Engineering Commons^™

Production Of Cerium Oxide And Zinc Sulfide Composites, Ted Autore

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Zinc sulfide has an infrared cutoff in the LWIR, but its low hardness makes it susceptible to rain erosion and abrasion. A composite of cerium oxide and zinc sulfide that retains an infrared cutoff in the LWIR, and with hardness higher than pure zinc sulfide is a potential solution to the rain erosion and abrasion issue. Several different processes were undertaken in this project to produce such a composite. The different reactions between ZnS and CeO2 were researched, along with the effects of different processing parameters. Composite samples were made that had a better hardness than zinc sulfide but did …

Investigating The Impact Of Stress And Irradiation Flux On Latent Track Formation In Tio2 Under Swift Heavy Ion Irradiation: A Phase Field Study, Ebrahim Ebrahimi

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Swift Heavy Ions (SHI) irradiation, characterized by high kinetic energy ions, induces significant material/structural modification, e.g., latent track. However, the intricate interaction among various physics, i.e., mechanical stress, phase transition, and heat transfer, has been ignored in the continuum-based approaches in favor of simplicity. Here, we developed a two-dimensional coupled phase-field inelastic-thermal spike (PF-iTS) model to investigate the effect of thermal crosstalk, elastic energy, and irradiation flux on latent track formation. A particular focus is placed on investigating the influence of internal mechanical stress on latent track formation. Simulation results reveal a shift in critical stopping energy and a reduction …

Architectural Optimization Of Emulator Embedded Neural Networks For Aerospace Vehicle Design, James L. Schmitz Ii

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An approach for the architecture optimization of emulator embedded neural networks is proposed. While the emulator embedded neural network has been shown to provide accurate predictions with suitable emulators, there is still a challenge regarding how to select the optimal hyperparameters of network architectures, such as, the number of neurons, layers, types of activation functions, etc. The selection of hyperparameters greatly affects the performance of the neural network model training both in terms of accuracy and efficiency. To address this challenge, this study proposes an algorithm that tests a range of hyperparameters and selects the best performing set. The algorithm …

Using Unsupervised Machine Learning To Reduce The Energy Requirements Of Active Flow Control, Jared N. Kerestes

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It is generally accepted that there exist two types of laminar separation bubbles (LSBs): short and long. The process by which a short LSB transitions to a long LSB is known as bursting. In this research, large eddy simulations (LES) are used to study the evolution of an LSB that develops along the suction surface of the L3FHW-LS at low Reynolds numbers. The L3FHW-LS is a new high-lift, high-work low-pressure turbine (LPT) blade designed at the Air Force Research Laboratory. The LSB is shown to burst over a critical range of Reynolds numbers. Bursting is discussed at length and its …

Rc Baja: Drivetrain And Chassis, Caden Harris

All Undergraduate Projects

The engineers in the CWU Mechanical Engineering Technology program were asked to design and manufacture a remote-controlled Baja car to compete in several different events. The car was required to compete in a drag race, slalom event, and Baja event against other cars created by engineering students. To compete at the highest level, the cars needed to finely balance ruggedness, weight, torque, and top speed.

This report is dedicated to the designing, manufacturing, and testing of the drivetrain and chassis that supported the RC car as it competed in the school-sanctioned competition; a partner was responsible for the steering and …

Rc Baja: Suspension And Steering, Daniel Davis

All Undergraduate Projects

Engineers enrolled in the Mechanical Engineering Technology program at Central Washington University were tasked with developing a vehicle to compete in the ASME Baja competition. The engineers were in teams of two, one focused on suspension and steering and the other focused on drive train and chassis.

To begin the design of the vehicle, engineering analyses were completed on each of the components to comply with the requirements set by the team. After completion of multiple analyses for the components of the vehicle, the dimensions were validated and have been created in a CAD program to allow for virtual assembly …

Reinforcement Learning For Optimal Kicking Actions In Humanoid Robotics: Advancing Robotic Autonomy And Versatility, Suresh Dodda, Sathish Kumar Chintala, Sukender Reddy Mallreddy, Sharath Chandra Macha, Yashwanth Vasa, Sapan Bharadwaj Bonala, Navin Kamuni, Sujatha Alla

