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Old Dominion University

Engineering Technology Faculty Publications

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Full-Text Articles in Physical Sciences and Mathematics

Integration Of Omnet++ Into A Networking Course In An Electrical Engineering Technology Program, Murat Kuzlu, Brian Emmanuel Tamayo, Salih Sarp, Otilia Popescu, Vukica M. Jovanovic Jan 2023

Integration Of Omnet++ Into A Networking Course In An Electrical Engineering Technology Program, Murat Kuzlu, Brian Emmanuel Tamayo, Salih Sarp, Otilia Popescu, Vukica M. Jovanovic

Engineering Technology Faculty Publications

Networking courses are an integral part of electrical engineering technology programs as the majority of electronics in the modern day are required to communicate with each other. They are also getting more attention in manufacturing engineering technology programs because of the development of emerging technologies in Industry 4.0 arena. From laptops, computers, cellphones, modern day vehicles and smart refrigerators, these devices require a certain level of networking in order to communicate with other devices, whether it be locally, or even across the other side of the world. The objective of networking courses in an electrical engineering program is to demonstrate …

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Development Of A Simevents Model For Printed Circuit Board (Pcb) Assembly Processes, Siqin Dong, Mileta Tomovic, Krishnanand Kaipa Jan 2023

Development Of A Simevents Model For Printed Circuit Board (Pcb) Assembly Processes, Siqin Dong, Mileta Tomovic, Krishnanand Kaipa

Engineering Technology Faculty Publications

Printed circuit boards (PCBs) are the foundational building blocks of most modern electronic devices. PCB assembly is defined as the process of mounting different electronic components on a PCB. Circuit board assembly utilizes an automated technique with most steps completed by machines for different operations (e.g., pick-and-place components, soldering, etc.). In this paper, details of a student course project, carried out at Old Dominion University, on the design and simulation of PCB assembly processes based on MATLAB discrete-event system are presented. An essential component in the advanced manufacturing technology course is the hands-on experience where students implement multiple software simulation …

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Cybersecurity And Digital Privacy Aspects Of V2x In The Ev Charging Structure, Umit Cali, Murat Kuzlu, Onur Elma, Osman Gazi Gucluturk, Ahmet Kilic, Ferhat Ozgur Catak Jan 2023

Cybersecurity And Digital Privacy Aspects Of V2x In The Ev Charging Structure, Umit Cali, Murat Kuzlu, Onur Elma, Osman Gazi Gucluturk, Ahmet Kilic, Ferhat Ozgur Catak

Engineering Technology Faculty Publications

With the advancement of green energy technology and rising public and political acceptance, electric vehicles (EVs) have grown in popularity. Electric motors, batteries, and charging systems are considered major components of EVs. The electric power infrastructure has been designed to accommodate the needs of EVs, with an emphasis on bidirectional power flow to facilitate power exchange. Furthermore, the communication infrastructure has been enhanced to enable cars to communicate and exchange information with one another, also known as Vehicle-to-Everything (V2X) technology. V2X is positioned to become a bigger and smarter system in the future of transportation, thanks to upcoming digital technologies …

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Development Of A Data Science Curriculum For An Engineering Technology Program, Salih Sarp, Murat Kuzlu, Otilia Popescu, Vukica M. Jovanovic, Zafer Acar Jan 2023

Development Of A Data Science Curriculum For An Engineering Technology Program, Salih Sarp, Murat Kuzlu, Otilia Popescu, Vukica M. Jovanovic, Zafer Acar

Engineering Technology Faculty Publications

Data science has gained the attention of various industries, educators, parents, and students thinking about their future careers. Statistics departments have traditionally offered data science courses for a long time. The main objective of these courses is to examine the fundamental concepts and theories. However, teaching data science courses has also expanded to other disciplines due to the vast amount of data being collected by numerous modern applications. Also, someone needs to learn how to collect and process data, especially from industrial devices, because of the recent development of Internet of Things (IoT) technologies. Hence, integrating data science into the …

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Teaching Data Acquisition Through The Arduino-Driven Home Weather Station Project, Sheryl Dutton, Kurt Galderisi, Murat Kuzlu, Otilia Popescu, Vukica Jovanovic Jan 2023

