Engineering Commons^™

Study On The Tribological Properties Of Din 16mncr5 Steel After Duplex Gas-Nitriding And Pack Boriding, Rafael Carrera Espinoza, Melvyn Alvarez-Vera, Marc Wettlaufer, Manuel Kerl, Stefan Barth, Pablo Moreno Garibaldi, Juan Carlos Díaz Guillen, Héctor Manuel Hernández García, Rita Muñoz Arroyo, Javier A. Ortega

Mechanical Engineering Faculty Publications

DIN 16MnCr5 is commonly used in mechanical engineering contact applications such as gears, joint parts, shafts, gear wheels, camshafts, bolts, pins, and cardan joints, among others. This study examined the microstructural and mechanical properties and tribological behavior of different surface treatments applied to DIN 16MnCr5 steel. The samples were hardened at 870 °C for 15 min and then quenched in water. The surface conditions evaluated were as follows: quenched and tempered DIN 16MnCr5 steel samples without surface treatments (control group), quenched and tempered DIN 16MnCr5 steel samples with gas-nitriding at 560 °C for 6 h, quenched and tempered DIN 16MnCr5 …

Protocol For Recording Neural Activity Evoked By Electrical Stimulation In Mice Using Two-Photon Calcium Imaging, Seungbin Park, Megan Lipton, Yujiao J. Sun, Maria Dadarlat

Purdue University Libraries Open Access Publishing Fund

Electrical stimulation provides a clinically viable approach for treating neurological disorders. Here, we present a protocol for recording neural activity evoked by electrical stimulation in mice using two-photon calcium imaging. We detail steps for chronically implanting a head fixation bar, a stimulating electrode, and a glass imaging window.We additionally describe the procedures for viral injections and awake head-fixed recordings.

Comparing Human Text Classification Performance And Explainability With Large Language And Machine Learning Models Using Eye-Tracking, Jeevithashree Divya Venkatesh, Aparajita Jaiswal, Gaurav Nanda

Purdue University Libraries Open Access Publishing Fund

To understand the alignment between reasonings of humans and artificial intelligence (AI) models, this empirical study compared the human text classification performance and explainability with a traditional machine learning (ML) model and large language model (LLM). A domain-specific noisy textual dataset of 204 injury narratives had to be classified into 6 cause-of-injury codes. The narratives varied in terms of complexity and ease of categorization based on the distinctive nature of cause-of-injury code. The user study involved 51 participants whose eye-tracking data was recorded while they performed the text classification task. While the ML model was trained on 120,000 pre-labelled injury …

Cellular Energy Cycle Mediates An Advection-Like Forward Cell Flow To Support Collective Invasion, Jian Zhang, Jenna Mosier, Yusheng Wu, Logan Waddle, Paul V. Taufelele, Wenjun Wang, Heng Sun, Cynthia A. Reinhart-King

Biomedical Engineering Faculty Publications and Presentations

Collective cell migration is a model for nonequilibrium biological dynamics, which is important for morphogenesis, pattern formation, and cancer metastasis. The current understanding of cellular collective dynamics is based primarily on cells moving within a 2D epithelial monolayer. However, solid tumors often invade surrounding tissues in the form of a stream-like 3D structure, and how biophysical cues are integrated at the cellular level to give rise to this collective streaming remains unclear. Here, it is shown that cell cycle-mediated bioenergetics drive a forward advective flow of cells and energy to the front to support 3D collective invasion. The cell division …

Rotational Rheometry Test Of Portland Cement-Based Materials – A Systematic Literature Review, Laura Silvestro, Artur Spat Ruviaro, Geannina Lima, Luís Urbano Durlo Tambara Júnior, Dimitri Feys, Ana Paula Kirchheim

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This Study Systematically Reviews 62 Papers on the Use of Rotational Rheometry to Assess the Fresh State Behavior of Portland Cement-Based Materials. the Research Highlights the Wide Variation in Test Methods and Aims to Provide a Comprehensive overview. Findings Reveal that 50.0% of Studies Employed Vane Geometry, despite its Limitations in Providing Transformation Equations. Regarding Dynamic Shearing Tests, 67.0% Followed a Consensus using a Pre-Shearing Step and a Stepwise Routine with Stabilization Times ≥ 10 S. While the Bingham Model is Commonly Used, the Study Emphasizes the Importance of Considering Shear-Thinning Behavior in Cementitious Materials. Models Like Herschel-Bulkley and Modified …