Engineering Management & Systems Engineering Faculty Publications

Acquiring the necessary skills to perform a work effectively and efficiently requires a significant investment of time and computing power. Previous applications of Reinforcement Learning (RL) for action optimization in humanoid robotics have shown how promising this technology is for moving robotics towards true autonomy and versatility. Therefore, this study offers the first use of RL to create an entirely optimal kicking action for the Alderbaran Nao robot. Kicking motions that were steady, precise, quick, and able to kick farther than any existing RoboCup squad were generated by optimizing for a multi-objective reward function. We demonstrate that the ideal kicking …

Data Driven Trade-Off Analysis For Cybersecurity, Goskel Kucukkaya, Murat Ozer, Murat Balci, Emrah Ugurlu

Engineering Management & Systems Engineering Faculty Publications

Trade-off analysis, a specialization of systems engineering, addresses design criteria like security, cost, performance, and compliance. Monte Carlo simulations are commonly employed to generate impact scenarios for trade-off analysis combined with solution alternatives that accommodate industry-specific considerations and uncertainties. In the cyber domain, this paper proposes a methodology for data-driven trade-off analysis in cybersecurity, leveraging industry reports as primary data sources using confidentiality, integrity, and availability as trade-off analysis objectives. Distribution functions are derived to manage and model uncertainties for various industries. The approach given in this study aims to facilitate informed choices and to enhance cybersecurity decision making and …

Engineering Management And Industrial Engineering Industry And Educational Workforce Development Strategy, Robert J. Gies, Resit Unal, Charles B. Keating

Engineering Management & Systems Engineering Faculty Publications

This paper provides an overview of the development and resulting product of a collaborative industry-academia engineering management and industrial engineering workforce development strategy. In the spring of 2017, Old Dominion University's (ODU) Engineering Management and Systems Engineering Department (EMSE) approached Newport News Shipbuilding (NNS) with a concept to develop an educational initiative to support the preparation and development of the future workforce. The concept came to fruition over the next two years as a certification program in Engineering Systems and Industrial Engineering for NNS working professionals. This paper examines the primary aspects of the development of the certification program. Emphasis …

System Of Systems Engineering: A Literature Review And Research Frontiers, Charles B. Keating, Polinpapilinho F. Katina, James C. Pyne

Engineering Management & Systems Engineering Faculty Publications

System of Systems Engineering (SoSE) has existed and been developing for well over 2 decades. The time is appropriate to take a reflective look at the past and examine the future evolution of this nascent field. To address this challenge, this paper is focused on two primary objectives. First, a literature review of the SoSE field is conducted. This literature review (1) organizes the SoSE body of knowledge and provides a synthesis of major crosscutting themes, and (2) provides a scholarly critique and identifies gaps in the current state of the SoSE field. The second objective is focused on providing …

Factors Influencing Engineering Student Persistence: A Two Institution Study, Stephen Drawbaugh

Murray State Theses and Dissertations

The purpose of this study was to investigate the persistence factors of undergraduate engineering students and compare those factors at an R2 research university and a regional university. The study further investigated if these factors are different based on gender and race/ethnicity. This study used quantitative methodology to determine the significance of the differences in universities, genders, and races/ethnicities. Tinto’s (1975, 1993) student departure theory, Bean’s (1988, 2001) student departure model, Astin’s student involvement and development theory, and a study by Marra et al. (2012) provided the theoretical framework for this study. Findings from the survey sample of 52 students …

Understanding The Link Between Conflict Profiles And Team Affective Outcomes Using Lpa And Nlp Techniques, Francisco Cima, Pilar Pazos-Lago

Engineering Management & Systems Engineering Faculty Publications

Team conflict is a naturally emerging phenomenon resulting from individuals' interactions during project execution. Cross-disciplinary teams can experience higher levels of conflict than single-discipline teams because of the increased diversity of knowledge and perspectives. Research has shown that team conflict can emerge from different types of disagreements (cognitive and interpersonal), which have different implications for team functioning. Past empirical research has focused on the impact of both conflict types independent from each other while overlooking their combined effects. This work examines the conflict profiles resulting from the combined levels of interpersonal and cognitive disagreements and their association with team outcomes. …

