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Electrical and Computer Engineering Faculty Research & Creative Works

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Full-Text Articles in Engineering

From Fiber Bragg Gratings To Coaxial Cable Bragg Gratings: One-Dimensional Microwave Quasi-Periodic Photonic Crystals, Chen Zhu, Osamah Alsalman, Jie Huang Apr 2023

From Fiber Bragg Gratings To Coaxial Cable Bragg Gratings: One-Dimensional Microwave Quasi-Periodic Photonic Crystals, Chen Zhu, Osamah Alsalman, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Coaxial cables and optical fibers are two types of cylindrical waveguides used in telecommunications. Fiber Bragg gratings (FBGs) have found successful applications in various fields, such as optical communications, fiber lasers, and fiber-optic sensing. In this paper, we propose and numerically investigate the implementations of various fiber Bragg configurations, including uniform, chirped, apodized, and phase-shifted configurations, on coaxial cables to generate the corresponding special types of coaxial cable Bragg gratings (CCBGs). The simulation results of different CCBGs match well with the well-known FBG theories. It is demonstrated that the reflection spectrum of a CCBG can be flexibly tailored by introducing …

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Fast Full-Wave Electromagnetic Forward Solver Based On Deep Conditional Convolutional Autoencoders, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng Apr 2023

Fast Full-Wave Electromagnetic Forward Solver Based On Deep Conditional Convolutional Autoencoders, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

This letter proposes a novel deep learning (DL) based fast solver for the electromagnetic forward (EMF) process. This proposed fast full-wave solver for EMF process is designed based on the deep conditional convolutional autoencoder (DCCAE), consisting of a complex-valued deep convolutional encoder network and its corresponding complex-valued deep convolutional decoder network. The encoder network makes use of the input consisting of the incident electromagnetic (EM) wave and the contrast (permittivities) distribution of the target domain, while the corresponding decoder network predicts the total EM field illuminated by the input incident EM wave. The training of the proposed DCCAE solver for …

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A Wave Equation-Based Hybridizable Discontinuous Galerkin-Robin Transmission Condition Algorithm For Electromagnetic Problems Analyzing, Xuan Zhang, Shi Min Liu, Ran Zhao, Xiao Chun Li, Jun Fa Mao, Li (Lijun) Jun Jiang, Ping Li Apr 2023

A Wave Equation-Based Hybridizable Discontinuous Galerkin-Robin Transmission Condition Algorithm For Electromagnetic Problems Analyzing, Xuan Zhang, Shi Min Liu, Ran Zhao, Xiao Chun Li, Jun Fa Mao, Li (Lijun) Jun Jiang, Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

In this work, a wave-equation-based discontinuous Galerkin (DG) method hybridized with the Robin transmission condition (DG-RTC) is developed to solve the frequency-domain electromagnetic (EM) problems. The proposed DG method directly discretizes the vector electric field wave equation in each subdomain, and subsequently, a term named numerical flux is introduced at the subdomain interfaces to connect the solutions between neighboring subdomains. However, the numerical flux depends not only on the electric field E but also on the magnetic field H residing over the interface. Thereby, another equation is essential for solving E and H simultaneously. Realizing that H only situates at …

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Nitrogen-Doped 4h Silicon Carbide Single-Crystal Electrode For Selective Electrochemical Sensing Of Dopamine, Fatemeh Fathi, Brandon Sueoka, Feng Zhao, Xiangqun Zeng Mar 2023

Nitrogen-Doped 4h Silicon Carbide Single-Crystal Electrode For Selective Electrochemical Sensing Of Dopamine, Fatemeh Fathi, Brandon Sueoka, Feng Zhao, Xiangqun Zeng

