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Articles 4891 - 4920 of 36809

Full-Text Articles in Engineering

Towards Robust Consensus For Intelligent Decision-Making In Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan Jan 2023

Towards Robust Consensus For Intelligent Decision-Making In Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Distributed consensus is the core aspect of blockchain protocol security design. Recent protocols like IOTA have improved concurrency and scalability over Proof-of-work (PoW) with Bitcoin but have core design decisions that are inefficient for limited devices and do not take advantage of previous network experience to reduce calculations. This work proposes the first blockchain consensus protocol based on active machine-learning decisions, called Proof-of-history (PoH). PoH is setup as a distributed reinforcement-learning task for monitoring classification and training of blockchain transactions with an inner deep classifier. Early theoretical analysis and simulations show that PoH is robust to uncoordinated byzantine attacks through …

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A Combined Model For Transient And Self-Heating Of Snapback Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, David Pommerenke, Daryl G. Beetner Jan 2023

A Combined Model For Transient And Self-Heating Of Snapback Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, David Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

A simplified physics-based model for predicting the transient response and self-heating behavior of silicon-controlled rectifier (SCR) snapback-type transient voltage suppressors (TVS) is presented. Comparisons of the predicted quasi-static behavior and transient waveforms with measurements suggest that the proposed model accurately captures the most important characteristics of the device. Its simplified nature means it can be easily tuned using only data obtained from package-level measurements.

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Deep-Learning-Based Accurate Beamforming Prediction Using Lidar-Assisted Network, Omar Rinchi, Ahmad Alsharoa, Ibrahem Shatnawi Jan 2023

Deep-Learning-Based Accurate Beamforming Prediction Using Lidar-Assisted Network, Omar Rinchi, Ahmad Alsharoa, Ibrahem Shatnawi

Electrical and Computer Engineering Faculty Research & Creative Works

Beamforming optimization can enhance the next-generation wireless networks. However, finding the optimal beamforming in real-time is hard due to the need for large beam training overhead. The problem can be more challenging in dynamic environments with small coherence channel time. In this paper, we propose an accurate beam prediction solution using light detection and ranging (LiDAR)-assisted radio frequency (RF) system. More specifically, we propose a deep-learning model based on long-sort term memory (LSTM) to predict future beam indices from a set of pre-defined beam steering codebook. In addition to solving the beamforming overhead problem, the proposed deep learning approach is …

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Accelerated Statistical Eye Diagram Estimation Method For Efficient Signal Integrity Analysis, Junyong Park, Youngwoo Kim, Donghyun Kim Jan 2023

Accelerated Statistical Eye Diagram Estimation Method For Efficient Signal Integrity Analysis, Junyong Park, Youngwoo Kim, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes an accelerated statistical eye diagram estimation method for efficient signal integrity (SI) analysis. An eye diagram is a critical metric in the SI analysis, however obtaining an eye diagram is time-consuming in simulation. The required time might be a few weeks depending on the complexity. Because the eye diagram is obtained by superposition of the received waveforms. Statistical eye diagram estimation methods were proposed to make the eye diagram acquisition efficient, however, it still has a limited improvement due to a large number of convolution operations. To address this limitation, the proposed method includes two approaches: (i) …

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Implementing The Fast Full-Wave Electromagnetic Forward Solver Using The Deep Convolutional Encoder-Decoder Architecture, He Ming Yao, Lijun Jiang, Michael Ng Jan 2023

Implementing The Fast Full-Wave Electromagnetic Forward Solver Using The Deep Convolutional Encoder-Decoder Architecture, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

In this communication, a novel deep learning (DL)-based solver is proposed for the electromagnetic forward (EMF) process. It is based on the complex-valued deep convolutional neural networks (DConvNets) comprising an encoder network and a corresponding decoder network with pixel-wise regression layer. The encoder network takes the incident EM wave and the contrast (permittivity) distribution of the object as the input. It channels the processed data into the corresponding decoder network to predict the total EM field due to the scatter of the input incident EM wave. The training of the proposed DConvNets is done using the simple synthetic dataset. Due …

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Bidirectional Asymmetric Clllc Resonant Dc-Dc Converter For Onboard Electric Vehicle Chargers, Angshuman Sharma, Alvaro Cardoza, Kartikeya J.P. Veeramraju, Oroghene Oboreh-Snapps, Jonathan W. Kimball Jan 2023

Bidirectional Asymmetric Clllc Resonant Dc-Dc Converter For Onboard Electric Vehicle Chargers, Angshuman Sharma, Alvaro Cardoza, Kartikeya J.P. Veeramraju, Oroghene Oboreh-Snapps, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

Bidirectional CLLLC resonant dc-dc converters with an asymmetric tank can narrow the switching frequency bandwidth required to meet the asymmetric voltage gains in the two directions of power flow. Consequently, higher power density and efficiency may be feasible. in this paper, a CLLLC resonant converter with asymmetric primary and secondary capacitances is investigated for charging and discharging the next-generation 900 V traction battery of an electric vehicle. First, a new voltage gain equation is formulated using the First Harmonic Approximation. Then, the proposed gain equation is used to design the asymmetric resonant tank. the effects of asymmetric capacitances on the …

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Retracted: A Robust Integrated Approach For Optimal Management Of Power Networks Encompassing Wind Power Plants, Aliasghar Baziar, Mohammad Reza Akbarizadeh, Amin Hajizadeh, Mousa Marzband, Rui Bo Jan 2023

