Engineering Commons^™

Statistical Analysis Of Electromagnetic Coupling To Printed Circuit Boards, Shengxuan Xia, Victor Khilkevich, Daryl Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Determining electromagnetic (EM) coupling to printed circuit boards (PCBs) is essential to finding potential EM susceptibilities early in the design process. For realistic PCB structures, analysis usually relies heavily on time-consuming full-wave simulations because of the complexity of the geometries and the lack of analytical solutions. In this paper, we adopt a segmentation approach based on far-field reciprocity which allows for rapid estimation of the voltage induced at trace terminations over frequency, and which is then used to estimate statistical characteristic of coupling across trace geometries. Frequency-domain results can then be used to estimate time-domain responses with appropriate transformations. Super-position …

On The Feasibility Of A Direct Injection Probe With A Capacitively Coupled Return And Integrated Voltage Monitor, Aaron Harmon, Daniel Szanto, Victor Khilkevich, Daryl Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Characterizing the susceptibility of an IC while it is integrated within a system can be challenging. Characterization is even harder if one wants to know the waveform at the target IC pin when injecting a signal on the pin. In this work, the feasibility of a direct injection probe with a capacitively coupled return and integrated voltage monitor is proposed. This probe is advantageous because it does not need to be soldered to the test device and its ability to provide a measurement of the waveform on the target IC pin during the injection. Methods for reconstructing the pin waveform …

Adaptive Critic Optimal Control Of An Uncertain Robot Manipulator With Applications, Ravi Prakash, Laxmidhar Behera, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Realistic manipulation tasks involve a prolonged sequence of motor skills in varying control environments consisting of uncertain robot dynamic models and end-effector payloads. To address these challenges, this article proposes an adaptive critic (AC)-based basis function neural network (BFNN) optimal controller. Using a single neural network (NN) with a basis function, the proposed optimal controller simultaneously learns task-related optimal cost function, robot internal dynamics, and optimal control law. This is achieved through the development of a novel BFNN tuning law using closed-loop system stability. Therefore, the proposed optimal controller provides real-time, implementable, cost-effective control solutions for practical robotic tasks. The …

Evaluation Of Transfer Learning Models On Traumatic Brain Injury Severity Classification, Ngoc Do, Daniel B. Hier, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

After traumatic brain injury (TBI), clinicians use the Glasgow Coma Scale (GCS) to classify patients by severity and radiologists use the Rotterdam score and the Marshall score to classify CT scans by severity. This work investigates a viable efficient low-cost transfer learning model to use MRI images to predict GCS, Rotterdam, and Marshall severity class after TBI. The enhanced transfer learning model architecture integrates multiple fine-tuning steps in which a few layers of the pre-trained model is unfrozen in each iteration so that the neural network is able to learn layer by layer further aspects of the image for better …

A Model For Corona Streamer Propagation On Glass During An Air Discharge, Zhekun Peng, Jianchi Zhou, Darryl Kostka, David Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Corona discharge to a glass surface is challenging to model due to a poorly understood air and surface ionization process. A modeling methodology based on the transmission line modeling (TLM) approach is proposed to simulate the streamer propagation process. The time-changing corona streamer resistance is estimated using the Rompe and Weizel spark model. The streamer is represented using small segments consisting of the arc resistance, per unit length (PUL) capacitance of the streamer, PUL inductance, a switch representing streamer formation, and a surface discharge gap voltage representing the voltage drop caused by ions within the streamer length. The propagation of …

Mechanisms For Unwanted Magnetic Field Coupling To A Shielded Magnetic Near-Field Probe, Xin Yan, Wei Zhang, Sajjad Sadeghi, Mehdi Gholizadeh, David J. Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Unwanted field coupling is a major concern when using magnetic near-field probes for high-frequency scanning. The unwanted coupling of the tangential electric field to a tangential magnetic field probe has been studied extensively. This article shows a second unwanted coupling mechanism: coupling from a vertical magnetic field. The standing wave of a shorted pure TEM microstrip in air is utilized to separate the magnetic and electric field coupling. Simulations show that the eddy currents induced within the probe by the vertical magnetic field couple inductively to the pickup loop if the layer stack up is not symmetric. The unwanted magnetic …

Low Noise Wireless Sensing In Termite Detection, Wei Zhang, Xiangshu Qi, Yunlong Luo, Alex Qi, Yihong Qi, Gang Feng