Electrical and Computer Engineering Faculty Research & Creative Works

In this work, we designed, fabricated, and characterized the first nitrogen (N)-doped single-crystalline 4H silicon carbide (4H-SiC) electrode for sensing the neurotransmitter dopamine. This N-doped 4H-SiC electrode showed good selectivity for redox reactions of dopamine in comparison with uric acid (UA), ascorbic acid (AA), and common cationic ([Ru(NH3)6]3+), anionic ([Fe(CN)6]3-), and organic (methylene blue) redox molecules. The mechanisms of this unique selectivity are rationalized by the unique negative Si valency and adsorption properties of the analytes on the N-doped 4H-SiC surface. Quantitative electrochemical detection of dopamine by the 4H-SiC electrode …

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Suppressing White-Noise Interference For Orbital Angular Momentum Waves Via The Forward-Backward Dynamic Mode Decomposition, Yanming Zhang, Lijun Jiang Mar 2023

Suppressing White-Noise Interference For Orbital Angular Momentum Waves Via The Forward-Backward Dynamic Mode Decomposition, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

When the orbital angular momentum (OAM)-carrying beam propagates in a highly boisterous environment, it causes the degradation of the OAM modes' purity, which brings the crosstalk in the demultiplexing process. To address this issue, we extend the dynamic mode decomposition (DMD) method to suppress white-noise interferences of OAM by using the forward-backward DMD (FBDMD) approach. The FBDMD-based scheme retrieves the noise-free DMD mapping matrix corresponding to the actual OAM's topological charges by combining the forward and backward DMD mapping matrix in the noisy environment and consequently reduces the crosstalk, particularly for sorting the superposed OAM modes. Numerical examples are provided …

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Deep Learning To Predict The Hydration And Performance Of Fly Ash-Containing Cementitious Binders, Taihao Han, Rohan Bhat, Sai Akshay Ponduru, Amit Sarkar, Jie Huang, Gaurav Sant, Hongyan Ma, Narayanan Neithalath, Aditya Kumar Mar 2023

Deep Learning To Predict The Hydration And Performance Of Fly Ash-Containing Cementitious Binders, Taihao Han, Rohan Bhat, Sai Akshay Ponduru, Amit Sarkar, Jie Huang, Gaurav Sant, Hongyan Ma, Narayanan Neithalath, Aditya Kumar

Electrical and Computer Engineering Faculty Research & Creative Works

Fly ash (FA) – an industrial byproduct – is used to partially substitute Portland cement (PC) in concrete to mitigate concrete's environmental impact. Chemical composition and structure of FAs significantly impact hydration kinetics and compressive strength of concrete. Due to the substantial diversity in these physicochemical attributes of FAs, it has been challenging to develop a generic theoretical framework – and, therefore, theory-based analytical models – that could produce reliable, a priori predictions of properties of [PC + FA] binders. In recent years, machine learning (ML) – which is purely data-driven, as opposed to being derived from theorical underpinnings – …

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Deep Learning To Predict The Hydration And Performance Of Fly Ash-Containing Cementitious Binders, Taihao Han, Rohan Bhat, Sai Akshay Ponduru, Amit Sarkar, Jie Huang, Gaurav Sant, Hongyan Ma, Narayanan Neithalath, Aditya Kumar Mar 2023

Deep Learning To Predict The Hydration And Performance Of Fly Ash-Containing Cementitious Binders, Taihao Han, Rohan Bhat, Sai Akshay Ponduru, Amit Sarkar, Jie Huang, Gaurav Sant, Hongyan Ma, Narayanan Neithalath, Aditya Kumar

Electrical and Computer Engineering Faculty Research & Creative Works

Fly ash (FA) – an industrial byproduct – is used to partially substitute Portland cement (PC) in concrete to mitigate concrete's environmental impact. Chemical composition and structure of FAs significantly impact hydration kinetics and compressive strength of concrete. Due to the substantial diversity in these physicochemical attributes of FAs, it has been challenging to develop a generic theoretical framework – and, therefore, theory-based analytical models – that could produce reliable, a priori predictions of properties of [PC + FA] binders. In recent years, machine learning (ML) – which is purely data-driven, as opposed to being derived from theorical underpinnings – …