Teaching Data Acquisition Through The Arduino-Driven Home Weather Station Project, Sheryl Dutton, Kurt Galderisi, Murat Kuzlu, Otilia Popescu, Vukica Jovanovic

Engineering Technology Faculty Publications

The main objective of this paper is to present one possible way to engage undergraduate students in designing a system that uses the Internet of Things (IoT) strategy for data acquisition and management. The MATLAB home weather station project presented here was developed by a team of students for the senior design course in the Electrical Engineering Technology undergraduate program at Old Dominion University (ODU). The main purpose of this project was for undergraduate students to learn how to create a localized, compact, and precise weather station. Utilizing various sensors, both homemade and sourced online, this weather station is capable …

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Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp Jan 2023

Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp

Engineering Technology Faculty Publications

The Arduino platform has long been an efficient tool in teaching electrical engineering technology, electrical engineering, and computer science concepts in schools and universities and introducing new learners to programming and microcontrollers. Numerous Arduino projects are widely available through the open-source community, and they can help students to have hands-on experience in building circuits and programming electronics with a wide variety of topics that can make learning electrical prototyping fun. The educational fields of electrical engineering and electrical engineering technology need continuous updating to keep up with the continuous evolution of the computer system. Although the traditional Arduino platform has …

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Digital Energy Platforms Considering Digital Privacy And Security By Design Principles, Umit Cali, Marthe Fogstad Dynge, Ahmed Idries, Sambeet Mishra, Ivanko Dmytro, Naser Hashemipour, Murat Kuzlu, Aleksandra Mileva (Ed.), Steffen Wendzel (Ed.), Virginia Franqueira (Ed.) Jan 2023

Digital Energy Platforms Considering Digital Privacy And Security By Design Principles, Umit Cali, Marthe Fogstad Dynge, Ahmed Idries, Sambeet Mishra, Ivanko Dmytro, Naser Hashemipour, Murat Kuzlu, Aleksandra Mileva (Ed.), Steffen Wendzel (Ed.), Virginia Franqueira (Ed.)

Engineering Technology Faculty Publications

The power system and markets have become increasingly complex, along with efforts to digitalize the energy sector. Accessing flexibility services, in particular, through digital energy platforms, has enabled communication between multiple entities within the energy system and streamlined flexibility market operations. However, digitalizing these vast and complex systems introduces new cybersecurity and privacy concerns, which must be properly addressed during the design of the digital energy platform ecosystems. More specifically, both privacy and cybersecurity measures should be embedded into all phases of the platform design and operation, based on the privacy and security by design principles. In this study, these …

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Defending Ai-Based Automatic Modulation Recognition Models Against Adversarial Attacks, Haolin Tang, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Yanxiao Zhao Jan 2023

Defending Ai-Based Automatic Modulation Recognition Models Against Adversarial Attacks, Haolin Tang, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Yanxiao Zhao

Engineering Technology Faculty Publications

Automatic Modulation Recognition (AMR) is one of the critical steps in the signal processing chain of wireless networks, which can significantly improve communication performance. AMR detects the modulation scheme of the received signal without any prior information. Recently, many Artificial Intelligence (AI) based AMR methods have been proposed, inspired by the considerable progress of AI methods in various fields. On the one hand, AI-based AMR methods can outperform traditional methods in terms of accuracy and efficiency. On the other hand, they are susceptible to new types of cyberattacks, such as model poisoning or adversarial attacks. This paper explores the vulnerabilities …

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Influence Of Defects On In-Plane Dynamic Properties Of Hexagonal Ligament Chiral Structures, Ning An, Xunwen Su, Dongmei Zhu, Mileta M. Tomovic Sep 2022

Influence Of Defects On In-Plane Dynamic Properties Of Hexagonal Ligament Chiral Structures, Ning An, Xunwen Su, Dongmei Zhu, Mileta M. Tomovic

Engineering Technology Faculty Publications

Although the six-ligament chiral structure has many unique properties, due to its special structure, the stress concentration is prone to defects. In addition, additive manufacturing is also prone to defects. This paper studies the effect of defects, which is helpful for the better application of the six-ligament chiral structure. Several new six-ligament chiral structures with random and concentrated defects were designed to explore the effects of the defects on the in-plane dynamic properties. The structures were studied with the finite element ANSYS/LSDYNA numerical simulation and experimental methods. According to the defect-free six-ligament chiral structures exhibiting different deformation modes at different …