Electrical and Computer Engineering Faculty Research & Creative Works

Termites cause enormous financial damages all around the world every year. The majority of research on wireless sensing is always concerned with the various human-centric applications, however, the vast potential of wireless sensing for termite detection is often disregarded. In this article, a Wireless Intelligent Sensing (WISe) millimeter-wave (mmWave) radar system for termite detection is proposed. Here, we design a three-layer architecture with some intelligent resources to monitor the movement signs of the termites. In addition, we present a low noise sensing architecture that minimizes the noise in hardware and digital signal processing, which can reduce the impact of environment …

A Method For Measuring The Transfer Function Inside A Compact Metallic Enclosure Using A Slot Antenna, Xiangrui Su, Wenchang Huang, Junghee Cho, Joonki Paek, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Radio frequency desensitization issues comprise two components: noise radiation sources and the transfer function from noise sources to the victim antenna. For modern electronic products, noise sources are often located inside a compact metal enclosure, making it difficult to measure the transfer function using conventional methods. Moreover, opening the metallic enclosure would dramatically change the transfer function, and inserting a near-field probe into the enclosure is challenging and may not even be possible because of the limited space inside. In this article, a novel practical method for measuring the transfer function inside a compact metallic enclosure is proposed and experimentally …

Virtual Inertia Scheduling (Vis) For Microgrids With Static And Dynamic Security Constraints, Buxin She, Fangxing Li, Jinning Wang, Hantao Cui, Xiaofei Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Microgrids feature a high penetration of inverter-interfaced distributed energy resources (DERs). The low inertia characteristic and fast dynamics of DERs pose challenges to conventional decoupled static economic operation and dynamic control design within microgrids. Hence, this paper proposed virtual inertia scheduling (VIS) for microgrids, aiming to ensure both economy and security. First, a unified framework for device-level control and grid-level operation is introduced, with VIS serving as a key application to address low inertia issues. VIS actively harnesses the controllability and flexibility of DERs to effectively manage microgrid inertia. It updates the conventional economic operation framework by incorporating the virtual …

Influence Of Variations In Imbalanced Lisn Termination Impedances On Radiated Emissions, Hossein Rezaei, Morten Sørensen, Kim Jensen, David Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Radiated emissions measurements are often performed using a line impedance stabilization network (LISN) with a balanced termination, but in the real-world the common-mode characteristic of the termination may be highly variable. An asymmetric LISN allows testing under more realistic asymmetric termination conditions. The common-mode termination impedance of these LISNs must fall within set tolerances, but the impact of these tolerances is unknown. An analysis of the radiated emissions from a device under test (DUT) for a wide variety of power cable termination impedances is performed in the following paper to estimate the impact of allowed variations in imbalanced LISN termination …

Dk And Df Characterization Of Low-Loss Dielectric Liquid By Cylindrical Cavity Resonator, Chaofeng Li, Seyedmehdi Mousavi, Reza Asadi, Seyedmostafa Mousavi, Reza Vahdani, Xiaoning Ye, Kai Wang, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

A novel cylindrical cavity resonator-based measurement method was developed to characterize the dielectric property of the low-loss dielectric liquid in the paper. The proposed method can be used to accurately measure the dielectric constant (Dk) and the loss tangent (Df) of the low-loss coolant for signal integrity analysis. The cylindrical cavity resonator works at tangential magnetic (TM010) mode is used in the paper to demonstrate the proposed method. A cylindrical cavity resonator apparatus was designed and investigated using full-wave simulations at first. The relative error of Dk and Df extractions based on the designed apparatus are less than 1% and …

Relative Altitude Estimation Of Infrared Thermal Uav Images Using Sift Features, Shirin Nasr Esfahani, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs) have become indispensable in various applications, including surveillance, urban scene analysis, and agricultural monitoring. Accurate altitude estimation is critical for UAV operations, especially in environments where traditional sensors like GPS, pressure altimeters, and radar may fail. This paper explores the use of infrared and thermal imaging for relative altitude estimation of UAVs, highlighting their significant advantages over traditional RGB images. Infrared and thermal imaging offer superior performance in low-light and adverse weather conditions, providing clearer visibility and more reliable feature detection. By leveraging the Scale-Invariant Feature Transform (SIFT) features, this approach utilizes the inherent benefits of …

Lifelong Direct Error-Driven Learning For Uav Altitude Estimation In Different Weather Conditions, Shirin Nasr-Esfahani, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