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Unmanned-Aircraft-System-Assisted Early Wildfire Detection With Air Quality Sensors †, Doaa Rjoub, Ahmad Alsharoa, Ala'eddin Masadeh Mar 2023

Unmanned-Aircraft-System-Assisted Early Wildfire Detection With Air Quality Sensors †, Doaa Rjoub, Ahmad Alsharoa, Ala'eddin Masadeh

Electrical and Computer Engineering Faculty Research & Creative Works

Numerous Hectares of Land Are Destroyed by Wildfires Every Year, Causing Harm to the Environment, the Economy, and the Ecology. More Than Fifty Million Acres Have Burned in Several States as a Result of Recent Forest Fires in the Western United States and Australia. According to Scientific Predictions, as the Climate Warms and Dries, Wildfires Will Become More Intense and Frequent, as Well as More Dangerous. These Unavoidable Catastrophes Emphasize How Important Early Wildfire Detection and Prevention Are. the Energy Management System Described in This Paper Uses an Unmanned Aircraft System (UAS) with Air Quality Sensors (AQSs) to Monitor Spot …

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Special Section On Local And Distributed Electricity Markets, Rui Bo, Linquan Bai, Antonio J. Conejo, Jianzhong Wu, Tao Jiang, Fei Ding, Babak Enayati Mar 2023

Special Section On Local And Distributed Electricity Markets, Rui Bo, Linquan Bai, Antonio J. Conejo, Jianzhong Wu, Tao Jiang, Fei Ding, Babak Enayati

Electrical and Computer Engineering Faculty Research & Creative Works

Driven by the Goals of Clean Energy and Zero Carbon Emissions, the Power Industry is Undergoing Significant Transformations. the Rapid Growth of Diverse Distributed Energy Resources (DERs) at Grid Edge Such as Rooftop Photovoltaics (PVs) and Electric Vehicles is Transforming the Traditional Centralized Power Grid Management to a Decentralized, Bottom-Up, and Localized Control Paradigm. Establishing Local and Distribution-Level Electricity Markets Provides an Effective Solution to Managing Large Amounts of Small-Scale DERs. New Regulations Such as the Recent FERC Order 2222 in the U.S. Open the Door to DERs in the Wholesale Markets. through Coordinating the Local and Distribution-Level Markets with …

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Deep Learning To Predict The Hydration And Performance Of Fly Ash-Containing Cementitious Binders, Taihao Han, Rohan Bhat, Sai Akshay Ponduru, Amit Sarkar, Jie Huang, Gaurav Sant, Hongyan Ma, Narayanan Neithalath, Aditya Kumar Mar 2023

Deep Learning To Predict The Hydration And Performance Of Fly Ash-Containing Cementitious Binders, Taihao Han, Rohan Bhat, Sai Akshay Ponduru, Amit Sarkar, Jie Huang, Gaurav Sant, Hongyan Ma, Narayanan Neithalath, Aditya Kumar

Electrical and Computer Engineering Faculty Research & Creative Works

Fly ash (FA) – an industrial byproduct – is used to partially substitute Portland cement (PC) in concrete to mitigate concrete's environmental impact. Chemical composition and structure of FAs significantly impact hydration kinetics and compressive strength of concrete. Due to the substantial diversity in these physicochemical attributes of FAs, it has been challenging to develop a generic theoretical framework – and, therefore, theory-Based analytical models – that could produce reliable, a priori predictions of properties of [PC + FA] binders. in recent years, machine learning (ML) – which is purely data-driven, as opposed to being derived from theorical underpinnings – …

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Calculations Of Adsorption-Dependent Refractive Indices Of Metal-Organic Frameworks For Gas Sensing Applications, Nahideh Salehifar, Peter Holtmann, Abhishek Prakash Hungund, Homayoon Soleimani Dinani, Rex E. Gerald, Jie Huang Feb 2023

