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Electrical and Computer Engineering Faculty Research & Creative Works

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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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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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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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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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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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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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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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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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Predicting Dissolution Kinetics Of Tricalcium Silicate Using Deep Learning And Analytical Models, Taihao Han, Sai Akshay Ponduru, Arianit Reka, Jie Huang, Gaurav Sant, Aditya Kumar Jan 2023

Predicting Dissolution Kinetics Of Tricalcium Silicate Using Deep Learning And Analytical Models, Taihao Han, Sai Akshay Ponduru, Arianit Reka, Jie Huang, Gaurav Sant, Aditya Kumar

Electrical and Computer Engineering Faculty Research & Creative Works

The dissolution kinetics of Portland cement is a critical factor in controlling the hydration reaction and improving the performance of concrete. Tricalcium silicate (C3S), the primary phase in Portland cement, is known to have complex dissolution mechanisms that involve multiple reactions and changes to particle surfaces. As a result, current analytical models are unable to accurately predict the dissolution kinetics of C3S in various solvents when it is undersaturated with respect to the solvent. This paper employs the deep forest (DF) model to predict the dissolution rate of C3S in the undersaturated solvent. The …

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Predicting Compressive Strength And Hydration Products Of Calcium Aluminate Cement Using Data-Driven Approach, Sai Akshay Ponduru, Taihao Han, Jie Huang, Aditya Kumar Jan 2023

Predicting Compressive Strength And Hydration Products Of Calcium Aluminate Cement Using Data-Driven Approach, Sai Akshay Ponduru, Taihao Han, Jie Huang, Aditya Kumar

Electrical and Computer Engineering Faculty Research & Creative Works

Calcium aluminate cement (CAC) has been explored as a sustainable alternative to Portland cement, the most widely used type of cement. However, the hydration reaction and mechanical properties of CAC can be influenced by various factors such as water content, Li2CO3 content, and age. Due to the complex interactions between the precursors in CAC, traditional analytical models have struggled to predict CAC binders' compressive strength and porosity accurately. To overcome this limitation, this study utilizes machine learning (ML) to predict the properties of CAC. The study begins by using thermodynamic simulations to determine the phase assemblages of …

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Cooperative Deep $Q$ -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan Jan 2023

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

Electrical and Computer Engineering Faculty Research & Creative Works

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 …

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Detection Of Surface Cracks In Metals Using Microwave And Millimeter-Wave Nondestructive Testing Techniques-A Review, Mohamed A. Abou-Khousa, Mohammed Saif Ur Rahman, Kristen M. Donnell, Mohammad Tayeb Al (Tayeb) (Al) Qaseer Jan 2023

Detection Of Surface Cracks In Metals Using Microwave And Millimeter-Wave Nondestructive Testing Techniques-A Review, Mohamed A. Abou-Khousa, Mohammed Saif Ur Rahman, Kristen M. Donnell, Mohammad Tayeb Al (Tayeb) (Al) Qaseer

Electrical and Computer Engineering Faculty Research & Creative Works

Integrity Assessment of Metallic Structures Requires Inspection Tools Capable of Detecting and Evaluating Cracks Reliably. to This End, Many Microwave and Millimeter-Wave Nondestructive Testing and Evaluation (NDT&E) Methods Have Been Developed and Applied Successfully in the Past. Detection of Fatigue Cracks with Widths Less Than 5 Μ M using Noncontact Microwave-Based Inspection Methods Was Demonstrated in the 1970s. Since their Introduction, These Methods Have Evolved Considerably Toward Enhancing the Detection Sensitivity and Resolution. Undertaking Key Application Challenges Has Attracted Considerable Attention in the Past Three Decades and Led to the Development of the Near-Field Techniques for Crack Detection. to Address …

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A Resilience-Oriented Multi-Stage Adaptive Distribution System Planning Considering Multiple Extreme Weather Events, Siyuan Wang, Rui Bo Jan 2023

A Resilience-Oriented Multi-Stage Adaptive Distribution System Planning Considering Multiple Extreme Weather Events, Siyuan Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Climate Change May Increase the Risk of an Area Being Hit by Multiple Extreme Weather Events, Which Brings Significant Challenges for Distribution System Planners in an Increasing Renewable Penetration Era. There is an Urgent Need for Planning Approaches to Be More Flexible and Allow for Adaptive Adjustments in the Future to Hedge Against High Uncertainties in Extreme Weather Event Scenarios. in This Work, We Propose a Resilience-Oriented Distribution System Planning Approach that Considers Multiple Extreme Weather Events. a Multi-Stage Hybrid-Stochastic-And-Robust Formulation is Developed to Model Decisions Not Only for Initial Investments, But Also for Adaptive Investments and Emergent Operations in …

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Extended Kalman Filter Based Resilient Formation Tracking Control Of Multiple Unmanned Vehicles Via Game-Theoretical Reinforcement Learning, Lei Xue, Bei Ma, Jian Liu, Chaoxu Mu, Donald C. Wunsch Jan 2023