Black Box Modeling Of Hvcb: A Comparative Approach, Raghdaa Elbahy, Ahmed Abdelbaset, Mahmoud Hammoda, Mansour H. Abdel-Rahman, Ebrahim A. Badran

Mansoura Engineering Journal

The extinction of an electric arc is a multifaceted process influenced by electric, magnetic, thermodynamic, and chemical phenomena. Black box models provide a mathematical depiction of the electrical characteristics of the arc. Although these models do not offer a complete explanation of the physical processes within a circuit breaker, they effectively describe its electric behavior. This study explores the modeling of electric arcs and the analysis of high-voltage circuit breakers using black box models such as Cassie, Mayr, and Schavemaker. To represent the circuit breaker model in ATPdraw, a customized MODELS block was employed. The paper presents a comparative evaluation …

Continuum Mechanics Modeling Of High Strain Rate Impact Of Thermoplastic Polymer Particles, Jeeva Muthulingam

Theses and Dissertations

The study of particle impact at high strain rates is crucial in fields ranging from materials science and engineering to space exploration and environmental science. In the particular case of cold spray, a particle undergoes intense plastic deformation upon impact, causing it to adhere to the target substrate. While metallic particles impacting on metallic substrates have been extensively studied, understanding the mechanical characteristics of polymeric particles on polymer and metal substrates requires further research. This study focuses on single particle impact modeling, analyzing impact parameters such as particle size, velocity, and angle of incidence using continuum mechanics finite element modeling …

Understanding The Mechanical And Electrochemical Impacts Of Binder Systems On Silicon Anodes In Lithium-Ion Batteries, Fei Sun

Theses and Dissertations

Silicon has emerged as a promising alternative to traditional graphite as an anode material in battery technology, primarily due to its high theoretical capacity and abundance. However, its application is hindered by significant challenges, including severe volume expansion in the active material (~275%) during cycling, which can lead to a series of electrode failure issues. Polymer binder plays an essential role in addressing these challenges as it accommodates silicon's volume expansion and the rearrangement of particles. This work conducted an analysis of how different binders influence mechanical and electrochemical properties of silicon electrodes. Our findings are supported by a series …

Understanding Social Impacts Of Major Disruptions From The Perspective Of Destination Access, Manika Rana Bhat

LSU Master's Theses

Major disruptions (like public health crises and extreme weather events) significantly impact human mobility and travel patterns. This study investigates the social impacts of major disruptions on human mobility from the perspective of accessing destinations. This study used a large-scale dataset from SafeGraph and focused on analyzing the impacts of COVID-19 and Hurricane Ida on destination access in Louisiana. The findings of the temporal plots indicated that the impact magnitude of Hurricane Ida was much smaller than that of the COVID-19 pandemic but still resulted in hardship on destination access. During COVID-19, it was found that parishes with limited active …

Integration Of Machine Learning In Structural Health Monitoring For Damage Identification And Response Prediction In Bridges, Naga Lakshmi Chittitalli Ravuri

Theses and Dissertations

Machine learning-based structural health monitoring (ML-SHM) plays a pivotal role in enhancing structural resilience. By recognizing potential hazards, implementing resistance measures, facilitating swift recovery, and continuously monitoring structural health, ML-SHM ensures proactive maintenance and minimizes recovery delays post-events. Leveraging machine learning algorithms and sensor data, ML-SHM enables early detection of anomalies, prediction of failures, and adaptive responses, enhancing the structure's ability to withstand and recover from adverse conditions. This integrated approach not only improves the structure's performance and adaptability but also contributes to overall safety and longevity. This thesis presents a comprehensive exploration of structural health monitoring (SHM) techniques for …

Tool Life Characterization In Refill Friction Stir Spot Welding, Ruth Guadalupe Belnap

Theses and Dissertations

As light-weighting becomes a priority for the automotive industry, refill friction stir spot welding emerges with enormous potential to supplement or replace conventional spot joining processes. This thesis addresses the limitations of current tooling options by examining materials beyond steel for use in RFSSW. Contained herein is an analysis of weld quality as a function of tool material, a production evaluation of RFSSW using various tool materials, and an assessment of long-term performance of a tungsten carbide tool. Over the course of this research, tungsten carbide emerged as a viable candidate for long-lasting RFSSW tooling.

