Digital Commons Network^™

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 …

Topological Photonic Metasurfaces For Light Manipulation And Strong Light-Matter Interaction, Svetlana Kiriushechkina

Dissertations and Theses

High-resolution nanopatterning techniques, such as electron beam lithography, extended opportunities for implementation of the various designs of photonic structures which exhibit exciting physical phenomena in the optical domain. A straightforward fabrication of on-slab nanostructures is advantageous for integration with various photonic on-chip devices. Last decade all-dielectric periodic nanostructures (photonic metasurfaces) boost a growth of novel optical technologies, from ultra-sensitive detectors to compact beam structured lasers. Moreover, they represent one of the most promising platforms in which topological phases can be explored and exploited.

Topological photonic structures attract a significant interest owing to their outstanding properties such as a resilience to …

Machine Learning Driven Resource Allocation In Edge Cloud, Arslan Qadeer Dr

Dissertations and Theses

Next generation mobile and immersive applications (e.g., Augmented Reality (AR), Virtual Reality (VR), Extended reality (XR)), and Internet of Things (IoTs) provide richer functionalities which possess resource-hungry and real-time constraints. To conserve energy and improve performance of such devices, certain computationally heavy tasks can be executed remotely by offloading them to the back-end cloud (BC) and utilizing its abundant compute resources. However, the long distance between a mobile/IoT device and the BC causes huge network delay, thus, deteriorating the user experience of real-time applications. Edge-cloud (EC) and beyond 5G (B5G) wireless communication are envisioned to cope with the above compute …

Nonlinear And Time-Modulated Metamaterials: Applications At Microwave Frequencies, Hady Mohammed Saied Sayed Moussa

Dissertations and Theses

Metamaterials (the Greek prefix meta, means beyond) are artificially structured materials that interact with the incoming waves in extraordinary ways, beyond the properties of natural materials, yielding unusual and exotic electromagnetics phenomena. By careful engineering of the material properties, invoking nonlinear elements and/or time-modulating some of the material parameters, linearity and/or time-invariance can be broken in metamaterials, enabling extraordinary wave phenomena that open opportunities for the microwave engineering community, including the creation of nonreciprocal devices, frequency conversion, and more. In this dissertation, we explore, investigate, design, and fabricate metamaterials that open new applications for nonlinearity-based and time-varying devices, particularly in …

Comprehensive Fault Diagnostics And Performance Forecasting Of Wind Turbines Through Condition Monitoring Solutions, Shuo Zhang

Doctoral

The operation and maintenance (O&M) issues of wind turbines (WTs) are challenging because unplanned maintenance, caused by sudden component failures, can bring about durable downtimes and significant revenue losses. It is important to carry out effective fault diagnostics and prognostics schemes under the rapid development of wind power generation. Hence, Condition Monitoring (CM) solutions focus on measurements and detections of high-risk WT components, which could result in high failure rates and long downtimes. Machine Learning (ML) models have been commonly applied in CM to allocate imminent indications of failure or degradation for curtailing the O&M costs of WTs. By way …

Synthesis And Application Of Redox-Active Covalent Organic Frameworks In Rechargeable Batteries, Mohammad K. Shehab

Theses and Dissertations

Synthesis and Application of Redox-Active Covalent Organic Frameworks in Rechargeable Batteries

Mohammad K. Shehab

Department of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States

Abstract

In recent years, lithium-ion batteries (LIBs) have been considered the dominant energy storage devices for portable electronics and electric vehicles due to their high energy density, low self-discharge rate, and long cycle life. In LIBs, the traditional positive electrodes employed are mainly derived from metal-containing inorganic compounds composed of cobalt, iron, nickel, or manganese (LiCoO₂, LiMn₂O₄, and LiFePO₄) coupled with graphite as the negative electrode. Despite …

Real-Time Motion Controller For Human-Robot Teams Utilizing Artificial Potential Fields, Gabriella Graziani

Theses and Dissertations

This thesis presents a real-time robotic motion control system for human-robot teams. The framework utilizes artificial potential fields (APFs) to guide robotic agents towards a “goal” agent while navigating around “obstacle” agents; these goals and obstacles are also dynamic agents with their own set of tasks. This system is also developed for a live-programming environment, where a controlling agent updates the tasks of all agents within the system at any time during the system’s runtime. This motion controller was created and tested for a human-robot choreographic team. After the controller was fully integrated on a Trossen Robotic LoCobot Wx200 robotic …

