Digital Commons Network^™

Optimized Electrocoagulation Pre-Treatment For Fouling Reduction During Nanofiltration Of Lake Water Containing Microcystin-Lr, Thomas Mckean, Chidambaram Tharmaraiselvan, Sarah Do, S. Ranil Wickramasinghe

Chemical Engineering Faculty Publications and Presentations

Microcystin-LR (MCLR) is a toxin produced by harmful algal blooms that is emerging as a threat to drinking and recreational water systems worldwide. Nanofiltration (NF) is an effective technique for purifying contaminated water sources; however, membrane fouling caused by coexisting organic matter limits the practicality of the process. This research studies the use of an electrocoagulation (EC) pretreatment to limit fouling during the NF process. Water for this study was taken from Lake Fayetteville, a local body of water where MCLR concentrations have been recorded to be >15 µg/L. EC was performed using polyaluminum chloride as a background electrolyte at …

Circular Economy In Construction: Decision-Making Factors And Future Research Avenues, Bahaa Chammout, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The construction sector is a major consumer of raw materials and a significant contributor to environmental degradation. Circular economy (CE) - an economic and systemic approach aimed at minimizing waste and fostering sustainable resource use - offers a remedy for these impacts. However, CE adoption in construction remains under-researched and limited. Accordingly, there is a need to provide a comprehensive understanding of CE decision-making factors in construction. This paper addresses this research need. First, the authors reviewed 138 journal articles on CE in construction, published between 2015 and 2023, and compiled a comprehensive list of 40 factors influencing CE decision-making. …

Comparative Analysis Of Lab-Data-Driven Models For International Friction Index Prediction In High Friction Surface Treatment (Hfst), Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High Friction Surface Treatments (HFSTs) are often utilized as a spot treatment to enhance selected areas with high friction demand rather than extended pavement sections and are helpful in increasing skid resistance and minimizing road accidents. A laboratory design approach was created to assess the fundamental ideas behind the international friction index (IFI) concept and update the present IFI model parameters for HFST applications based on test findings to gain a better understanding of HFST performance. Two aggregate types in three sizes were tested under controlled polishing cycles. Friction and texture were measured using the Dynamic Friction Tester (DFT) and …

Microstructural Evolution And Rheological Enhancement Of Asphalt–Rubber Binders: Unveiling The Role Of Morphology In Performance, Eslam Deef-Allah, Mohyeldin Ragab, Mohamed Attia, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Understanding the development of an asphalt binder's internal network structure is essential when interacting asphalt and crumb rubber. Thus, the focus of this study was to reveal the development of asphalt–rubber binders' (A-RBs) network structures at different interaction times and their correlation with performance. Atomic force microscopy (AFM) was utilized to image the morphologies of the binders, and the binders' performances were explored rheologically with a dynamic shear rheometer. Extending the interaction time to 8 h and utilizing a soft binder altered the network structures from agglomerated dispersoids—minuscule distributed phase zones embedded in the continuous matrix of the asphalt binder—to …

Recent Advances In Multitone Microwave Frequency Measurement, Md Abu Zobair, Behzad Boroomandisorkhabi, Mina Esmaeelpour

Electrical and Computer Engineering Faculty Research & Creative Works

This review explores various advanced photonic-assisted techniques for microwave frequency measurement, highlighting their distinct advantages and challenges in detecting multi-tone and broadband microwave frequency signals. Different optical processing techniques for instantaneous frequency measurement, including frequency-to-time mapping techniques, are discussed in detail. The application of multicore and few-mode fibers, artificial intelligence-enhanced, and complex modulation techniques are also discussed. These recent advances collectively push the boundaries of microwave frequency measurement, offering robust and scalable solutions for various applications.