Digimindready: Enhancing Military Readiness Through Edge Ai-Driven Wellness, Education, And Digital Discipline Via Privacy-First Mhealth Innovation, Md Mehedi Hasan

Master's Theses

Military personnel often find themselves in intense situations that require high focus. Successfully engaging in these dangerous missions means they must efficiently control cognitive load, manage overwhelming stress, and stay focused through distractions to perform at their best. Military training significantly focuses on human performance, which benefits military readiness. The 21st century has introduced unanticipated challenges to all, such as the adverse effects of excessive screen time, external distractions, and over-reliance on technology without being aware of digital discipline. Militaries are no exception. These challenges have become an emerging threat to military personnel's cognitive, emotional, and physical well-being. On top …

Cognitive Manufacturing: Definition And Current Trends, Fadi El Kalach, Ibrahim Yousif, Thorsten Wuest, Amit Sheth, Ramy Harik

Publications

Manufacturing systems have recently witnessed a shift from the widely adopted automated systems seen throughout industry. The evolution of Industry 4.0 or Smart Manufacturing has led to the introduction of more autonomous systems focused on fault tolerant and customized production. These systems are required to utilize multimodal data such as machine status, sensory data, and domain knowledge for complex decision making processes. This level of intelligence can allow manufacturing systems to keep up with the ever-changing markets and intricate supply chain. Current manufacturing lines lack these capabilities and fall short of utilizing all generated data. This paper delves into the …

Large-Scale Research Infrastructure Empowers High-Quality Development Of Private Enterprises: Current Situation, Challenges, And Policy Recommendations, Lingling Zhang, Fuqiang Wang, Mingze Zhang, Zexia Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Private enterprises have become an important source of innovation in China’s economic development. Large-scale research infrastructure, as a crucial strategic support and innovation element for breaking through key technologies, provides a platform for the innovative development of private enterprises. At present, some large-scale research infrastructures in China, such as the China Spallation Neutron Source and the Shanghai Synchrotron Radiation Facility, have begun actively exploring mechanisms to serve private enterprises. These efforts have helped a number of private companies overcome critical technological bottlenecks and achieve original innovations. Nevertheless, in the current process of opening up large-scale research infrastructures to private enterprises …

Aligning Clinical Productivity Of Cancer Care Providers: A Simulation-Based Approach, Maile Sinclair-Baxter

USF Tampa Graduate Theses and Dissertations

The growing number of cancer patients over the years has presented many challenges and opportunities for improvement in the healthcare system. These challenges and opportunities have demonstrated the need for a tool that can enhance the clinical productivity of healthcare providers, ultimately impacting patients’ overall experience. We studied the clinical Full Time Equivalency (cFTE) for providers at a cancer research center. cFTE is the percentage of time allocated for clinical work. In this cancer research center, the clinical work of each provider is supposed to match a targeted cFTE. The cancer research center’s concern was that the provider’s clinical productivity …

Advancing Adversarial Audio: Human-In-The-Loop Black-Box Attacks, Rui Duan

USF Tampa Graduate Theses and Dissertations

Adversarial audio attacks pose significant security challenges to real-world audio applications. Attackers may manipulate speech to impersonate a speaker, gaining access to smart devices like Amazon Echo. In audio applications, there are two key areas: music and speech. In music, most attackers create a small noise-like perturbation on the original signal to evade copyright detection. However, this method degrades music's perceived quality for human listeners. In the speech, creating an adversarial example often requires many queries to the target model, a process too cumbersome for practical use in real-world scenarios, like interacting with smart devices numerous times.

In this dissertation, …

Copper-Based Electrocatalysts For Electrochemical Reduction Of Co2 To C2 Products, Monsuru Olatunji Dauda

LSU Master's Theses

The electrochemical reduction of CO₂ using copper-based electrocatalysts has emerged as a promising approach for sustainable chemical production, offering a pathway to mitigate the rising atmospheric CO₂ levels while generating valuable fuels and chemicals. However, the selectivity and efficiency of copper-based catalysts towards specific C₂ products remain a major challenge, hindering their commercial viability. This thesis focuses on the development, characterization, and mechanistic understanding of three promising electrocatalyst systems for multi-carbon product generation from CO₂ reduction: copper-phosphide (Cu-P), copper-tin (Cu-Sn), and copper selenide (Cu₂Se). A comprehensive investigation of the electrocatalysts was conducted using advanced …

Enhancing Contractor Selection Through Fuzzy Topsis And Fuzzy Saw Techniques, Mohammadsoroush Tafazzoli, Ayoub Hazrati, Kishor Shrestha, Krishna Kisi