A Pade-Eno Flux Reconstruction For High-Speed Flows, Blake Martin

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The development of high order numerical schemes has been instrumental in advancing computational fluid dynamics (CFD), particularly for applications requiring high resolution of discontinuities and complex flow phenomena prevalent in high-speed flows. This thesis introduces the Pade-ENO scheme, a high-order method that integrates Essentially Non-Oscillatory (ENO) techniques with compact Pade stencils to achieve superior accuracy, up to 7th order, while maintaining stability in harsh environments. The scheme’s performance is evaluated through benchmark tests, including the advection equation, Burgers’ equation, and the Euler equations. For high Mach number flows, such as the sod shock tube the Pade-ENO method demonstrates its ability …

Advanced Digital Wideband Receiver Design: High Dynamic Range And Enhanced Multi-Signal Detection With Fpga-Based Custom Fft And Nyquist Folding, Kiran Jayarama

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In modern wideband receiver standards, efficient frequency spectrum utilization is essential to meet demands for high data rates, reduced latency, and enhanced connectivity. The Fast Fourier Transform (FFT) stands as a pivotal technology, particularly in radar signal processing, where it supports tasks such as target detection, range estimation, and velocity estimation by analyzing the frequency content of the received radar signals. This dissertation introduces the design of an advanced digital wideband receiver featuring a high dynamic range for multiple signals, with a focus on improved performance, compact size, and reduced power consumption, implemented on an FPGA using custom hardware. Key …

Fabricating And Analyzing Liquid And Polymer Electrolytes For Sodium Ion Batteries, Kekule Augustine

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The abundance and the cost-effectiveness of sodium resources have made sodium-ion batteries (SIBs) viable alternatives to lithium-ion batteries. Developing low-cost and high-performance electrolytes is one of the key areas for the advancement of SIB technology. The highly conductive liquid or solid electrolytes have the potential for practical sodium-ion battery applications. Long-term stability, alternative polymers, and full-cell integrations are other avenues that need further research to improve scalability and performance for SIBs. This research covers preparing and evaluating liquid and polymer electrolytes, with a focus on ionic conductivities. Liquid electrolytes were prepared by the dissolution of different sodium salts including NaCl, …

Mouralherwaqh Coastal Wetland Road Crossing Da'luk, Natalie Mendez

Cal Poly Humboldt theses and projects

The integration of Indigenous and Western science plays an essential role in Tribally led collaborations for land management. This process of woven sciences is rooted in reciprocal relations and partnerships guided by Tribal Nations. Our cohort was invited by Wiyot Tribal Representatives to investigate a culvert located within the wetlands of Mouralherwaqh— a parcel of land reacquired by the Wiyot Tribe in 2022. This document seeks to share our experience and analysis as part of the Wiyot Tribe’s broader journey in navigating ecocultural restoration projects within Mouralherwaqh. The four community interests we investigated for the wetland crossing included a resized …

Restoration Of Strength In Polyamide Woven Glass Fiber Organosheets By Hot Pressing, Mohammad Nazmus Saquib, Edwing Chaparro-Chavez, Christopher Morris, Kuthan Çelebi, Diego Pedrazzoli, Mingfu Zhang, Sergii G. Kravchenko, Oleksandr G. Kravchenko

Mechanical & Aerospace Engineering Faculty Publications

Thermoplastic composite organosheets (OSs) are increasingly recognized as a viable solution for automotive and aerospace structures, offering a range of benefits including cost-effectiveness through high-rate production, lightweight design, impact resistance, formability, and recyclability. This study examines the impact response, post-impact strength evaluation, and hot-pressing repair effectiveness of woven glass fiber nylon composite OSs across varying impact energy levels. Experimental investigations involved subjecting composite specimens to impact at varying energy levels using a drop-tower test rig, followed by compression-after-impact (CAI) tests. The results underscore the exceptional damage tolerance and improved residual compressive strength of the OSs compared to traditional thermoset composites. …

An Efficient And Trusted Deep Learning Framework For Real-Time Ppe Detection In Secure Iomt Environment, Anusha Verma

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Occupationally-acquired infections impact thousands of healthcare workers (HCWs) in the U.S., with many cases preventable through proper use of personal protective equipment (PPE). This study seeks to develop a robust system to enhance PPE compliance and reduce infection risks among HCWs. The objectives of this thesis are twofold: (1) to create a hybrid machine learning model that combines object detection and keypoint detection to ensure correct donning and doffing of PPE, and (2) to design a real-time feedback system using LED indicators and a display interface to offer actionable guidance to HCWs during PPE usage. The goal is to optimize …