A Cfd Analysis Of Equipment Fires In An Underground Development Heading For Improved Auxiliary Ventilation Design, Oluwafemi B. Salami, Jurgen F. Brune, Guang Xu

Mining Engineering Faculty Research & Creative Works

Abstract: This study investigates the intricacies of equipment fires in a blind development heading of an underground mine using computational fluid dynamics (CFD). A series of fire dynamic simulations (FDS) were conducted for various ventilation velocities in the main airway, and with different distance between the auxiliary ventilation duct outlet to the blind working face. The impacts of the ventilation velocity in the main airway, and separation distance between the duct outlet to the blind face on temperature distribution and smoke spread mechanism were investigated. The findings indicate that the distance of the auxiliary ventilation duct outlet to the working …

On-Demand Heterogeneous Drone Delivery Problem, Xupeng Wen, Zhiguang Cao, Shu Xu, Dapeng Ren, Guohua Wu, Yaoxin Wu

Research Collection School Of Computing and Information Systems

In the on-demand problem domain, actual demand frequently deviates from the expected demand. This paper intricately delves into the exploration of on-demand heterogeneous multi-drone routing problem (ODHDRP), in which a transport drone carries multiple terminal drones to subregions in the first echelon, and the terminal drones deliver parcels during a flight trip to customers with demands in subregions to maintain economies of scale in the second echelon. We formulate the customer demands using a normal distribution, and exploit a reliability model of customer demands with chance constraints. To solve the ODHDRP efficiently, we propose a hybrid iterative optimisation heuristic (HIOH) …

Performance Evaluation Of Aminated Multi-Walled Carbon Nanotubes Incorporated With Green Synthesized Iron Nanoparticles For Toxic Dyes Sequestration From Textile Wastewater, Titus Chinedu Egbosiuba, Cynthia Chukwuemeka, Jonah Chukwudi Umeuzuegbu, Nwanneka Chibuzo Mmonwuba, Ugochukwu Ewuzie, Monday Uchenna Okoronkwo, Valentine Chikaodili Anadebe, Saheed Mustapha, Ambali Saka Abdulkareem, Jimoh Oladejo Tijani, Ashish Patel, Virendra Kumar Yadav

Chemical and Biochemical Engineering Faculty Research & Creative Works

This study evaluates the performance of aminated multi-walled carbon nanotubes (AM-MWCNTs) integrated with zerovalent iron nanoparticles (ZVI) synthesized using cashew leaf (Anacardium occidentale) extract (AM-MWCNTs@ZVI) for the removal of Congo Red (CR) and Methylene Blue (MB) dyes from textile industrial wastewater. The nanocomposite was characterized using FTIR, XRD, BET, HRSEM, and HRTEM analyses, confirming its functional groups, crystalline structure, and enhanced surface area of 1050.4 m²/g. The ecological risk degree of the textile pollutants was assessed to determine the percentage concentrations of crystal violet, Congo red, methyl orange, methylene blue and rhodamine B. Batch adsorption experiments identified optimal …

How Regulations Impact Contractors In California: Licensing, Insurance, Bonding & Permitting, Byron Rolando Calderon Cifuentes

Construction Management

This senior project researches the impact of regulatory requirements, specifically licensing, insurance, bonding, and permitting, on contractors in California. The study addresses the question: How do regulations affect contractors’ ability to operate and grow? To examine this, qualitative interviews were conducted with six industry professionals, including general contractors, specialty contractors, and design-build firms. Additionally, 25 survey responses were collected from contractors and construction professionals to gain broader insights. The findings reveal that while licensing, insurance, and bonding are seen as foundational for establishing credibility and legal compliance, the permitting process presents the most significant challenge. Respondents consistently described permitting as …

Investigation Of Retention And Dehydration Of Preformed Particle Gel For Conformance Control In Fractured Carbonates, Abdulaziz A. Almakimi, Abdullah O. Almansour, Junchen Liu, Baojun Bai, Ibnelwaleed A. Hussein