Civil Engineering & Construction: Faculty Publications

Contractors play an integral role in construction projects, and their qualifications directly impact various aspects of a project’s success. The unbiased selection of contractors is a challenge in the construction industry worldwide, particularly in public projects where impartiality in the final selection is essential. Numerous factors must be considered when evaluating contractors, making the selection process challenging for the human brain. This paper introduces and compares two methods for assessing contractor prequalification by applying the fuzzy theory. The idea is to facilitate using human judgments in a mathematical system for decision-making with regard to selecting contractors. The method is based …

Stretching The Limits Of Mri—Stretchable And Modular Coil Array Using Conductive Thread Technology, Folk W. Narongrit, Thejas Vishnu Ramesh, Joseph V. Rispoli

Purdue University Libraries Open Access Publishing Fund

Objective: We propose a modular stretchable coil design using conductive threads and commercially available embroidery machines. The coil design increases customizability of coil arrays for individual patients and each body part. Methods: Eight rectangular coils were constructed with custom-fabricated stretchable tinsel copper threads incorporated onto textile. Tune, match, and detune circuits were incorporated on the coil. A hook-and-loop mechanism was used to attach and decouple the modular coils. Phantom and in vivo scans at various anatomical flexion angles were acquired to highlight performance, and a temperature test was performed to verify safety. Results: In vivo MRI experiments demonstrate high sensitivity …

Water Quality Impacts Of Recycling Nutrients Using Organic Fertilizers In Circular Agricultural Scenarios, W. Lisenbee, A. Saha, P. Mohammadpour, R. Cibin, Jason Philip Kaye, C. Grady, Indrajeet Chaubey

Biological and Agricultural Engineering Faculty Publications and Presentations

CONTEXT

OBJECTIVE

METHODS

California 4-H Computer Science Education Pathway, Steven M. Worker, Roshan Nayak, Fe Moncloa

Journal of Extension

Young people need digital competency and confidence to effectively harness computing power to solve problems and design solutions; a core component is improving young people’s computational thinking. Unfortunately, access to computer science education is lacking for all youth, and in particular for youth who live in lower-income households, who are Black or Latino, or live in rural areas. With funding from Google, through the National 4-H Council, California 4-H embarked on a three-year project to build the capacity of 4-H professionals, volunteers, and teenagers to facilitate computer science education with youth. Our programming was effective as assessed with survey methodology. …

Exploring Differences In Perceived Learning For Students In Online Versus Face-To-Face Collegiate Pilot Ground Schools: A Quantitative Causal-Comparative Study, Christopher Komsa

Doctoral Dissertations and Projects

The purpose of this quantitative, causal-comparative study was to determine if there was a difference in the perceived learning of students completing online versus face-to-face collegiate pilot ground schools. Higher education institutions with pilot training programs are highly invested in student success and Federal Aviation Administration (FAA) compliance. A growing number of students are taking online courses in college, and this shift was accelerated by the COVID-19 pandemic. Perceived learning was quantified using a web-based survey that collected perceived learning data as measured by the Cognitive, Affective, and Psychomotor (CAP) Perceived Learning Scale. A sample of 86 students at University …

Corridor Counting, Anthony Bryson, Vincent Zhou, Amy Ha

Computer Science and Engineering Senior Theses

Information on traffic patterns is essential for identifying and addressing sources of traffic congestion and informing future road layouts to create safer and more efficient roads. To this end, we develop a Corridor Counting, or Multi- Camera Vehicle Counting, algorithm that quantifies the number of vehicles traveling along a specific stretch of road. Our work builds upon the related problem of Multi-Camera Vehicle Tracking and draws inspiration from methods used for Single-Camera Counting. We propose a six-step solution comprising Vehicle Detection, Feature Extraction, Single- Camera Vehicle Tracking, Re-Identification, Movement Matching, and Multi-Camera Vehicle Counting. Finally, we adapt an evaluation metric …

Two-Step Hierarchical Multi-Camera People Tracking, Eerina Haque, Eric Huang, Sihang Li

Computer Science and Engineering Senior Theses

The possibility of an efficient and accurate solution for multi-camera people tracking (MCPT) is enabled by the improvement of computing power and the advancement of machine learning technologies. The problem of multi-camera people tracking serves as a cornerstone of real-world applications such as video surveillance or warehouse automation. The current solutions for MCPT suffer from problems such as appearance inconsistency, object occlusion, etc. Our work targets tackling the challenges faced by modern MCPT algorithms to bring a more robust, efficient, and accurate solution.