Calculations Of Adsorption-Dependent Refractive Indices Of Metal-Organic Frameworks For Gas Sensing Applications, Nahideh Salehifar, Peter Holtmann, Abhishek Prakash Hungund, Homayoon Soleimani Dinani, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Detection of Volatile Organic Compounds (VOCs) is One of the Most Challenging Tasks in Modelling Breath Analyzers Because of their Low Concentrations (Parts-Per-Billion (Ppb) to Parts-Per-Million (Ppm)) in Breath and the High Humidity Levels in Exhaled Breaths. the Refractive Index is One of the Crucial Optical Properties of Metal-Organic Frameworks (MOFs), Which is Changeable Via the Variation of Gas Species and Concentrations that Can Be Utilized as Gas Detectors. Herein, for the First Time, We Used Lorentz–Lorentz, Maxwell–Ga, and Bruggeman Effective Medium Approximation (EMA) Equations to Compute the Percentage Change in the Index of Refraction (∆n%) of ZIF-7, ZIF-8, ZIF-90, …

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Identification Of Volatile Organic Liquids By Combining An Array Of Fiber-Optic Sensors And Machine Learning, Wassana Naku, Anand K. Nambisan, Muhammad Roman, Chen Zhu, Rex E. Gerald, Jie Huang Feb 2023

Identification Of Volatile Organic Liquids By Combining An Array Of Fiber-Optic Sensors And Machine Learning, Wassana Naku, Anand K. Nambisan, Muhammad Roman, Chen Zhu, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Report an Array of Fiber-Optic Sensors based on the Fabry-Perot Interference Principle and Machine Learning-Based Analyses for Identifying Volatile Organic Liquids (VOLs). Three Optical Fiber Tip Sensors with Different Surfaces Were Included in the Array of Sensors to Improve the Accuracy for Identifying Liquids: An Intrinsic (Unmodified) Flat Cleaved Endface, a Hydrophobic-Coated Endface, and a Hydrophilic-Coated Endface. the Time-Transient Responses of Evaporating Droplets from the Optical Fiber Tip Sensors Were Monitored and Collected Following the Controlled Immersion Tests of 11 Different Organic Liquids. a Continuous Wavelet Transform Was Used to Convert the Time-Transient Response Signal into …

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Guest Editorial: Transition Towards Deep Decarbonisation Of Modern Energy Systems, Yujian Ye, Can Wan, Chenghong Gu, Dan Wu, Goran Strbac, Hongjian Sun, Peng Zhang, Rui Bo, Yi Tang, Zhongbei Tian Feb 2023

Guest Editorial: Transition Towards Deep Decarbonisation Of Modern Energy Systems, Yujian Ye, Can Wan, Chenghong Gu, Dan Wu, Goran Strbac, Hongjian Sun, Peng Zhang, Rui Bo, Yi Tang, Zhongbei Tian

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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A Novel Data-Driven Method For Two-Dimensional Angles Finding Via Uniform Rectangular Array With Automatic Pairing, Yanming Zhang, Lijun Jiang Feb 2023

A Novel Data-Driven Method For Two-Dimensional Angles Finding Via Uniform Rectangular Array With Automatic Pairing, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

A new hybrid dynamic mode decomposition (HDMD) algorithm is proposed to estimate the azimuth and elevation angles of multiple independent sources for two-dimensional (2D) massive MIMO systems with the uniform rectangular array (URA). To this end, the proposed hybrid scheme integrates the modified DMD with the augmented DMD. By treating the received data as spatial-spatial correlated signals, the modified DMD is first used to decompose these signals into spatial DMD spectrum and corresponding spatial dynamic modes. The obtained spatial DMD spectrum directly yields the electrical angle in the y-direction. Then, the corresponding electrical angle in the x-direction is computed using …

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Enhanced Two-Step Deep-Learning Approach For Electromagnetic-Inverse-Scattering Problems: Frequency Extrapolation And Scatterer Reconstruction, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng Feb 2023