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Preformed particle gel (PPG) treatment has proved to be among the most effective methods to reduce excessive water production in fractured reservoirs. The blocking ability of PPGs to fractures or fracture-like features is highly dependent on injected gel properties and volume. Gel dehydration during extrusion through fracture is common and has a considerable effect on gel properties, transport, and plugging efficiency. As the gel particles propagate through the fracture, continuous dehydration is often associated and causes the gel to concentrate and require high-pressure gradients to move. Dehydration might be desirable to a certain limit because it can help to form …

Supporting Academic Parents: The Effects Of Dependent Care Policies On Research Productivity Trends, Drake Van Egdom, Matthew M. Piszczek, Christiane Spitzmueller, Peggy Lindner, Aaron Clauset

Engineering Management and Systems Engineering Faculty Research & Creative Works

On average, women faculty take on more childcare responsibilities, posing barriers to career success. Work-family policies represent one solution for advancing gender equity in academia as they support parents after childbirth with benefits for children, employees, and organizations. We contribute to understanding how the availability and use of dependent care policies (paid parental leave and childcare benefits) relate to long-term research productivity trends. Based on the work-home resources model, we theorize that policy availability provides contextual resources and policy use provides personal resources, leading to improvements in an individual's research productivity after they have a child. We also examine potential …

Meta-Learning Hyperparameters For Foundation Model Adaptation In Remote-Sensing Imagery, Zichen Tian, Yaoyao Liu, Qianru Sun

Research Collection School Of Computing and Information Systems

Training large foundation models of remote-sensing (RS) images is almost impossible due to the limited and long-tailed data problems. Fine-tuning natural image pre-trained models on RS images is a straightforward solution. To reduce computational costs and improve performance on tail classes, existing methods apply parameter-efficient fine-tuning (PEFT) techniques, such as LoRA and AdaptFormer. However, we observe that fixed hyperparameters -- such as intra-layer positions, layer depth, and scaling factors, can considerably hinder PEFT performance, as fine-tuning on RS images proves highly sensitive to these settings. To address this, we propose MetaPEFT, a method incorporating adaptive scalers that dynamically adjust module …

How Argentina Won The 2022 Fifa Men's World Cup: A Data Story, Aniruddha Parthasarathy

Dissertations, Theses, and Capstone Projects

This project analyzes Argentina’s 2022 FIFA Men’s World Cup win using open-source football (soccer) data. The project evaluates the team’s performance at a micro-level across three domains: without possessing the ball, possessing the ball and the team’s in-game management tactics. A statistical framework, i.e., multiple linear regression modeling, was used to identify the five key defensive actions influencing the Argentinian team’s intensity of pressure applied, and visualized by heatmaps and time-segmented plots. More specifically, an Expected Threat (xT) analysis quantified the threat or danger from passes and progressive carries (moving the ball at least 10 meters), revealing that Lionel Messi’s …

Energy Conversion Materials: Computational Design Of Electrocatalysts Toward Sustainable Energy Applications, Courtney M. Brea

Dissertations, Theses, and Capstone Projects

As the global-scale need for sustainable energy technologies emerges due to anthropogenic climate change, electrocatalysis plays a crucial role in facilitating many sustainable processes. Several heterogenous cathode materials can perform different electrochemical activities using water, oxygen, hydrogen, carbon dioxide to deliver renewable electricity and value-added chemicals. By using the density functional theory method, it is possible to explore the structural and electronic properties that govern a catalysts’ activity and selectivity. In this thesis, we start by exploring 48 reconstructed transition metal dichalcogenides edges (MX₂, M = Mo, W; X = S, Se, Te) for carbon dioxide reduction reaction …

A Critical Evaluation Of The Criticisms Against Neutrosophic Statistical Methods, Muhammad Aslam, Abdulrahman Alaita, Florentin Smarandache