While deep neural networks achieve remarkable visual perception capabilities for UAV position and orientation estimation, their resilience to different weather conditions still needs improvement. These models often suffer from catastrophic forgetting when adapted to new environments, losing previously acquired knowledge. Lifelong learning methods aim to balance learning flexibility and memory stability. In this paper, we present an image-based approach to estimate the relative altitude of a UAV using 2D images under varying weather conditions, including sunny, sunset, and foggy scenarios. Our experiments demonstrate significant performance degradation when the model is trained sequentially on different weather datasets, especially when new images …

Cascading Of 2d And 3d Simulations Of Asic Substrate Interconnect Up To 100 Ghz, Zhekun Peng, Junyong Park, Sathvika Bandi, Santosh Pappu, Srinivas Venkataraman, Xu Wang, Granthana Ranzaswamy, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

A method of cascading 3D models and 2D models to model the full channel of ASIC package substrate interconnects is proposed, showing good match to full-wave results in S-parameter and TDR up to 100 GHz.

Rapid Control Prototyping Platform For Grid Connected Electrical Energy Conversion Systems, Shruti Pandey, Noah Damron, Michael Mcintyre

Electrical and Computer Engineering Faculty Research & Creative Works

Electrical Energy Conversion Systems (EECSs) are extensively utilized in contemporary stand-alone systems to supply power to isolated loads. They are also integrated into distributed generation systems, micro grids, and smart grids. In each of these contexts, it is essential to conduct efficient energy management procedures to optimize the electrical energy systems output and ensure the effective and high-quality delivery of electric energy to consumers. To create the energy management system for such a system, careful consideration must be given to the configuration of the power conversion and conditioning system, as well as the specific hardware devices that make up this …

Cross-Temporal Hierarchical Forecast Reconciliation Of Natural Gas Demand, Colin O. Quinn, George F. Corliss, Richard J. Povinelli

Electrical and Computer Engineering Faculty Research and Publications

Local natural gas distribution companies (LDCs) require accurate demand forecasts across various time periods, geographic regions, and customer class hierarchies. Achieving coherent forecasts across these hierarchies is challenging but crucial for optimal decision making, resource allocation, and operational efficiency. This work introduces a method that structures the gas distribution system into cross-temporal hierarchies to produce accurate and coherent forecasts. We apply our method to a case study involving three operational regions, forecasting at different geographical levels and analyzing both hourly and daily frequencies. Trained on five years of data and tested on one year, our model achieves a 10% reduction …

Tunable Metasurface For Efficient Harmonic Generation And Amplitude Modulation, Steve Mares

Masters Theses

The manipulation of microwave signals is critical in the information and communication technology industry. This research investigates the application of time-coding techniques on metasurfaces to achieve tunable control of electromagnetic signal transmission. The integration of mounted PIN diodes facilitates dynamic modulation of signal behavior. Both passive (without PIN diodes) and active (with PIN diodes) metasurfaces were analyzed through simulations using Ansys HFSS and validated with experimental measurements. A major contribution of this work is the design and testing of active metasurfaces that leverage PIN diodes for harmonic generation and amplitude modulation. The study reveals a clear relationship between modulating signal …

Particle Accelerator Spin-Transparent Storage Rings For Beyond State-Of-The-Art Science, R. Suleiman, Y. Derbenev, M. Grau, V. Morozov

Physics Faculty Publications

We will describe spin-transparent storage rings that exhibit spin-coherence times of several hours and store a large number of particles and their use in novel applications. For example, these rings can be used to directly measure the electric dipole moment of the electron, relevant to CP violation and matter-antimatter asymmetry in the universe, and to search for dark energy and ultra-light dark matter*. These rings can also serve as a compelling platform for quantum computing. In this presentation, we will describe how spin-transparent rings can be used in conjunction with ion traps to enhance scalability and increase quantum coherence times …

Integrating Generative Artificial Intelligence With Systems Architecting Diagram Creation: Advancement, Challenges, Opportunities And Future Perspectives, Cansu Yalim, Holly H. Handley

Engineering Management & Systems Engineering Faculty Publications

Generative AI (GenAI) serves as a powerful tool that can create a wide range of content, including but not limited to text, speech, images, code, videos, and 3D models. ChatGPT stands out as a particularly appealing Generative Pretrained Transformer (GPT) model that offers supplementary capabilities through GPTs and plugins. These extensions enable users to engage with the chatbot and improve its functionality, surpassing mere content generation. Our study delves into the potential of ChatGPT, specifically GPT-4, to expedite the creation of diagrams to support the system architecting process. To this end, we explored the use of ChatGPT's Diagrams Show Me …