Enhanced Two-Step Deep-Learning Approach For Electromagnetic-Inverse-Scattering Problems: Frequency Extrapolation And Scatterer Reconstruction, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

The electromagnetic-inverse-scattering (EMIS) problem is solved by a novel two-step deep-learning (DL) approach in this article. The newly proposed two-step DL approach not only predicts the multifrequency EM scattered field, but also overcomes the limitation of the conventional methods for solving EMIS problems, such as expensive computational cost, strong ill-conditions, and invalidity on high contrast. In the first step, the complex-valued deep residual convolutional neural network (DRCNN) is utilized to predict multifrequency EM scattered fields only using single-frequency EM scattered field information. Based on a new complex-valued deep convolutional encoder-decoder (DCED) structure, the second step utilizes the obtained multifrequency EM …

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Customised Multi-Energy Pricing: Model And Solutions, Qiuyi Hong, Fanlin Meng, Jian Liu Feb 2023

Customised Multi-Energy Pricing: Model And Solutions, Qiuyi Hong, Fanlin Meng, Jian Liu

Electrical and Computer Engineering Faculty Research & Creative Works

With the increasing interdependence among energies (e.g., electricity, natural gas and heat) and the development of a decentralized energy system, a novel retail pricing scheme in the multi-energy market is demanded. Therefore, the problem of designing a customized multi-energy pricing scheme for energy retailers is investigated in this paper. In particular, the proposed pricing scheme is formulated as a bilevel optimization problem. At the upper level, the energy retailer (leader) aims to maximize its profit. Microgrids (followers) equipped with energy converters, storage, renewable energy sources (RES) and demand response (DR) programs are located at the lower level and minimize their …

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Natural Organic Materials Based Memristors And Transistors For Artificial Synaptic Devices In Sustainable Neuromorphic Computing Systems, Md Mehedi Hasan Tanim, Zoe Templin, Feng Zhao Feb 2023

Natural Organic Materials Based Memristors And Transistors For Artificial Synaptic Devices In Sustainable Neuromorphic Computing Systems, Md Mehedi Hasan Tanim, Zoe Templin, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

Natural organic materials such as protein and carbohydrates are abundant in nature, renewable, and biodegradable, desirable for the construction of artificial synaptic devices for emerging neuromorphic computing systems with energy efficient operation and environmentally friendly disposal. These artificial synaptic devices are based on memristors or transistors with the memristive layer or gate dielectric formed by natural organic materials. The fundamental requirement for these synaptic devices is the ability to mimic the memory and learning behaviors of biological synapses. This paper reviews the synaptic functions emulated by a variety of artificial synaptic devices based on natural organic materials and provides a …

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The Visualization Of Orphadata Neurology Phenotypes, Daniel B. Hier, Raghu Yelugam, Michael D. Carrithers, Donald C. Wunsch Jan 2023

The Visualization Of Orphadata Neurology Phenotypes, Daniel B. Hier, Raghu Yelugam, Michael D. Carrithers, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Disease Phenotypes Are Characterized by Signs (What a Physician Observes during the Examination of a Patient) and Symptoms (The Complaints of a Patient to a Physician). Large Repositories of Disease Phenotypes Are Accessible through the Online Mendelian Inheritance of Man, Human Phenotype Ontology, and Orpha data Initiatives. Many of the Diseases in These Datasets Are Neurologic. for Each Repository, the Phenotype of Neurologic Disease is Represented as a List of Concepts of Variable Length Where the Concepts Are Selected from a Restricted Ontology. Visualizations of These Concept Lists Are Not Provided. We Address This Limitation by using Subsumption to Reduce …

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A Bilevel Game-Theoretic Decision-Making Framework For Strategic Retailers In Both Local And Wholesale Electricity Markets, Qiuyi Hong, Fanlin Meng, Jian Liu, Rui Bo Jan 2023