Neutrosophic Systems with Applications

Neutrosophic statistical analysis has gained attention for incorporating the degree of indeterminacy when analyzing imprecise and interval data under uncertainty–-an aspect often overlooked by classical statistics, fuzzy statistical analysis, and interval statistics. Recently, critical discussions have emerged regarding the use and applications of neutrosophic statistics, with some questioning its usefulness and validity. In this paper, we present a critical assessment of the existing literature, focusing on areas where misunderstandings and misinterpretations of neutrosophic statistical methods have occurred. We also examine flawed comparisons made between the results of neutrosophic statistics and interval statistics. Furthermore, substantial issues have been identified in the …

Childhood Neuroanatomical Markers Of Familial And Nonfamilial Attention-Deficit/Hyperactivity Disorder, Rahman Baboli

Dissertations

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder, characterized by developmentally inappropriate levels of inattention, hyperactivity, and impulsivity. Children with family history of ADHD are at an elevated risk of having ADHD as well as a higher risk of persistent ADHD into adulthood, reflecting a source of etiological heterogeneity in ADHD. This heterogeneity in terms of both biological and environmental risk factors may explain differences in neural correlates, outcomes, cognitive, behavioral as well as developmental trajectories. It is therefore critical to understand the influence of having, or not having positive family risk factors on the neuroanatomical structures of the …

Burst Pressure Performance Of Multilayer Co-Extruded Polystyrene/Poly (Methyl Methacrylate) Pipes, Negar Shaghaghi, Erik Steinmetz, João Maia

Faculty Scholarship

This study investigates advancements in multilayer co-extrusion of annular structures, focusing on the mechanical properties of a 129-layer polystyrene (PS)/poly(methyl methacrylate) (PMMA) pipe with 50% PS as a skin layer for proof-of-concept validation. We explore the impact of angular rotation on burst pressure, layer structure, and failure mechanisms, emphasizing the potential of this technique for enhanced mechanical performance through biaxial orientation and the elimination of weld lines. Utilizing high aspect ratio (HAR) multipliers and angular rotation, our findings demonstrate improved layer structure and burst pressure performance at higher velocity ratios, which is the ratio of the linear component of angular …

The Prospect Of Geospatial Analysis In The Prediction Of Surface Quality In Machining, Prithbey Raj Dey, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

This research underscores the prospect of geospatial analysis in machining operations to enhance precise prediction and robustness, offering a comprehensive framework of spatial modeling for advanced manufacturing processes. Geospatial analysis not only provides accurate predictions but also estimates the uncertainty associated with these predictions, offering valuable insights for process optimization. The surface quality in the machining processes is expressed by the estimation of the average surface roughness. While machining parameters are extensively analyzed for their influence on surface quality, the roughness profile parameters are inadequately explored. This work integrates these underexplored parameters into geospatial predictive models and evaluates their impact …

A System Of Systems (Sos) Meta-Architecture Approach To Design Digital Platform-Based Domestic Worker Distribution System, Prithbey Raj Dey, Cihan H. Dagli, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this research, a System of Systems (SoS) meta-architecture is conceptualized to design a digital platform-based system framework for the distribution of domestic workers to boost the crowd-sourced economy. While an Object Process Methodology (OPM) is used to articulate the relationships between the objects and functions, a Design Structure Matrix (DSM) has been applied to address the interactions between individual components to categorize them into subsystems to create the SoS architecture. This SoS architecture incorporates several Key Performance Attributes (KPAs) and Key Performance Parameters (KPPs) to systematically evaluate the meta-architectures. The Analytical Hierarchical Process (AHP), Pugh’s Evaluation Matrix, and Technique …

Blockchain-Based Ai-Assisted Cyber-Physical Systems For Robust And Reliable Machining Processes, Prithbey Raj Dey, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

This study demonstrates the prospects of Blockchain-based Cyber-Physical Systems (CPS) to establish a scalable framework for designing a secured, automated, and traceable modeling in machining processes. Machining operations like turning, being inherently complex, rely on different types of explanatory parameters such as feed rate, depth of cut, cutting speed, tools, and environmental factors. All of these variables significantly influence key response variables like surface quality, tool wear, cutting forces, and energy consumption. The proposed Blockchain-based framework, designed using the Object-Process Methodology (OPM) systems modeling language, enables the reliable exchange of comparative data streams within a unified data analytics platform. By …