Extended Kalman Filter Based Resilient Formation Tracking Control Of Multiple Unmanned Vehicles Via Game-Theoretical Reinforcement Learning, Lei Xue, Bei Ma, Jian Liu, Chaoxu Mu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Discuss the Resilient Formation Tracking Control Problem of Multiple Unmanned Vehicles (MUV). a Dynamic Leader-Follower Distributed Control Structure is Utilized to Optimize the Performance of the Formation Tracking. for the Follower of the MUV, the Leader is a Cooperative Unmanned Vehicle, and the Target of Formation Tracking is a Non-Cooperative Unmanned Vehicle with a Nonlinear Trajectory. Therefore, an Extended Kalman Filter (EKF) Observer is Designed to Estimate the State of the Target. Then the Leader of the MUV is Adjusted Dynamically According to the State of the Target. in Order to Describe the Interactions between the …

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Advances In Fiber-Optic Extrinsic Fabry-Perot Interferometric Physical And Mechanical Sensors: A Review, Chen Zhu, Hongkun Zheng, Lingmei Ma, Zheyi Yao, Bo Liu, Jie Huang, Yunjiang Rao Jan 2023

Advances In Fiber-Optic Extrinsic Fabry-Perot Interferometric Physical And Mechanical Sensors: A Review, Chen Zhu, Hongkun Zheng, Lingmei Ma, Zheyi Yao, Bo Liu, Jie Huang, Yunjiang Rao

Electrical and Computer Engineering Faculty Research & Creative Works

Fabry-Perot Interferometers Have Found a Multitude of Scientific and Industrial Applications Ranging from Gravitational Wave Detection, High-Resolution Spectroscopy, and Optical Filters to Quantum Optomechanics. Integrated with Optical Fiber Waveguide Technology, the Fiber-Optic Fabry-Perot Interferometers Have Emerged as a Unique Candidate for High-Sensitivity Sensing and Have Undergone Tremendous Growth and Advancement in the Past Two Decades with their Successful Applications in an Expansive Range of Fields. the Extrinsic Cavity-Based Devices, I.e., the Fiber-Optic Extrinsic Fabry-Perot Interferometers (EFPIs), Enable Great Flexibility in the Design of the Sensitive Fabry-Perot Cavity Combined with State-Of-The-Art Micromachining and Conventional Mechanical Fabrication, Leading to the Development of …

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Decoupling Optimization For Complex Pdn Structures Using Deep Reinforcement Learning, Ling Zhang, Li Jiang, Jack Juang, Zhiping Yang, Er Ping Li, Chulsoon Hwang Jan 2023

Decoupling Optimization For Complex Pdn Structures Using Deep Reinforcement Learning, Ling Zhang, Li Jiang, Jack Juang, Zhiping Yang, Er Ping Li, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

This Article Presents a New Optimization Method for Complex Power Distribution Networks (PDNs) with Irregular Shapes and Multilayer Structures using Deep Reinforcement Learning (DRL), Which Has Not Been Considered Before. a Fast Boundary Integration Method is Applied to Compute the Impedance Matrix of a PDN Structure. Subsequently, a New DRL Algorithm based on Proximal Policy Optimization (PPO) is Proposed to Optimize the Decoupling Capacitor (Decap) Placement by Minimizing the Number of Decaps While Satisfying the Desired Target Impedance. in the Proposed Approach, the PDN Structure Information is Encoded into Matrices and Serves as the Input of the DRL Algorithm, Which …

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A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi Jan 2023

A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi

Electrical and Computer Engineering Faculty Research & Creative Works

According to the Third Generation Partnership Project Specification, a Period of 8-12.8 H is Required to Evaluate the Multiple-Input-Multiple-Output (MIMO) Performance of a Wireless Terminal for a Single Frequency Point and Channel Model Combination. the Following Article Proposes a Semi-Simulation, Semi-Measurement-Based MIMO throughput Modeling Scheme Which Can Reduce the 8-12.8-H Measurement Time to 40-60 Min, Corresponding to More Than a Ten Times Improvement of the Test Efficiency, Without Loss of the Test Accuracy.

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Decentralized And Coordinated V-F Control For Islanded Microgrids Considering Der Inadequacy And Demand Control, Buxin She, Fangxing Li, Hantao Cui, Jinning Wang, Liang Min, Oroghene Oboreh-Snapps, Rui Bo Jan 2023

Decentralized And Coordinated V-F Control For Islanded Microgrids Considering Der Inadequacy And Demand Control, Buxin She, Fangxing Li, Hantao Cui, Jinning Wang, Liang Min, Oroghene Oboreh-Snapps, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Proposes a Decentralized and Coordinated Voltage and Frequency (V-F) Control Framework for Islanded Microgrids, with Full Consideration of the Limited Capacity of Distributed Energy Resources (DERs) and V-F Dependent Load. First, the Concept of DER Inadequacy is Illustrated with the Challenges It Poses. Then, a Decentralized and Coordinated Control Framework is Proposed to Regulate the Output of Inverter-Based Generations and Reallocate Limited DER Capacity for V-F Control. the Control Framework is Composed of a Power Regulator and a V-F Regulator, Which Generates the Supplementary Signals for the Primary Controller. the Power Regulator Regulates the Output of Grid-Forming Inverters …

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