Surface Properties, Work Function, And Thermionic Electron Emission Characterization Of Materials For Next-Generation Dispenser Cathodes, Antonio Mantica

Theses and Dissertations--Chemical and Materials Engineering

A dispenser cathode’s ability to thermionically emit electrons is highly dependent on its material properties, especially those of the surface. Understanding the relationship between surface properties and electron emission, therefore, is vital to reach the next generation of the many vacuum electron devices (VEDs) that rely on the physics of electron emission. In the past century, many techniques have been developed to characterize material surfaces and quantify thermionic emission. These techniques are based on a wide range of different physical phenomena, including measuring photoemission via the photoelectric effect, measuring the electrostatic potential between metals in electrical contact, and current collection …

A Robust Model For Spot Virtual Machine Bidding In The Cloud Market Using Information Gap Decision Theory (Igdt), Mona Naghdehforoushha, Mehdi Dehghan Takht Fooladi, Mohammed Hossein Rezvani, Mohammad Mehdi Gilanian Sadeghi

Turkish Journal of Electrical Engineering and Computer Sciences

The spot market is one of the most common cloud markets where cloud providers, such as Amazon EC2, rent their surplus computing resources at lower prices in the form of spot virtual machines (SVMs). In this market, which is often managed through an auction mechanism, users seek optimal bidding strategies for renting SVMs to minimize cost and risk. Uncertainty in the price of SVMs and their low availability/reliability is a challenging issue to bid on the user side. In this paper, we present a robust model for minimizing the cost of executing tasks by considering the uncertainty of the price …

Coulomb Blockade-Mediated Field Emission Sources Using Ultra-Nanocrystalline Diamond, Jevin Jensen

Graduate Research Theses & Dissertations

Coulomb Blockade effects in field emission provide interesting means of achieving brighter electron sources for numerous applications, ranging from vacuum electronics to the next generation of electron beam technology. Microelectronics cleanroom methods are presented in this thesis for production of field emission sources moderated by the Coulomb Blockade. The use of common processes is an essential step toward widespread experimentation with Coulomb Blockade-mediated field emission apparatuses. The main feature to be explored is the use of nano-diamond films for their potential applicability for this desired outcome. Ultra-Nanocrystalline Diamond is used in two different ways to achieve this, both as a …

Prioritized Object Detection Integrating Fuzzy Logic Risk Assessment And Planned Path., Khatereh Mohammadi

Graduate Research Theses & Dissertations

Nowadays, Autonomous Vehicles are in the spotlight as a response to the challenges stemming from population growth, worsening traffic congestion, and rising road accidents. Researchers and companies are concentrating on developing Automated Driving Systems (ADS) to tackle these issues.Of the various components that constitute an autonomous vehicle, perception plays a pivotal role, akin to the function of human eyes and the human brain. Therefore, ensuring precise and reliable perception within Autonomous Vehicles is paramount. This thesis is inspired by the principles of human perception, particularly on the road, and endeavors to replicate this process. Just as a human driver does …

A High-Precision Electron Emission Model: Computational Methods For Nanoscale Structures, Alister J. Tencate

Graduate Research Theses & Dissertations

The high-intensity, high-brightness and precision frontiers for charged particle beams are an increasingly important focus for study. Electron microscopy has demonstrated high quality beams from a single nanotip emitter, and cathodes of structured nanoscale arrays show promise as ultracold electron sources. Optimization of the cathode design for precision applications necessitates a detailed treatment of the interplay between the structure geometry, quantum mechanical emission mechanism, and electromagnetic interactions between the emitted electrons and the boundary interface. This dissertation details the numerical tools developed to simulate these processes efficiently with enough fidelity to be accurate even in the ultracold regime.