An Enhanced Real-Time Object Detection Of Helmets And License Plates Using A Lightweight Yolov8 Deep Learning Model, Mounika Thatikonda

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Traffic surveillance and enforcement heavily depend on the real-time detection of helmets and license plates, particularly in high-density urban environments. This study presents a dynamic and optimized lightweight model, the proposed G-YOLOv8n, designed for resource constrained edge devices like the Raspberry Pi. By integrating the GhostNet module into the YOLOv8n architecture, this research achieves a nearly 50% reduction in model size and computational load, while maintaining comparable detection accuracy to the original YOLOv8n. These enhancements enable real-time processing capabilities crucial for traffic monitoring operations. The growing demand for real-time, low-power solutions in intelligent transportation systems necessitates lightweight, efficient detection models. …

Integrative Machine Learning Approaches For Enhanced Classification Of Genomic Sequences: A Next-Generation Sequencing Perspective, Sujatha Alla, Nagesh Bheesetty, Sai Gireesh Komaragiri, Prasanthi Chidipudi, Joshit Mohanty, Sathish Kumar Chintala, Jubin Thomas, Jayapal Vummadi, Hemanth Volikatla, Navin Kamuni

Engineering Management & Systems Engineering Faculty Publications

The advent of Next-Generation Sequencing (NGS) techniques has revolutionized genomic research by enabling the rapid sequencing of DNA and RNA. This data can be used for various applications, including genome sequencing, transcriptome profiling, metagenomics, and epigenetics studies. For this study, DNA classifier dataset was extracted from UCI repository of machine learning databases. This vast amount of genomic data necessitates the development of sophisticated machine learning (ML) models for effective classification and analysis. This study presents a comprehensive comparison of various ML models, including Support Vector Machines (SVM), Random Forests (RF), and Neural Networks (NNs), approaches, in classifying genomic data. We …

College Of Computing And Engineering Graduate Catalog 2024-2025, Nova Southeastern University

College of Psychological Services / College of Psychology Postgraduate Student and Course Catalogs

No abstract provided.

Educating For Shalom In Engineering, Julie Wildschut

University Faculty Publications and Creative Works

Created in the image of God, humans have a unique purpose within creation. We are given the task of worshipping God (Isa 43:21), sharing the gospel of Jesus Christ (Mat 28:18-20), discovering and developing the potentials of creation (Gen 2:15), struggling and praying for shalom (Isa 1:17), and celebrating instances of God’s coming kingdom (Isa 9:1-7, Col 1:19-20). As Christian engineering educators, we have the additional task of preparing students to become capable engineers and to use those skills in response to God’s call in their lives. We have the blessing of not only teaching the technical aspects of engineering, …

Project Control System (Pcs) Implementation In Engineering And Construction Projects: An Empirical Study In Saudi's Petroleum And Chemical Industry, Sahar Jawad, Ann Ledwith, Rashid Khan

School of Cybersecurity Faculty Publications

Purpose

There is growing recognition that effective project control systems (PCS) are critical to the success of projects. The relationship between the individual elements of PCS and successfully achieving project objectives has yet to be explored. This research investigates the enablers and barriers that influence the elements of PCS success and drive project objectives.

Design/methodology/approach

This study adopts a mixed approach of descriptive analysis and regression models to explore the impact of six PCS elements on project outcomes. Petroleum and chemical projects in Saudi Arabia were selected as a case study to validate the research model.

Findings

Data from a …

Digitalization Of Railway Transportation Through Ai-Powered Services: Digital Twin Trains, Salih Sarp, Murat Kuzlu, Vukica Jovanovic, Zekeriya Polat, Ozgur Guler

Engineering Technology Faculty Publications

Digitalization is a key concept that transformed the various industries through technologies like Internet of Things (IoT), Artificial Intelligence (AI), and Digital Twin (DT). Although innovations provided by the advancement of digitalization have paved the way for more efficient operations and products for transportation, the rail transportation sector struggles to keep up with the rest of the transportation industry, since trains are designed to last for decades, and the insufficient infrastructure investment leads to multiple railroad derailments across the globe. Therefore, the primary aim is to transform current railway systems into human-centric, adaptable, sustainable and future-proof networks, aligning with Industry …