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Security Concerns On Machine Learning Solutions For 6g Networks In Mmwave Beam Prediction, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Umit Cali, Devrim Unal Jan 2022

Security Concerns On Machine Learning Solutions For 6g Networks In Mmwave Beam Prediction, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Umit Cali, Devrim Unal

Engineering Technology Faculty Publications

6G – sixth generation – is the latest cellular technology currently under development for wireless communication systems. In recent years, machine learning (ML) algorithms have been applied widely in various fields, such as healthcare, transportation, energy, autonomous cars, and many more. Those algorithms have also been used in communication technologies to improve the system performance in terms of frequency spectrum usage, latency, and security. With the rapid developments of ML techniques, especially deep learning (DL), it is critical to consider the security concern when applying the algorithms. While ML algorithms offer significant advantages for 6G networks, security concerns on artificial …

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A Pilot Course As A Step Towards New Academic Programs In Renewable Energies, Otilia Popescu, Orlando Ayala, Isaac Flory, Jose Fernandez, Vukica Jovanović Jan 2022

A Pilot Course As A Step Towards New Academic Programs In Renewable Energies, Otilia Popescu, Orlando Ayala, Isaac Flory, Jose Fernandez, Vukica Jovanović

Engineering Technology Faculty Publications

The challenges arising from climate change have never before in human history been more pressing for solutions. Addressing pollution and the transition to clean energies are essential problems to solve in the upcoming decades. The process of transitioning to renewable energies has started already, with some states leading the process. As the development of industries sees a fast growth, the supply of qualified engineers and technicians to support these industries needs to keep up. At the community college level, some efforts have already started to introduce courses on renewable energies as well as boot camps or certifications to prepare the …

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Augmented Reality Integrated Welder Training For Mechanical Engineering Technology, Aditya Akundi, Hamid Eisazadeh, Mona Torabizadeh Jan 2022

Augmented Reality Integrated Welder Training For Mechanical Engineering Technology, Aditya Akundi, Hamid Eisazadeh, Mona Torabizadeh

Engineering Technology Faculty Publications

The shortage of welders is well documented and projected to become more severe for various industries such as shipbuilding in coming years. It is mainly because welding training is a critical and often costly endeavor. This study examines the training potential using augmented reality technology as a critical part of welder training for mechanical engineering technology students. This study assessed the performance of two groups of MET students trained with two different methods. One group received training with the traditional method in three sessions. The second group acquired training initially with an augmented reality welding system for three sessions. Then, …

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Development Of Experiential Learning Experiences For K-12 Students Focusing On Smart Cities, Murat Kuzlu, Vukica Jovanovic, Nathan Puryear, Patrick J. Martin, Sherif Abdelwahed, Özgür Güler Jan 2022

Development Of Experiential Learning Experiences For K-12 Students Focusing On Smart Cities, Murat Kuzlu, Vukica Jovanovic, Nathan Puryear, Patrick J. Martin, Sherif Abdelwahed, Özgür Güler

Engineering Technology Faculty Publications

The main objective of this paper is to describe a project focused on the development of experiential learning experiences for undergraduate and graduate students focusing on smart cities. The future workforce needs students with various data analytics skills, service reliability, and sustainability. The team of researchers from Old Dominion University and Virginia Commonwealth University is developing a virtual smart city lab environment at both universities and collaborating on multiple research projects. The main purpose of this virtual labs is to provide a testbed that can be used for students who are interested in careers related to cyber-physical systems (CPS). These …

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Defensive Distillation-Based Adversarial Attack Mitigation Method For Channel Estimation Using Deep Learning Models In Next-Generation Wireless Networks, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Umit Cali, Ozgur Guler Jan 2022

Defensive Distillation-Based Adversarial Attack Mitigation Method For Channel Estimation Using Deep Learning Models In Next-Generation Wireless Networks, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Umit Cali, Ozgur Guler

Engineering Technology Faculty Publications

Future wireless networks (5G and beyond), also known as Next Generation or NextG, are the vision of forthcoming cellular systems, connecting billions of devices and people together. In the last decades, cellular networks have dramatically grown with advanced telecommunication technologies for high-speed data transmission, high cell capacity, and low latency. The main goal of those technologies is to support a wide range of new applications, such as virtual reality, metaverse, telehealth, online education, autonomous and flying vehicles, smart cities, smart grids, advanced manufacturing, and many more. The key motivation of NextG networks is to meet the high demand for those …