A Bilevel Game-Theoretic Decision-Making Framework For Strategic Retailers In Both Local And Wholesale Electricity Markets, Qiuyi Hong, Fanlin Meng, Jian Liu, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a bilevel game-theoretic model for multiple strategic retailers participating in both wholesale and local electricity markets while considering customers' switching behaviors. At the upper level, each retailer maximizes its own profit by making optimal pricing decisions in the retail market and bidding decisions in the day-ahead wholesale (DAW) and local power exchange (LPE) markets. The interaction among multiple strategic retailers is formulated using the Bertrand competition model. For the lower level, there are three optimization problems. First, the welfare maximization problem is formulated for customers to model their switching behaviors among different retailers. Second, a market-clearing problem …

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Subtypes Of Relapsing-Remitting Multiple Sclerosis Identified By Network Analysis, Quentin Howlett-Prieto, Chelsea Oommen, Michael D. Carrithers, Donald C. Wunsch, Daniel B. Hier Jan 2023

Subtypes Of Relapsing-Remitting Multiple Sclerosis Identified By Network Analysis, Quentin Howlett-Prieto, Chelsea Oommen, Michael D. Carrithers, Donald C. Wunsch, Daniel B. Hier

Electrical and Computer Engineering Faculty Research & Creative Works

We used network analysis to identify subtypes of relapsing-remitting multiple sclerosis subjects based on their cumulative signs and symptoms. The electronic medical records of 113 subjects with relapsing-remitting multiple sclerosis were reviewed, signs and symptoms were mapped to classes in a neuro-ontology, and classes were collapsed into sixteen superclasses by subsumption. After normalization and vectorization of the data, bipartite (subject-feature) and unipartite (subject-subject) network graphs were created using NetworkX and visualized in Gephi. Degree and weighted degree were calculated for each node. Graphs were partitioned into communities using the modularity score. Feature maps visualized differences in features by community. Network …

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Patients Arms Segmentation And Gesture Identification Using Standalone 3d Lidar Sensors, Omar Rinchi, Nathanael Nisbett, Ahmad Alsharoa Jan 2023

Patients Arms Segmentation And Gesture Identification Using Standalone 3d Lidar Sensors, Omar Rinchi, Nathanael Nisbett, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

The intelligent and autonomous learning of patients' activities will lead to an incredible progression toward future smart e-health systems. With the recent advances in artificial intelligence, signal processing, and computational capabilities; light detection and ranging (LiDAR) technology can play a significant role in enhancing the current patients' activity recognition (PAR) systems. In this paper, we propose confidential and accurate patient arms behavior monitoring using a standalone three-dimensional (3D) LiDAR sensor. Due to the unavailability of LiDAR data, we use a computer-programmed 3D simulator to generate virtual-LiDAR (V-LiDAR) 3D point cloud data that simulates real patient movements. These virtual data are …

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Securing The Transportation Of Tomorrow: Enabling Self-Healing Intelligent Transportation, Elanor Jackson, Sahra Sedigh Sarvestani Jan 2023

Securing The Transportation Of Tomorrow: Enabling Self-Healing Intelligent Transportation, Elanor Jackson, Sahra Sedigh Sarvestani

Electrical and Computer Engineering Faculty Research & Creative Works

The safety of autonomous vehicles relies on dependable and secure infrastructure for intelligent transportation. The doctoral research described in this paper aims to enable self-healing and survivability of the intelligent transportation systems required for autonomous vehicles (AV-ITS). The proposed approach is comprised of four major elements: qualitative and quantitative modeling of the AV-ITS, stochastic analysis to capture and quantify interdependencies, mitigation of disruptions, and validation of efficacy of the self-healing process. This paper describes the overall methodology and presents preliminary results, including an agent-based model for detection of and recovery from disruptions to the AV-ITS.