Conventional simulation …

Analysis Of Localization Algorithms For Wireless Sensor Networks Using Binary Data, Alexander Joseph Hart

Graduate Research Theses & Dissertations

The detection, localization, and tracking of environmental and physical conditions can be accomplished using wireless sensor networks (WSNs). Recent advancements in sensors, processors, and wireless communications have improved the quality and acquisition speed of data in WSNs. However, the data gathered by a WSN is inherently random due to component and environmental variations. Thus, statistical signal processing algorithms are needed to analyze the random data in a robust way. Though many algorithms for the analysis of random data are established and available, they are problem-specific and must be adapted to the application. This thesis provides an analysis of established localization …

Probing Signal-Based Data-Driven Modeling Of Power Electronics Smart Converter Dynamics Using Power Hardware-In-The-Loop, Nischal Guruwacharya

Electronic Theses and Dissertations

The main objective of this dissertation is to develop a generalized simulation and modeling framework for extracting dynamics of power electronic converters (PECs) with grid support functions (GSFs) and validate model accuracy through experimental comparison with physical measurements. The dynamic models obtained from this modeling framework aim to facilitate accurate dynamic analysis of a highly integrated power system comprising inverter-based resources (IBRs), specifically for stability assessment. These dynamic models helped in reducing simulation time and computational complexity, thereby enhancing efficiency. Moreover, it provides valuable insights for utilities and grid operators involved in effective system planning, operation, and dispatch. The dynamics …

Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan

Publications

In this article, we address two key challenges in deep reinforcement learning (DRL) setting, sample inefficiency, and slow learning, with a dual-neural network (NN)-driven learning approach. In the proposed approach, we use two deep NNs with independent initialization to robustly approximate the action-value function in the presence of image inputs. In particular, we develop a temporal difference (TD) error-driven learning (EDL) approach, where we introduce a set of linear transformations of the TD error to directly update the parameters of each layer in the deep NN. We demonstrate theoretically that the cost minimized by the EDL regime is an approximation …

Moment-Based Reinforcement Learning For Ensemble Control, Yao-Chi Yu, Vignesh Narayanan, Jr-Shin Li

Publications

Problems involving controlling the collective behavior of a population of structurally similar dynamical systems, the so-called ensemble control, arise in diverse emerging applications and pose a grand challenge in systems science and control engineering. Owing to the severely under-actuated nature and the difficulty of placing large-scale sensor networks, ensemble systems are limited to being actuated and monitored at the population level. Moreover, mathematical models describing the dynamics of ensemble systems are often elusive. Therefore, it is essential to design broadcast controls that excite the entire population in such a way that the heterogeneity in system dynamics are robustly compensated. In …

Energy-Efficient Multi-Rate Opportunistic Routing In Wireless Mesh Networks, Mohammad Ali Mansouri Khah, Neda Moghim, Nasrin Gholami, Sachin Shetty

VMASC Publications

Opportunistic or anypath routing protocols are focused on improving the performance of traditional routing in wireless mesh networks. They do so by leveraging the broadcast nature of the wireless medium and the spatial diversity of the network. Using a set of neighboring nodes, instead of a single specific node, as the next hop forwarder is a crucial aspect of opportunistic routing protocols, and the selection of the forwarder set plays a vital role in their performance. However, most opportunistic routing protocols consider a single transmission rate and power for the nodes, which limits their potential. To address this limitation, this …

Data-Integrity Aware Stochastic Model For Cascading Failures In Power Grids, Rezoan Ahmed Shuvro, Pankaz Das, Jamir Shariar Jyoti, Joana M. Abreu, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

The reliable operation of power grids during cascading failures is heavily dependent on the interdependencies between the power grid components and the supporting communications and control networks. Moreover, the system operators' expertise in dealing with cascading failures can play a pivotal role during contingencies. In this paper, a dynamical probabilistic model is developed based on Markov-chains, which captures the dynamics of cascading failures in the power grid. Specifically, a previously developed Markov-chain based model is extended to capture the trade-off between the benefits of having a robust communication infrastructure and its vulnerability from data integrity (e.g., cyber-attacks). State-space reduction of …

Optimizing Constraint Selection In A Design Verification Environment For Efficient Coverage Closure, Vanessa Cooper

CCAC Theses and Dissertations

No abstract provided.