Gas Assisted Electron Beam Patterning Processes, Deepak Kumar

Theses and Dissertations--Electrical and Computer Engineering

Radiolysis is a complex phenomenon in which molecules subjected to ionizing radiation form new chemical species. Electron-beam irradiation has proven to be a versatile approach for significantly altering materials’ properties and forms the basis for electron-beam lithography using both organic and inorganic resists. Electron-beam exposure is normally carried out under high vacuum conditions to reduce contamination and allow for unhindered interaction between the electrons and the resist material. Exposure under an ambient gas at sub-atmospheric pressures has been found to provide a distinct mechanism which can be exploited to circumvent some of the challenges associated with material processing and significantly …

Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, Venkata Sai Praneeth Karempudi

Theses and Dissertations--Electrical and Computer Engineering

The long-standing technological pillars for computing systems evolution, namely Moore's law and Von Neumann architecture, are breaking down under the pressure of meeting the capacity and energy efficiency demands of computing and communication architectures that are designed to process modern data-centric applications related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In response, both industry and academia have turned to 'more-than-Moore' technologies for realizing hardware architectures for communication and computing. Fortunately, Silicon Photonics (SiPh) has emerged as one highly promising ‘more-than-Moore’ technology. Recent progress has enabled SiPh-based interconnects to outperform traditional electrical interconnects, offering advantages like high bandwidth density, …

Design And Control Of Axial Flux Permanent Magnet Coreless Machines With Special Windings, Yaser Chulaee

Theses and Dissertations--Electrical and Computer Engineering

Permanent magnet synchronous machines (PMSMs), particularly those of the axial flux type, are being researched and developed for various applications such as HVAC systems, aviation propulsion, and electric vehicles. The coreless (air-cored) stator axial flux permanent magnet (AFPM) machine topology offers notable advantages over conventional designs by eliminating magnetic cores and their associated losses. These advantages include potentially higher efficiency, zero cogging torque, and reduced audible noise and vibration. Eliminating the magnetic core also allows for more effective cooling systems, as coolants can be in direct contact with the stator windings, potentially improving power density and specific torque.

The absence …

Ultra‐Fast Finite Element Analysis Of Coreless Axial Flux Permanent Magnet Synchronous Machines, Yaser Chulaee, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Large‐scale design optimisation techniques enable the design of high‐performance electric machines. Electromagnetic 3D finite element analysis (FEA) is typically employed in optimisation studies for accurate analysis of axial flux permanent magnet (AFPM) machines, which require extensive computational resources. To reduce the computational burden, a FEA‐based mathematical method relying on the geometric and magnetic symmetry of coreless AFPM machines is proposed to estimate the machine performance indicators using the least number of FEA solutions, thereby significantly lowering the running time. This method is generally applicable to AFPM machines with low saturation effects and cogging torque as exemplified for a printed circuit …

Design And Optimization Of High-Efficiency Coreless Pcb Stator Axial Flux Pm Machines With Minimal Eddy And Circulating Current Losses, Yaser Chulaee, Greg Heins, Ali Mohammadi, Mark Thiele, Dan M. Ionel, Ben Robinson

Electrical and Computer Engineering Graduate Research

This paper proposes a systematic multi-step design procedure for highly efficient printed circuit board (PCB) stator coreless axial flux permanent magnet (AFPM) machines with minimal eddy and circulating current losses. The process begins with initial sizing, providing specific coefficients based on experience with multiple design projects. It continues with the optimization of the machine envelope design using an evolutionary algorithm and computationally efficient 3D finite element analysis (FEA) models. The subsequent step focuses on the detailed design of a PCB stator, aiming to minimize eddy and circulating current losses. Several open circuit loss mitigation techniques are proposed based on analytical …

Design Optimization Of A Direct-Drive Wind Generator With A Reluctance Rotor And A Flux Intensifying Stator Using Different Pm Types, Ali Mohammadi, Oluwaseun A. Badewa, Yaser Chulaee, Donovin D. Lewis, Somasundaram Essakiappan, Madhav Manjrekar

Electrical and Computer Engineering Graduate Research

This paper presents a large-scale multi-objective design optimization for a direct-drive wind turbine generator concept that is based upon an experimentally validated computational model for a small-scale prototype motor of the same type. By integrating an outer reluctance-type rotor and a segmented stator with toroidally wound single-coil modules containing spoke-type PMs, the design optimization aims to minimize losses, active mass, and torque ripple while adhering to a power factor constraint. The AC windings and PMs are positioned in the stator and this concept enhances flux concentration, enabling the use of more affordable high energy non-rare-earth (special type) magnets. The exterior …