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A Physics-Based Model For Snapback-Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, Daryl G. Beetner Jan 2023

A Physics-Based Model For Snapback-Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

A simplified physical-based model for deep-snapback transient voltage suppressors (TVS) is developed in this article. While based on physics, the number of parameters and components is minimized, so the model can be tuned easily from available measurements of the packaged TVS. SPICE convergence issues seen in previous snapback device models are eliminated by adding nonlinear damping components to the model. No convergence issues were seen among any of the simulations performed for this study, which includes transmission-line pulse tests with multiple levels and rise times. The proposed model was used to represent two different TVS devices and was validated in …

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Miniature Optical Fiber-Tip High-Temperature Sensors Modified By Femtosecond Laser, Chen Zhu, Jie Huang Jan 2023

Miniature Optical Fiber-Tip High-Temperature Sensors Modified By Femtosecond Laser, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Miniature optical fiber-tip Fabry-Perot interferometric sensors fabricated by femtosecond laser micromachining for eliminating the additional Fresnel reflection and avoiding complicated amplitude modulation in the reflection spectra are demonstrated.

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Predicting Radiated Emissions From An Electrical Drive System, Giorgi Tsintsadze, Haran Manoharan, Daryl G. Beetner, Daniel Commerou, Brain Booth, Kerry Martin Jan 2023

Predicting Radiated Emissions From An Electrical Drive System, Giorgi Tsintsadze, Haran Manoharan, Daryl G. Beetner, Daniel Commerou, Brain Booth, Kerry Martin

Electrical and Computer Engineering Faculty Research & Creative Works

A Measurement-Based SPICE Model is Proposed to Predict Radiated Emissions from an Electrical Drive System over a Frequency Range from 20-300 MHz. the Model Combines a Model for the Radiated Emissions from the Cabling and Housings with a Model for Coupling Inside the Electrical Motor. the Electromagnetic Properties of the Cabling and Housings Were Captured with Measured S-Parameters. the Coupling Mechanisms Inside the Electrical Machine Were Represented using a Circuit- Element based Model. the Intent is to Provide Insight into How Coupling Mechanisms and Placement of Structures in the Motor Affect Radiated Emissions from the Drive System, and to Give …

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Challenges And Solutions For Automotive Ota Testing, Jiyu Wu, Yihong Qi, Penghui Shen, Wei Yu, Lie Liu, James L. Drewniak Jan 2023

Challenges And Solutions For Automotive Ota Testing, Jiyu Wu, Yihong Qi, Penghui Shen, Wei Yu, Lie Liu, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

OTA (Over-The-Air) Testing is Essential for Developing Assisted and Autonomous Driving Systems in Vehicles, as It Plays a Crucial Role in the Localization, Perception, and Intelligent Driving Capabilities of ICVs (Intelligent Connected Vehicles). Automotive Antennas, Typically Much Smaller in Size Than the Vehicle itself and Can Be Located in Various Positions, Require Spherical Near-Field Measurement for OTA Testing. While There Are Established Standards for OTA Testing Methods and Uncertainties for Mobile Devices, Base Stations, and Satellite Components, There Are Still Many Challenges in the OTA Testing of Automotive Systems. These Challenges, specifically in SISO (Single Input Single Output) and MIMO …

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A Thermal-Aware Dc-Ir Drop Analysis For 2.5d Ic, Shengxuan Xia, Baris M. Dogruoz, Yansheng Wang, Songping Wu, Siqi Bai, Chulsoon Hwang, Zhonghua Wu Jan 2023

A Thermal-Aware Dc-Ir Drop Analysis For 2.5d Ic, Shengxuan Xia, Baris M. Dogruoz, Yansheng Wang, Songping Wu, Siqi Bai, Chulsoon Hwang, Zhonghua Wu