Void Fraction And Quality Correlation Analysis Using The Separated Flow Model For Pulsed-Power Heat Loads, Zachary Joseph Carner

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Aircraft platforms are continually upgraded with increasingly high quantities of high-powered electronics. As such, efficient thermal management systems are crucially important to overcome system instabilities and support pulsed power profiles. To create effective thermal control systems, it is imperative to thoroughly examine and account for a variety of potential system behaviors caused by transient changes in the flow regime. If left unconstrained, these changes will create thermal instabilities, which can severely damage electronics and hurt the overall reliability of the aircraft. These instabilities can be described by both void fraction and quality. Electrical Capacitance Tomography (ECT) allows for the collection …

Mechanical Reliability Of Aerosol Jet Printed Sensors And Interconnects, Lemuel A. Duncan

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Heterogeneous integration (HI) is currently being investigated to maintain the pace of technological progress in the electronics industry. With the recent acceleration witnessed in additive manufacturing (AM) technology, interest has been expressed in introducing aerosol jet (AJ) printing to the fabrication process for sensors and electronic packages. Integrating AM technology in these areas promises design flexibility and minimal material waste. Three AJ printed applications investigated in this work include strain sensors, electrical interconnects, and metal embedded chip assemblies. Before moving forward with the use of AJ printing in these applications, it is necessary to evaluate their performance under standard mechanical …

Integrating Knowledge Graphs With Large Language Models For Natural Language Querying, Rakesh Kandula

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This research explores the integration of knowledge graphs with large language models that have already been trained on a vast pool of unstructured text data. Large language models trained on this type of data have a tendency to hallucinate and produce factually inaccurate results. This behavior is primarily due to the data being trained is unstructured and huge text corpus, and large language model uses predictive text analysis methods to obtain a response. These issues can be addressed by applying Retrieval Augmented Generation and Fine-tuning to large language models, employing an underlying domainspecific knowledge graph. Integrating knowledge graph and large …

Prediction Interpretations Of Ensemble Models In Chronic Kidney Disease Using Explainable Ai, K M Tawsik Jawad

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Chronic Kidney Disease (CKD) poses significant health and financial threat to millions of patients all around the world. The irreversible nature of this disease not just leads to comorbid diseases like Diabetes Mellitus, Hypertension, Anemia, Bone Disease, Neurological Implants etc. It can permanently damage the kidney by progressing to Acute Kidney Injury (AKI) or End Stage Renal Diseases (ESRD). The risk factors of CKD become more dangerous as patients suffering from it have little to no idea about the presence of CKD in their body until it takes the shape of AKI or ESRD. There are severe economic burdens for …

Biomechanical Simulation Of Cardiovascular Implantable Electronic Device Leads With Residual Properties, Anmar Mahdi Salih

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Implantable leads used in pacemakers, defibrillators, and cardiac resynchronization therapy are designed for in-vivo applications, yet their longevity is inevitably shaped by the conditions within the human body. The mechanical behavior of these leads can be affected over time, necessitating the evaluation of their residual properties. Two main insulators, silicone, and polyurethane are commonly used for the outer insulation of cardiac leads. Understanding the long-term performance of these insulators is crucial for ensuring the reliability and safety of cardiac implantable devices. The research aims to assess the long-term mechanical properties and performance of implantable leads utilized in cardiovascular implantable electronic …

Potential Role Of Ttt Complex In Regulating Dna Replication Checkpoint In The Fission Yeast Schizosaccharomyces Pombe, Sankhadip Bhadra

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DNA replication can be perturbed by various agents that slow or stall the replication forks, causing replication stress. If undetected, stressed forks may collapse, causing mutagenic DNA damage or cell death. In response to replication stress and DNA damage, the eukaryotic cell activates the DNA replication checkpoint (DRC) and DNA damage checkpoint (DDC) pathways to promote DNA synthesis, repair, and cell survival. The two cell cycle checkpoint pathways are controlled by the protein sensor kinases Rad3 (hATR/scMec1) and Tel1 (hATM/scTel1) in fission yeast, although Tel1 plays a minimal role in checkpoint functions. Rad3 and Tel1 belong to a family of …