Linear Mixed Model For The Surface Roughness Prediction In Hard Turning Operation, Prithbey Raj Dey, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Surface machining using hard turning is an intricate operation due to the influence of multiple machining parameters, their non-linear interactions, and the inherent variability introduced by different experimental trials. This study proposes a Linear Mixed Model (LMM) for predicting surface roughness, effectively addressing the challenges in traditional linear models, posed by the influencing factors, non-linearity, and interactions. The LMM incorporates variability from both fixed effects, such as cutting parameters (feed rate, depth of cut, and cutting speed), and random effects arising from tool wear across experimental runs. As a result, it provides a more comprehensive understanding of how these factors …

Price-Signal-Based Control Strategy For Heat Pump Water Heaters In Demand Response Applications, Othman A. Murad

Dissertations and Theses

This work presents a price-signal-based control strategy for residential Heat Pump Water Heaters (HPWHs) aimed at reducing electricity costs and shifting load away from high-price periods. By integrating the California Load Flexibility Research and Development Hub (CalFlexHub) prototype price signals, the Consumer Technology Association (CTA-2045-B) communication protocol, and the Object-oriented, Controllable, High-resolution Residential Energy (OCHRE) simulation framework, a rule-based controller was developed to align HPWH operation with dynamic electricity pricing while maintaining hot water availability.

The control strategy was evaluated through two case studies: one using a fixed water draw profile under varying levels of price signal foresight, and another …

Influencing Factors Of Angle-Of-Arrival Estimator Based On Deep Learning, Guohao Pang

Dissertations and Theses

Deep learning (DL)-based angle-of-arrival (AoA) estimation offers significant advantages over traditional signal processing methods, especially in complex and high-noise environments. However, situational complexity and differences in hardware can significantly impact the estimator's performance. It is therefore of interest to investigate the relationship between the performance of deep learning models and the variation of physical parameters such as the number of signal sources, the number of receiving antennas, and the signal-to-noise ratio (SNR). In this study, we investigate the impact of these variations on deep learning-based AoA estimation by systematically analyzing how the variations in the characteristics of the received signal …

Codelympics: An Educational Game, Shreyas Raghunath, Riley Guioguio

Computer Science and Engineering Senior Theses

This thesis addresses the growth of Computer Science and the increasing demand for resources that educate people about programming. The central problem is that existing resources either fall short in engaging the user, or are ineffective at communicating the basics of programming. Through a year of development and testing, we developed an application to serve as a bridge between games and educational content, making programming skills fun and accessible for younger students with no prior experience.

This thesis details the development of Codelympics, an educational game designed to teach the basics of computer programming, including control flow, functions, variables, and …

Axiomatic Aggregation Data, Carl D. Sorensen, Christopher A. Mattson, Michael L. Anderson, Thomas J. Ashworth

ScholarsArchive Data

This data set includes the ideation results of an experiment in ideation effectiveness, along with tools for analyzing the quality of the ideation.

All ideas generated by 15 teams of BYU students are included in the database. The ideas have been placed into an OPED genealogy tree format. The quality of all the ideas has been evaluated. The novelty of one team's ideas has been evaluated.

Instructions for performing the OPED organization, evaluating quality, and evaluating novelty are included in the data workbook.