Commentary On Healthcare And Disruptive Innovation, Hilary Finch, Affia Abasi-Amefon, Woosub Jung, Lucas Potter, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Exploits of technology have been an issue in healthcare for many years. Many hospital systems have a problem with “disruptive innovation” when introducing new technology. Disruptive innovation is “an innovation that creates a new market by applying a different set of values, which ultimately overtakes an existing market” (Sensmeier, 2012). Modern healthcare systems are historically slow to accept new technological advancements. This may be because patient-based, provider-based, or industry-wide decisions are tough to implement, giving way to dire consequences. One potential consequence is that healthcare providers may not be able to provide the best possible care to patients. For example, …

Embedded Ai For Wheat Yellow Rust Infection Type Classification, Uferah Shafi, Rafia Mumtaz, Muhammad Deedahwar Mazhar Qureshi, Zahid Mahmood, Sikander Khan Tanveer, Ihsan Ul Haq, Syed Mohammad Hassan Zaidi

Articles

Wheat is the most important and dominating crop in Pakistan in terms of production and acreage, which is grown on 37% of the cultivated area, accounting for 70% of the total production. However, wheat yield is highly affected by stripe rust, which is considered the most devastating fungal disease, causing 5.5 million tonnes of loss per year globally. In order to minimize this loss, the accurate and timely detection of rust disease is crucial instead of manual inspection. Towards this end, we propose a system to detect wheat rust disease and classify its infection types into four classes, including healthy, …

Adaptive Fuzzy Supplementary Controller For Ssr Damping In A Series-Compensated Dfig-Based Wind Farm, Mohamed Abdeen, Sayed Hosny Ahmed El-Banna, Sara Elgohary, Hend Mostafa, Nora Ghaly, Nourhan Adel, Zeinab Elkhwas, Mohamed Alahmady, Hossam Zawbaa, Salah Kamel

Articles

Although using a series compensation technique in a long transmission line effectively increases the transmittable power; it may cause a sub-synchronous resonance (SSR) phenomenon. Gate-controlled series capacitor (GCSC) is an effective method for SSR damping by controlling the turn-off angle. In the previous studies, a constant supplementary damping controller (SDC) was used for controlling the turn-off angle, which can mitigate the SSR phenomenon. However, these methods can not capture the maximum transmittable power at different operating points. In this paper, a fuzzy logic controller (FLC) is proposed to compute the gain of SDC based on the wind speed and the …

Design And Implementation Of A New Adaptive Mppt Controller For Solar Pv Systems, Saibal Manna, Deepak Kumar Singh, Ashok Kumar Akella, Hossam Kotb, Kareem M. Aboras, Hossam Zawbaa, Salah Kamel

Articles

This research provides an adaptive control design in a photovoltaic system (PV) for maximum power point tracking (MPPT). In the PV system, MPPT strategies are used to deliver the maximum available power to the load under solar radiation and atmospheric temperature changes. This article presents a new adaptive control framework to enhance the performance of MPPT, which will minimize the complexity in system control and efficiently manage uncertainties and disruptions in the environment and PV system. Here, the MPPT algorithm is decoupled with model reference adaptive control (MRAC) techniques, and the system gains MPPT with overall system stability. The simulation …

Distributed Intermittent Fault Diagnosis In Wireless Sensor Network Using Likelihood Ratio Test, Bhabani Sankar Gouda, Meenakshi Panda, Trilochan Panigrahi, Sudhakar Das, Bhargav Appasani, Omprakash Acharya, Hossam Zawbaa, Salah Kamel

Articles

In current days, sensor nodes are deployed in hostile environments for various military and commercial applications. Sensor nodes are becoming faulty and having adverse effects in the network if they are not diagnosed and inform the fault status to other nodes. Fault diagnosis is difficult when the nodes behave faulty some times and provide good data at other times. The intermittent disturbances may be random or kind of spikes either in regular or irregular intervals. In literature, the fault diagnosis algorithms are based on statistical methods using repeated testing or machine learning. To avoid more complex and time consuming repeated …

Intelligent Beam Steering For Wireless Communication Using Programmable Metasurfaces, Nouman Ashraf, Taqwa Saeed, Hamidreza Taghvaee, Sergi Abadal, Vasos Vasos, Christos Liaskos Christos Liaskos, Andreas Pitsillides, Marios Lestas Marios Lestas

Articles

Future generations of wireless communications are envisioned to provide several Gbps data rates per user for billions of users simultaneously [1]. The proliferation of billions of Internet of Things (IoT) devices in various industries has pushed wireless networks to their limits in terms of the required capacity to effectively communicate the vast amounts of data that are generated [2]. Moreover, the increasing number of IoT devices is changing mobile communication services from interpersonal communication to smart interconnection among billions of devices. 6G is expected to fulfill the requirements of a fully connected world and provide ubiquitous wireless connectivity for all …