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Bfv-Based Homomorphic Encryption For Privacy-Preserving Cnn Models, Febrianti Wibawa, Ferhat Ozgur Catak, Salih Sarp, Murat Kuzlu Jan 2022

Bfv-Based Homomorphic Encryption For Privacy-Preserving Cnn Models, Febrianti Wibawa, Ferhat Ozgur Catak, Salih Sarp, Murat Kuzlu

Engineering Technology Faculty Publications

Medical data is frequently quite sensitive in terms of data privacy and security. Federated learning has been used to increase the privacy and security of medical data, which is a sort of machine learning technique. The training data is disseminated across numerous machines in federated learning, and the learning process is collaborative. There are numerous privacy attacks on deep learning (DL) models that attackers can use to obtain sensitive information. As a result, the DL model should be safeguarded from adversarial attacks, particularly in medical data applications. Homomorphic encryption-based model security from the adversarial collaborator is one of the answers …

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Security Hardening Of Intelligent Reflecting Surfaces Against Adversarial Machine Learning Attacks, Ferhat Ozgur Catak, Murat Kuzlu, Haolin Tang, Evren Catak, Yanxiao Zhao Jan 2022

Security Hardening Of Intelligent Reflecting Surfaces Against Adversarial Machine Learning Attacks, Ferhat Ozgur Catak, Murat Kuzlu, Haolin Tang, Evren Catak, Yanxiao Zhao

Engineering Technology Faculty Publications

Next-generation communication networks, also known as NextG or 5G and beyond, are the future data transmission systems that aim to connect a large amount of Internet of Things (IoT) devices, systems, applications, and consumers at high-speed data transmission and low latency. Fortunately, NextG networks can achieve these goals with advanced telecommunication, computing, and Artificial Intelligence (AI) technologies in the last decades and support a wide range of new applications. Among advanced technologies, AI has a significant and unique contribution to achieving these goals for beamforming, channel estimation, and Intelligent Reflecting Surfaces (IRS) applications of 5G and beyond networks. However, the …

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A Comparison Of Deep Learning Algorithms On Image Data For Detecting Floodwater On Roadways, Sarp Salih, Kuzlu Murat, Zhao Yanxiao, Cetin Mecit Jan 2022

A Comparison Of Deep Learning Algorithms On Image Data For Detecting Floodwater On Roadways, Sarp Salih, Kuzlu Murat, Zhao Yanxiao, Cetin Mecit

Engineering Technology Faculty Publications

Object detection and segmentation algorithms evolved significantly in the last decade. Simultaneous object detection and segmentation paved the way for real-time applications such as autonomous driving. Detection and segmentation of (partially) flooded roadways are essential inputs for vehicle routing and traffic management systems. This paper proposes an automatic floodwater detection and segmentation method utilizing the Mask Region-Based Convolutional Neural Networks (Mask-R-CNN) and Generative Adversarial Networks (GAN) algorithms. To train the model, manually labeled images with urban, suburban, and natural settings are used. The performances of the algorithms are assessed in accurately detecting the floodwater captured in images. The results show …

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A Look Into Increasing The Number Of Veterans And Former Government Employees Converting To Career And Technical Cybersecurity Teachers, Vukica M. Jovanovic, Michael Anthony Crespo, Drew E. Brown, Deborah Marshall, Otilia Popescu, Murat Kuzlu, Petros J. Katsioloudis, Linda Vahala Jul 2021

A Look Into Increasing The Number Of Veterans And Former Government Employees Converting To Career And Technical Cybersecurity Teachers, Vukica M. Jovanovic, Michael Anthony Crespo, Drew E. Brown, Deborah Marshall, Otilia Popescu, Murat Kuzlu, Petros J. Katsioloudis, Linda Vahala

Engineering Technology Faculty Publications

The current state of technology with recent explosions in the digital processing of paperwork, computer networking use, and online and virtual approaches to areas, which until very recently had traditional and non-computerized ways of operating, led to a steady increase in the demand for jobs in the area of computer science and cybersecurity. The education system, the pipeline for the incoming workforce, needs to keep up with this tremendous pace in technology and the job market. The current K-12 school system has been extensively challenged to fill out necessary positions in order to address the increasing need for programs that …