Electrical and Computer Engineering Faculty Research & Creative Works

With the Trend of Higher Integration, 3D/2.5D IC Solutions Such as CoWoS (Chip-On-Wafer-On-Substrate) Have Become More Popular in Recent Years. Power Integrity (PI) is Always a Critical Part of the Design Especially When the Power Consumption Requirements Are Important Specs for High-Performance Computing. DC-IR Drop is One of the Criteria within Power Integrity Considerations. However, Ordinary Electrical-Only Simulation for DC-IR Drop Will Be an Underestimation Because It Neglects the Copper Conductivity Dropping Due to the Temperature Rising. Thus, an Engineering Solution for Electrical-Thermal Co-Simulation is Important to Help to Provide Both an Accurate PI Analysis and the Proper Mitigations of …

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Characterization And Modeling Of Sparkless Discharge To A Touch Screen Display, Jianchi Zhou, Cheung Wei Lam, Zhekun Peng, Daryl G. Beetner, David Pommerenke Jan 2023

Characterization And Modeling Of Sparkless Discharge To A Touch Screen Display, Jianchi Zhou, Cheung Wei Lam, Zhekun Peng, Daryl G. Beetner, David Pommerenke

Electrical and Computer Engineering Faculty Research & Creative Works

Although Corona Discharge to a Touchscreen Display is Not Associated with the Spark, It Could Cause Soft and Hard Failures Due to Electromagnetic Coupling to Sensitive Electronics Beneath the Glass. Experimental Data Were Obtained to Characterize These Sparkless Discharges and an Equivalent Circuit Model Was Constructed to Predict the Resulting Coupling to Touchscreen Electronics. Measurements and Simulation Indicate that a Thinner Glass and a Higher Touchscreen Indium-Tin-Oxide (ITO) Sense Trace Impedance Both Lead to Higher ESD Risk by Delivering Higher Energy into the Sensing IC. a CST Co-Simulation Model is Proposed and is Shown to Model the Displacement Current Accurately. …

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Inverter Pq Control With Trajectory Tracking Capability For Microgrids Based On Physics-Informed Reinforcement Learning, Buxin She, Fangxing Li, Hantao Cui, Hang Shuai, Oroghene Oboreh-Snapps, Rui Bo, Nattapat Praisuwanna, Jingxin Wang, Leon M. Tolbert Jan 2023

Inverter Pq Control With Trajectory Tracking Capability For Microgrids Based On Physics-Informed Reinforcement Learning, Buxin She, Fangxing Li, Hantao Cui, Hang Shuai, Oroghene Oboreh-Snapps, Rui Bo, Nattapat Praisuwanna, Jingxin Wang, Leon M. Tolbert

Electrical and Computer Engineering Faculty Research & Creative Works

The increasing penetration of inverter-based resources (IBRs) calls for an advanced active and reactive power (PQ) control strategy in microgrids. To enhance the controllability and flexibility of the IBRs, this paper proposed an adaptive PQ control method with trajectory tracking capability, combining model-based analysis, physics-informed reinforcement learning (RL), and power hardware-in-the-loop (HIL) experiments. First, model-based analysis proves that there exists an adaptive proportional-integral controller with time-varying gains that can ensure any exponential PQ output trajectory of IBRs. These gains consist of a constant factor and an exponentially decaying factor, which are then obtained using a model-free deep reinforcement learning approach …

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Filter-Based Fault Detection And Isolation In Distributed Parameter Systems Modeled By Parabolic Partial Differential Equations, Hasan Ferdowsi, Jia Cai, Sarangapani Jagannathan Jan 2023

Filter-Based Fault Detection And Isolation In Distributed Parameter Systems Modeled By Parabolic Partial Differential Equations, Hasan Ferdowsi, Jia Cai, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper covers model-based fault detection and isolation for linear and nonlinear distributed parameter systems (DPS). The first part mainly deals with actuator, sensor and state fault detection and isolation for a class of DPS represented by a set of coupled linear partial differential equations (PDE). A filter based observer is designed based on the linear PDE representation using which a detection residual is generated. A fault is detected when the magnitude of the detection residual exceeds a detection threshold. Upon detection, several isolation estimators are designed using filters whose output residuals are compared with predefined isolation thresholds. A fault …

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