Software tools to aggregate the individual evaluations into team scores and to display the results of the …

Comprehensive Risk Assessment Of Power Grids Using Fuzzy Bayesian Networks Through Expert Elicitation: A Technical Analysis, Yasir Mahmood, Nof Yasir, Nita Yodo, Ying Huang, Di Wu, Roy A. Mccann

Electrical Engineering and Computer Science Faculty Publications and Presentations

Power grid infrastructures, essential to modern societies for electricity distribution, are prone to vulnerabilities due to their numerous sensitive components, necessitating a comprehensive risk assessment. Uncertainty in historical failure data often compromises accurate risk quantification, leading to the integration of expert elicitation as a solution. This study develops a Bayesian network (BN) risk assessment model integrated with fuzzy set theory (FST), referred to as the fuzzy Bayesian network (FBN). By incorporating expert insights, this model quantifies internal and external risk variables more comprehensively. Crisp probabilities (CPr), derived from regional transmission operator (RTO) failure incident data, are complemented by fuzzy probabilities …

Modeling Rice Leaf Area Index And Canopy Height In The Us Mid-South Region, Ellie J. Kuhn, Beatriz Moreno-Garcia, Michele Reba, Kusum Naithani, Benjamin R. Runkle

Biological and Agricultural Engineering Faculty Publications and Presentations

Crop growth modeling plays a critical role in addressing the global challenges of food scarcity, carbon cycling, and water management. By simulating crop development from environmental factors, these models help predict harvest yield and carbon or water cycle terms and thus can inform policy and investment decisions. However, for some agricultural regions, such as the US Mid-South, there is a lack of comprehensive data specific to rice (Oryza sativa) cultivars and their growing conditions. Here, we use 30 field seasons of observational data to predict leaf area index (LAI) and canopy height (Hcan), key inputs for crop growth models, for …

True-Bsg: A True Random Bit-Stream Generator For Fast And Efficient Stochastic Computing, Mehran Shoushtari Moghadam, M. Hassan Najafi

Faculty Scholarship

Stochastic computing (SC) leverages random bitstreams to perform arithmetic operations, offering ultra-lowcost, fault-tolerant, and highly parallelizable computations. The quality of these bit-streams is crucial for the accuracy and reliability of SC. This paper introduces TRUE-BSG, a novel true random bit-stream generator designed for fast and energyefficient SC. Unlike state-of-the-art (SoTA) pseudo-random and quasi-random bit-stream generators, TRUE-BSG utilizes a highquality true random number generator (TRNG), capable of producing random bits at a rate of 1 Gigabit per second. Our TRNG ensures high entropy and minimal correlation. TRUE-BSG shows comparable accuracy to software-based generators and better energy efficiency than SoTA bit-stream generators, …

Ams-Hd: Acute Mountain Sickness Detection With Hyperdimensional Computing, M. Hassan Najafi, Mehran Shoushtari Moghadam

Faculty Scholarship

Acute mountain sickness (AMS) is a potentially life-threatening condition that affects many individuals traveling to high altitudes. Early diagnosis is crucial, especially for travelers who may not have immediate access to medical resources. While traditional machine learning (ML) methods have been used to detect AMS using biomedical data (e.g., heart rate, blood oxygen saturation, respiration rate, blood pressure, and body temperature), hyperdimensional computing (HDC) has yet to be explored for this purpose using the few of biomedical data. Previous classification methods fall short of balancing accuracy with low hardware complexity, but HDC offers a promising solution. HDC provides a hardware-efficient …

Historical Overview, Advancements, And Future Prospects Of Coalfield Structure Research In China, Cao Daiyong, Ju Yiwen, Xia Yucheng, Jiang Bo, Ning Shuzheng, Wei Yingchun, Wang Anmin, Li Xiaoming, Zhan Wenfeng, Li Huantong, Wang Lu, Cai Zhuocheng

Coal Geology & Exploration

Background Coalfield structures represent a basic aspect of coalfield geology. In China, research into this domain has a history of over a century, yielding numerous results after undergoing exploration, learning, and innovation. These results have played a positive role in the long-term, stable coal supply in China. Amidst the ongoing energy structure optimization and the transformation and upgrading of coalfield geology in China, it is both practically and historically significant to review the history of coalfield structure research, summarize relevant experience, and contemplate future directions of the research under emerging circumstances.Methods Based on literature analysis, as well as the …