Metaheuristic Optimization Techniques Used In Controlling Of An Active Magnetic Bearing System For High-Speed Machining Application, Suraj Suraj, Pabitra Kumar Biswas Pabitra Kumar Biswas, Sukanta Debnath, Anumoy Ghosh, Thanikanti Sudhakar Babu, Hossam Zawbaa, Salah Kemal

Articles

Smart control tactics, wider stability region, rapid reaction time, and high-speed performance are essential requirements for any controller to provide a smooth, vibrationless, and efficient performance of an in-house fabricated active magnetic bearing (AMB) system. In this manuscript, three pre-eminent population-based metaheuristic optimization techniques: Genetic algorithm (GA), Particle swarm optimization (PSO), and Cuckoo search algorithm (CSA) are implemented one by one, to calculate optimized gain parameters of PID controller for the proposed closed-loop active magnetic bearing (AMB) system. Performance indices or, objective functions on which these optimization techniques are executed are integral absolute error (IAE), integral square error (ISE), integral …

Performance Improvement Of Hybrid System Based Dfig-Wind/Pv/Batteries Connected To Dc And Ac Grid By Applying Intelligent Control, Younes Sahri, Salah Tamalouzt, Sofia Lalouni Belaid, Mohit Bajaj, Sherif S.M. Ghoneim, Hossam Zawbaa, Salah Kamel

Articles

One of the main causes of CO2 emissions is the production of electrical energy. Therefore, many researchers goal’s is to develop renewable power systems. This paper proposes a new intelligent control development of hybrid PV–Wind-Batteries. Neuro-Fuzzy Direct Power Control (NF-DPC) is invested in order to enhance system performance and generated currents quality. An improved MPPT algorithm based on Fuzzy Controller (FC) is invested for PV power optimization. In addition, a new Modified Fuzzy Direct Power Control (MF-DPC) is developed and applied to the grid side converter to control the active and reactive power by monitoring the involved active power flow …

Analysis And Design Of Secure Sampled-Data Control Subject To Denial-Of-Service Attacks, Hira Sana, Ghulam Mustafa, Owais Khan, Nouman Ashraf, Abdul Qayyum Khan, Muhammad Abid, Haroom Ur Rashid Khan

Articles

This study addresses the issue of secure control design for cyber-physical systems (CPS) against denial of service (DoS) attacks. We take into account a continuous-time linear system with a convex quadratic performance measure and a sampled linear state feedback control. DoS attacks impose constraints on the CPS, where packets may be jammed between the sensor and controller by a malicious entity, potentially resulting in system instability and performance degradation. We assume that the attacker can perform DoS attacks with a limited time and frequency due to energy restrictions. We devise an efficient procedure using the linear matrix inequality approach to …

Nipuna: A Novel Optimizer Activation Function For Deep Neural Networks, Golla Madhu, Sandeep Kautish, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

In recent years, various deep neural networks with different learning paradigms have been widely employed in various applications, including medical diagnosis, image analysis, self-driving vehicles and others. The activation functions employed in deep neural networks have a huge impact on the training model and the reliability of the model. The Rectified Linear Unit (ReLU) has recently emerged as the most popular and extensively utilized activation function. ReLU has some flaws, such as the fact that it is only active when the units are positive during back-propagation and zero otherwise. This causes neurons to die (dying ReLU) and a shift in …

Wind Energy Harvesting And Conversion Systems: A Technical Review, Sinhara M. H. D. Perera, Ghanim Putrus, Michael Conlon, Mahinsasa Narayana, Keith Sunderland

Articles

Wind energy harvesting for electricity generation has a significant role in overcoming the challenges involved with climate change and the energy resource implications involved with population growth and political unrest. Indeed, there has been significant growth in wind energy capacity worldwide with turbine capacity growing significantly over the last two decades. This confidence is echoed in the wind power market and global wind energy statistics. However, wind energy capture and utilisation has always been challenging. Appreciation of the wind as a resource makes for difficulties in modelling and the sensitivities of how the wind resource maps to energy production results …