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Wg2An: Synthetic Wound Image Generation Using Generative Adversarial Network, Salih Sarp, Murat Kuzlu, Emmanuel Wilson, Ozgur Guler Mar 2021

Wg2An: Synthetic Wound Image Generation Using Generative Adversarial Network, Salih Sarp, Murat Kuzlu, Emmanuel Wilson, Ozgur Guler

Engineering Technology Faculty Publications

In part due to its ability to mimic any data distribution, Generative Adversarial Network (GAN) algorithms have been successfully applied to many applications, such as data augmentation, text-to-image translation, image-to-image translation, and image inpainting. Learning from data without crafting loss functions for each application provides broader applicability of the GAN algorithm. Medical image synthesis is also another field that the GAN algorithm has great potential to assist clinician training. This paper proposes a synthetic wound image generation model based on GAN architecture to increase the quality of clinical training. The proposed model is trained on chronic wound datasets with various …

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Role Of Artificial Intelligence In The Internet Of Things (Iot) Cybersecurity, Murat Kuzlu, Corinne Fair, Ozgur Guler Feb 2021

Role Of Artificial Intelligence In The Internet Of Things (Iot) Cybersecurity, Murat Kuzlu, Corinne Fair, Ozgur Guler

Engineering Technology Faculty Publications

In recent years, the use of the Internet of Things (IoT) has increased exponentially, and cybersecurity concerns have increased along with it. On the cutting edge of cybersecurity is Artificial Intelligence (AI), which is used for the development of complex algorithms to protect networks and systems, including IoT systems. However, cyber-attackers have figured out how to exploit AI and have even begun to use adversarial AI in order to carry out cybersecurity attacks. This review paper compiles information from several other surveys and research papers regarding IoT, AI, and attacks with and against AI and explores the relationship between these …

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The Enlightening Role Of Explainable Artificial Intelligence In Chronic Wound Classification, Salih Sarp, Murat Kuzlu, Emmanuel Wilson, Umit Cali, Ozgur Guler Jan 2021

The Enlightening Role Of Explainable Artificial Intelligence In Chronic Wound Classification, Salih Sarp, Murat Kuzlu, Emmanuel Wilson, Umit Cali, Ozgur Guler

Engineering Technology Faculty Publications

Artificial Intelligence (AI) has been among the most emerging research and industrial application fields, especially in the healthcare domain, but operated as a black-box model with a limited understanding of its inner working over the past decades. AI algorithms are, in large part, built on weights calculated as a result of large matrix multiplications. It is typically hard to interpret and debug the computationally intensive processes. Explainable Artificial Intelligence (XAI) aims to solve black-box and hard-to-debug approaches through the use of various techniques and tools. In this study, XAI techniques are applied to chronic wound classification. The proposed model classifies …

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Fluid-Wall Interactions In Pseudopotential Lattice Boltzmann Models, Cheng Peng, Luis F. Ayala, Orlando M. Ayala Jan 2021

Fluid-Wall Interactions In Pseudopotential Lattice Boltzmann Models, Cheng Peng, Luis F. Ayala, Orlando M. Ayala

Engineering Technology Faculty Publications

Designing proper fluid-wall interaction forces to achieve proper wetting conditions is an important area of interest in pseudopotential lattice Boltzmann models. In this paper, we propose a modified fluid-wall interaction force that applies for pseudopotential models of both single-component fluids and partially miscible multicomponent fluids, such as hydrocarbon mixtures. A reliable correlation that predicts the resulting liquid contact angle on a flat solid surface is also proposed. This correlation works well over a wide variety of pseudopotential lattice Boltzmann models and thermodynamic conditions.

