Jumansyah, Agus Mohamad Soleh, Utami Dyah Syafitri

Knowledge Engineering and Data Science

Movie reviews are crucial in determining a film's success by influencing audience decisions. Automating sentiment classification is essential for efficient public opinion analysis. However, it faces challenges such as high-dimensional data and imbalanced class distributions. This study addresses these issues by applying manifold learning techniques, Principal Component Analysis (PCA) and Laplacian Eigenmaps (LE) to reduce data complexity and undersampling strategies (Random Undersampling (RUS) and EasyEnsemble) to balance data and improve predictions for both sentiment classes. On reviews of The Raid 2: Berandal, EasyEnsemble achieved the highest average G-Mean of 0.694 using Term Frequency-Inverse Document Frequency (TF IDF) features with a …

Thermal Conductivity Characterization Of High Oleic Vegetable Oils Based Hybrid Nanofluids Formulated Using Gnp, Tio2, Mos2, Al2o3 Nanoparticles For Mql Machining, Anthony Chukwujekwu Okafor, Tobechukwu Kingsley Abor, Saidanvar Esanjonovich Valiev, Ignatius Echezona Ekengwu, Abiodun Saka, Monday Uchenna Okoronkwo

Chemical and Biochemical Engineering Faculty Research & Creative Works

This paper presents the results of thermal conductivity characterization of six high oleic soybean oil (HOSO) and four high oleic canola oil (HOCO)-Based hybrid nanofluids formulated with four types of nanoparticles (Graphene nanoplatelet (xGnP), TiO₂, MoS₂, and Al₂O₃) at nanoparticles wt.% concentration from 1 % to 7 % in 1 % increment using the two-step method for use in MQL machining of difficult-to-cut metals. Thermal conductivity of the formulated hybrid nanofluids were measured using Thermtest Transient Hot Wire Liquid Thermal Conductivity Meter at temperatures from 25 °C to 75 °C in increment …

A Fiber Optics Based Surface Enhanced Raman Spectroscopy Sensor For Chemical And Biological Sensing, Jiayu Liu, Bohong Zhang, Amjed Abdullah, Sura A. Muhsin, Jie Huang, Mahmoud Almasri

Electrical and Computer Engineering Faculty Research & Creative Works

This paper investigates an innovative surface-enhanced Raman scattering (SERS) sensor developed on a side-polished multimode optical fiber core. The optical fiber was integrated into specifically designed 3-dimensional printed mold, where manual polishing of the fiber took place. Microsphere Photolithography (MPL) techniques was employed to pattern periodic nanoantenna arrays on the polished surface, incorporating multiple disk diameters at a fixed periodicity. Subsequent gold deposition/lift-off were carried out to transfer the pattern from the photoresist to the fiber core, resulting in highly periodic hexagonal closed pack (HCP) arrays of nano disks. These arrays can significantly enhance the SERS signal intensity compared to …