The Impact Of Emojis On User Engagement With Trolling Content In Online Platforms, Diya Saraf

Computer Science and Engineering Senior Theses

This thesis examines the impact of emojis on user engagement within online discussions, particularly focusing on the trolling behavior on social media platforms such as Reddit. The central problem addressed is understanding how different types of emojis—in emotional, informational, and popularity-based categories—affect user interactions and engagement in online communications. Through a robust methodological approach, combining quantitative data analysis and Random Forest regression modeling, this research meticulously analyzes emoji usage patterns and their correlations with engagement metrics like upvotes and comments.

The results highlight that emotional and popular emojis significantly enhance engagement by facilitating emotional expression and connection among users. In …

Ragu Conversational Menu Assistant: An Llm Retrieval Augmented Generation Approach, Sam Abdel, Seth Mak, Aaron Pham, Christopher Michael

Computer Science and Engineering Senior Theses

This project introduces a novel Conversational Menu Assistant leveraging Retrieval Augmented Generation (RAG) techniques within a modified Large Language Model (LLM) framework to enhance dining experiences by providing personalized menu assistance. The main innovation lies in the system’s ability to integrate up-to-date menu information from various sources, including web scraping, into its responses, thereby circumventing the limitations commonly associated with LLMs, such as the need for frequent retraining and the challenge of handling dynamic information. Our solution addresses the pressing issue of reducing the workload on restaurant servers and streamlining the ordering process by offering precise menu details, personalized recommendations …

Investigation Of Process-Structure-Property Relationships In Additively Manufactured Chopped Fiber-Reinforced Polymer Composites, Indu Modala

Theses and Dissertations

Fiber-reinforced polymer (FRP) composites are widely used in various industries because of their high stiffness-to-weight ratio. However, traditional manufacturing processes restrict the application of FRP composites to the production of parts with simple geometries. With the advent of additive manufacturing (AM), it is possible to produce topologically optimized parts with complex geometries using chopped FRPs. Fully leveraging the advantages of AM in the fabrication of chopped FRP parts requires a thorough understanding of the effect of the process parameters on the microstructure, and subsequently on the mechanical properties of the manufactured part. This research focuses on studying the process-structure-property (P-S-P) …

Characterizing The Potential For Failure In Environment Testing Due To Bolted-Joint Friction Nonlinearity And Bilinearity, Brennen Clark

Theses and Dissertations

Nonlinear behavior in systems complicates the analysis and design of many systems in engineering. In vibration engineering, typical methods such as modal analysis fail or require significant adjustment in the presence of nonlinearity. Understanding and modeling nonlinear behavior is becoming more important in many modern engineering applications. One area that is relatively unexplored is how nonlinearity affects environment testing. This can cover a wide variety of subtopics, but this thesis focuses on failures that can occur in a system which are not predicted by corresponding linearized systems. To further limit the scope of this work, and to provide a context …

Evaluating Computational Predictions Of Magnetic Resonance Acoustic Radiation Force Imaging For Breast Cancer Focused Ultrasound Surgery, Chloe K. Nelson

Theses and Dissertations

Purpose: In magnetic resonance-guided focused ultrasound (MRgFUS) therapies performed in highly heterogeneous tissues such as the breast, the focal location must be located and characterized to guide successful treatments of tumors. Treatment time can be minimized by a priori prediction of the focal location through computational models. The purpose of this work is to evaluate numerical simulations of focused ultrasound (FUS) on their predictions of the focal location. Those simulations are compared to clinical magnetic resonance acoustic radiation force imaging (MR-ARFI) data collected during in vivo treatment of breast tumors. Methods: The focal location was evaluated prior to MRgFUS treatment …

Extreme Value Statistics Analysis Of Process Defects In Additive Manufacturing Materials, Ayorinde E. Olatunde, Kristen Hernandez, Austin Ngo, Arafath Nihar, Thomas G. Ciardi, Rachel Yamamoto, Pawan K. Tripathi, Roger H. French, John J. Lewandowski, Anirban Mondal

Faculty Scholarship

Fatigue and fracture studies focused on process defects that occur in Additive Manufacturing (AM) materials have shown that defect populations possess features which are better measured with extreme value statistics (EVS). In AM alloys, defect occurrences increase with material volume. This situation facilitates the need to model process defects in the path of fatigue crack growth with suitable statistical tools, such as EVS, which is more cost-effective when compared to destructive experiments. The application of EVS on defect space features helps determine the difference in defects present on fracture surfaces. As the fatigue quality of any material depends on its …