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Gaining Insight Into Solar Photovoltaic Power Generation Forecasting Utilizing Explainable Artificial Intelligence Tools, Murat Kuzlu, Umit Cali, Vinayak Sharma, Özgür Güler Oct 2020

Gaining Insight Into Solar Photovoltaic Power Generation Forecasting Utilizing Explainable Artificial Intelligence Tools, Murat Kuzlu, Umit Cali, Vinayak Sharma, Özgür Güler

Engineering Technology Faculty Publications

Over the last two decades, Artificial Intelligence (AI) approaches have been applied to various applications of the smart grid, such as demand response, predictive maintenance, and load forecasting. However, AI is still considered to be a ‘‘black-box’’ due to its lack of explainability and transparency, especially for something like solar photovoltaic (PV) forecasts that involves many parameters. Explainable Artificial Intelligence (XAI) has become an emerging research field in the smart grid domain since it addresses this gap and helps understand why the AI system made a forecast decision. This article presents several use cases of solar PV energy forecasting using …

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Attainment Of Rigorous Thermodynamic Consistency And Surface Tension In Single-Component Pseudopotential Lattice Boltzmann Models Via A Customized Equation Of State, Cheng Peng, Luis F. Ayala, Zhicheng Wang, Orlando M. Ayala Jan 2020

Attainment Of Rigorous Thermodynamic Consistency And Surface Tension In Single-Component Pseudopotential Lattice Boltzmann Models Via A Customized Equation Of State, Cheng Peng, Luis F. Ayala, Zhicheng Wang, Orlando M. Ayala

Engineering Technology Faculty Publications

The lack of thermodynamic consistency is a well-recognized problem in the single-component pseudopotential lattice Boltzmann models which prevents them from replicating accurate liquid and vapor phase densities; i.e., current models remain unable to exactly match coexisting density values predicted by the associated thermodynamic model. Most of the previous efforts had attempted to solve this problem by introducing tuning parameters, whose determination required empirical trial and error until acceptable thermodynamic consistency was achieved. In this study, we show that the problem can be alternatively solved by properly designing customized equations of state (EOSs) that replace any cubic EOS of choice during …

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A Low-Cost Soft Robotic Hand Exoskeleton For Use In Therapy Of Limited Hand–Motor Function, Grant Rudd, Liam Daly, Vukica Jovanovic, Filip Cukov Sep 2019

A Low-Cost Soft Robotic Hand Exoskeleton For Use In Therapy Of Limited Hand–Motor Function, Grant Rudd, Liam Daly, Vukica Jovanovic, Filip Cukov

Engineering Technology Faculty Publications

We present the design and validation of a low-cost, customizable and 3D-printed anthropomorphic soft robotic hand exoskeleton for rehabilitation of hand injuries using remotely administered physical therapy regimens. The design builds upon previous work done on cable actuated exoskeleton designs by implementing the same kinematic functionality, but with the focus shifted to ease of assembly and cost effectiveness as to allow patients and physicians to manufacture and assemble the hardware necessary to implement treatment. The exoskeleton was constructed solely from 3D-printed and widely available of-the-shelf components. Control of the actuators was realized using an Arduino microcontroller, with a custom-designed shield …

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Exposing Students To Stem Careers Through Hands-On Activities With Drones And Robots, Vukica M. Jovanović, George Mcleod, Thomas E. Alberts, Cynthia Tomovic, Otilia Popescu, Tysha Batts, Ms. Mary Louise Sandy Jan 2019

Exposing Students To Stem Careers Through Hands-On Activities With Drones And Robots, Vukica M. Jovanović, George Mcleod, Thomas E. Alberts, Cynthia Tomovic, Otilia Popescu, Tysha Batts, Ms. Mary Louise Sandy

Engineering Technology Faculty Publications

Autonomous robots have been used in a variety of ways from collecting specimen in hazardous environments to space exploration. These robots can be found in various manufacturing systems as Autonomous Guided Vehicles (AGVs) to transport parts and assemblies throughout the manufacturing system. They have also been used as a vehicle to convey design thinking and other STEM-related concepts in mechanical engineering/mechanical engineering technology, electrical engineering/electrical engineering technology, computer science, and computer engineering. Various outreach events have included robotics based activities that engage students in building and programming autonomous robots for the purpose of achieving a specific task. These events are …

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Spin Response Function For Spin Transparency Mode Of Rhic, V. S. Morozov, P. Adams, Y. S. Derbenev, Y. Filatov, H. Huang, A. M. Kondratenko, M. A. Kondratenko, F. Lin, F. Méot, V. Ptitsyn, W. B. Schmidke, Y. Zhang Jan 2019