Large-Scale Design Optimization Of An Axial-Flux Vernier Machine With Dual Stator And Spoke Pm Rotor For Ev In-Wheel Traction, Ali Mohammadi, Yaser Chulaee, Aaron M. Cramer, Ion G. Boldea, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper presents the optimization study targeting a specific drive cycle for a MAGNUS-type axial-flux permanent magnet vernier machine (AFPMVM). The proposed MAGNUS machine has a novel design with a dual-stator configuration, where only one stator is wound, with a high-polarity spoke permanent magnet (PM) rotor. The machine topology has a 3D flux path, which necessitates the analysis of a large finite element (FE) model. However, due to the computational complexity and time required for such a large FE model, a new approach was developed. This approach involves a computationally efficient finite element analysis (CE-FEA) model combined with a single …

Economical And Environmental Evaluation Of Non-Residential Demand Response In The European Transition To Zero-Carbon Energy, Markus Fleshutz

Theses

To meet climate objectives, major energy consumers with local multi-energy systems (L- MESs) must transition to renewable energy sources soon. The variability of renewable energies requires increased operational flexibility for integration. In this context, demand response (DR), a strategy in which electricity consumers adjust their load profiles in response to incentives, has become crucial, offering cost-effective flexibility. It supports L-MESs in integrating renewable energy, reducing decarbonization costs, and enhancing resilience. However, quantifying the economic DR potentials for L-MESs under carbon emission constraints is complex, especially when considering investment options in distributed energy resources. This complexity hinders the rapid adoption of …

Detection Of Tooth Position By Yolov4 And Various Dental Problems Based On Cnn With Bitewing Radiograph, Kuo Chen Li, Yi-Cheng Mao, Mu-Feng Lin, Yi-Qian Li, Chiung-An Chen, Tsung-Yi Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Periodontitis is a high prevalence dental disease caused by bacterial infection of the bone that surrounds the tooth. Early detection and precision treatment can prevent more severe symptoms such as tooth loss. Traditionally, periodontal disease is identified and labeled manually by dental professionals. The task requires expertise and extensive experience, and it is highly repetitive and time-consuming. The aim of this study is to explore the application of AI in the field of dental medicine. With the inherent learning capabilities, AI exhibits remarkable proficiency in processing extensive datasets and effectively managing repetitive tasks. This is particularly advantageous in professions demanding …

Photoluminescence Switching In Quantum Dots Connected With Carboxylic Acid And Thiocarboxylic Acid End-Group Diarylethene Molecules, Ephraiem S. Sarabamoun, Pramod Aryal, Jonathan M. Bietsch, Maurice Curran, Sugandha Verma, Grayson Johnson, Lucy U. Yoon, Amelia G. Reid, Esther H. R. Tsai, Charles W. Machan, Christopher Paolucci, Guijun Wang, Joshua J. Choi

Chemistry & Biochemistry Faculty Publications

We contrast the switching of photoluminescence (PL) of PbS quantum dots (QDs) cross-linked with photochromic diarylethene molecules with different end groups, 4,4′-(1-cyclopentene-1,2-diyl)bis[5-methyl-2-thiophenecarboxylic acid] (1C) and 4,4′-(1-cyclopentene-1,2-diyl)bis[5-methyl-2-thiophenethiocarboxylic acid] (2T). Our results show that the QDs cross-linked with the carboxylic acid end group molecules (1C) exhibit a greater amount of switching in photoluminescence intensity compared to QDs cross-linked with the thiocarboxylic acid end group (2T). We also demonstrate that regardless of the molecule used, greater switching amounts are observed for smaller quantum dots. Varying these parameters allows for the fabrication of photoswitches with tunable PL change. We relate these observations to the …

Automated Flood Depth Estimation On Roadways, Kwame Ampofo, Megan A. Witherow, Alex Glandon, Monibor Rahman, Ahmed Temtam, Mecit Cetin, Khan M. Iftekharuddin

Civil & Environmental Engineering Faculty Publications

Recurrent nuisance flooding is common across many parts of the globe and causes extensive challenges for drivers on the roadways. The prevailing monitoring methods for roadway flooding are costly and not automated or effective. The ubiquity of visual data from cameras and advancements in computing such as deep learning may offer cost-effective methods for automated flood depth estimation on roadways based on reference objects such as cars. However, flood depth estimation faces challenges due to the limited amount of data annotated with water levels and diverse scenes showing reference objects at various scales and perspectives. This study proposes a novel …