Spin Response Function For Spin Transparency Mode Of Rhic, V. S. Morozov, P. Adams, Y. S. Derbenev, Y. Filatov, H. Huang, A. M. Kondratenko, M. A. Kondratenko, F. Lin, F. Méot, V. Ptitsyn, W. B. Schmidke, Y. Zhang

Engineering Technology Faculty Publications

In the Spin Transparency (ST) mode of RHIC, the axes of its Siberian snakes are parallel. The spin tune in the ST mode is zero and the spin motion becomes degenerate: any spin direction repeats every particle turn. In contrast, the lattice of a conventional collider determines a unique stable periodic spin direction, so that the collider operates in the Preferred Spin (PS) mode. Contributions of perturbing magnetic fields to the spin resonance strengths in the PS mode are usually calculated using the spin response function. However, in that form, it is not applicable in the ST mode. This paper …

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Reliability Estimation Of Reciprocating Seals Based On Multivariate Dependence Analysis And It's Experimental Validation, Chao Zhang, Rentong Chen, Shaoping Wang, Yujie Qian, Mileta M. Tomovic Jan 2019

Reliability Estimation Of Reciprocating Seals Based On Multivariate Dependence Analysis And It's Experimental Validation, Chao Zhang, Rentong Chen, Shaoping Wang, Yujie Qian, Mileta M. Tomovic

Engineering Technology Faculty Publications

Accurate reliability estimation for reciprocating seals is of great significance due to their wide use in numerous engineering applications. This work proposes a reliability estimation method for reciprocating seals based on multivariate dependence analysis of different performance indicators. Degradation behavior corresponding to each performance indicator is first described by the Wiener process. Dependence among different performance indicators is then captured using D-vine copula, and a weight-based copula selection method is utilized to determine the optimal bivariate copula for each dependence relationship. A two-stage Bayesian method is used to estimate the parameters in the proposed model. Finally, a reciprocating seal degradation …

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Experimental Verification Of Transparent Spin Mode In Rhic, V. S. Morozov, P. Adams, Y. S. Derbenev, Y. Filatov, H. Huang, A. M. Kondratenko, M. A. Kondratenko, F. Lin, F. Méot, V. Ptitsyn, W. B. Schmidke, Y. Zhang Jan 2019

Experimental Verification Of Transparent Spin Mode In Rhic, V. S. Morozov, P. Adams, Y. S. Derbenev, Y. Filatov, H. Huang, A. M. Kondratenko, M. A. Kondratenko, F. Lin, F. Méot, V. Ptitsyn, W. B. Schmidke, Y. Zhang

Engineering Technology Faculty Publications

High electron and ion polarizations are some of the key design requirements of a future Electron Ion Collider (EIC). The transparent spin mode, a concept inspired by the figure 8 ring design of JLEIC, is a novel technique for preservation and control of electron and ion spin polarizations in a collider or storage ring. It makes the ring lattice "invisible" to the spin and allows for polarization control by small quasi-static magnetic fields with practically no effect on the beam’s orbital characteristics. It offers unique opportunities for polarization maintenance and control in Jefferson Lab’s JLEIC and in BNL’s eRHIC. The …

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Comparison Of Observed And Simulated Drop Size Distributions From Large Eddy Simulations With Bin Microphysics, Mikael K. White, Patrick Y. Chuang, Orlando Ayala, Lian-Ping Wang, Graham Feingold Jan 2019

Comparison Of Observed And Simulated Drop Size Distributions From Large Eddy Simulations With Bin Microphysics, Mikael K. White, Patrick Y. Chuang, Orlando Ayala, Lian-Ping Wang, Graham Feingold

Engineering Technology Faculty Publications

Two case studies of marine stratocumulus (one nocturnal and drizzling, the other daytime and nonprecipitating) are simulated by the UCLA large-eddy simulation model with bin microphysics for comparison with aircraft in situ observations. A high-bin-resolution variant of the microphysics is implemented for closer comparison with cloud drop size distribution (DSD) observations and a turbulent collision–coalescence kernel to evaluate the role of turbulence on drizzle formation. Simulations agree well with observational constraints, reproducing observed thermodynamic profiles (i.e., liquid water potential temperature and total moisture mixing ratio) as well as liquid water path. Cloud drop number concentration and liquid water content profiles …

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