Retracted: A Robust Integrated Approach For Optimal Management Of Power Networks Encompassing Wind Power Plants, Aliasghar Baziar, Mohammad Reza Akbarizadeh, Amin Hajizadeh, Mousa Marzband, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper basically concentrates on providing some significant steps for congestion management of the power systems based on an interval-Based robust chance constrained transmission switching (IBRCC-TS) approach for decreasing the congestion of the system while increasing the robustness of the system against uncertainties of the wind turbines. However, the utilization of TS approach in the power system is a severe challenge, since there is no limitation over the switching rate during a certain timespan in the network as well as the power switches' failure uncertainty. Besides, the frequent switching by the TS method decreases the switch maintenance and puts the …

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Small Signal Stability Analysis Of Virtual Impedance Control In Islanded Microgrid, Oroghene Oboreh-Snapps, Kartikeya J.P. Veeramraju, Arnold Fernandes, Alvaro Cardoza, Angshuman Sharma, Jonathan Saelens, Jonathan W. Kimball Jan 2023

Small Signal Stability Analysis Of Virtual Impedance Control In Islanded Microgrid, Oroghene Oboreh-Snapps, Kartikeya J.P. Veeramraju, Arnold Fernandes, Alvaro Cardoza, Angshuman Sharma, Jonathan Saelens, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper examines the impact of virtual impedance control in an inverter-dominated microgrid (MG) system. the goal is to provide a clear understanding of Virtual Impedance (VI) control toward MG stability. This analysis is performed by developing the system's Small-Signal Model (SSM) and studying the poles' trajectory change when the system's key control parameters are varied. the results indicate that VI will benefit system stability when considering MG with low X/R while negatively affecting MG with high X/R. Also, there is a trade-off between the coupling impedance of the inverter and the VI parameters, which needs to be considered when …

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Natural Organic Fructose-Based Nonvolatile Resistive Switching Memory For Environmental Sustainability In Computing, Yuan Xing, Feng Zhao Jan 2023

Natural Organic Fructose-Based Nonvolatile Resistive Switching Memory For Environmental Sustainability In Computing, Yuan Xing, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

The fast growth and wide applications of Internet of Things (IoT) require enormous amounts of energy consumption and hardware devices for computation, which present significant challenges of energy efficiency and environmental sustainability. Von Neumann computing architecture is reaching its bottleneck and limited by low energy efficiency. Fabrication of conventional semiconductor devices results in depletion of nonrenewable resources, while the disposal of these devices causes electronic waste with serious ecological, health, and economic issues. One potential solution to address these challenges simultaneously is by brain-like neuromorphic computing with essential hardware components made from natural organic materials for energy efficient operation, sustainable …

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A Machine Learning Approach To Support Neuromorphic Device Design And Microfabrication, Abdi Yamil Vicenciodelmoral, Md Mehedi Hasan Tanim, Feng Zhao, Xinghui Zhao Jan 2023

A Machine Learning Approach To Support Neuromorphic Device Design And Microfabrication, Abdi Yamil Vicenciodelmoral, Md Mehedi Hasan Tanim, Feng Zhao, Xinghui Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

Neuromorphic chips provide a potential solution for sustainable computing, as they attempt to mimic the neuronal architectures in human brain and show great potentials in reducing energy consumption in the order of magnitude and also improve the computational performance. However, the fabrication process for neuromorphic chips is costly and currently based on trial-and-error, which adds complexity to the design process. In this paper, we address these challenges by designing and developing machine learning guided microfabrication process for Resistive Random Access Memory (RRAM), which is a key device in neuromorphic chips. Specifically, our research makes the following contributions: 1) we successfully …

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Instantaneous Frequency Estimation Of Fm Signals Under Gaussian And Symmetric Alpha-Stable Noise: Deep Learning Versus Time-Frequency Analysis, Huda Saleem Razzaq, Zahir M. Hussain Jan 2023

Instantaneous Frequency Estimation Of Fm Signals Under Gaussian And Symmetric Alpha-Stable Noise: Deep Learning Versus Time-Frequency Analysis, Huda Saleem Razzaq, Zahir M. Hussain

Research outputs 2022 to 2026

Deep learning (DL) and machine learning (ML) are widely used in many fields but rarely used in the frequency estimation (FE) and slope estimation (SE) of signals. Frequency and slope estimation for frequency-modulated (FM) and single-tone sinusoidal signals are essential in various applications, such as wireless communications, sound navigation and ranging (SONAR), and radio detection and ranging (RADAR) measurements. This work proposed a novel frequency estimation technique for instantaneous linear FM (LFM) sinusoidal wave using deep learning. Deep neural networks (DNN) and convolutional neural networks (CNN) are classes of artificial neural networks (ANNs) used for the frequency and slope estimation …

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Improved Rate Of Secret Key Generation Using Passive Re-Configurable Intelligent Surfaces For Vehicular Networks, Hina Ayaz, Muhammad Waqas, Ghulam Abbas, Ziaul Haq Abbas, Muhammad Bilal, Kyung-Sup Kwak Jan 2023

Improved Rate Of Secret Key Generation Using Passive Re-Configurable Intelligent Surfaces For Vehicular Networks, Hina Ayaz, Muhammad Waqas, Ghulam Abbas, Ziaul Haq Abbas, Muhammad Bilal, Kyung-Sup Kwak

Research outputs 2022 to 2026

The reconfigurable intelligent surfaces (RIS) is a new technology that can be utilized to provide security to vehicle-to-vehicle (V2V) communications at the physical layer. In this paper, we achieve a higher key generation rate for V2V communications at lower cost and computational complexity. We investigate the use of a passive RIS as a relay, to introduce channel diversity and increase the key generation rate (KGR), accordingly. In this regard, we consider the subsets of consecutive reflecting elements instead of the RIS as a whole in a time slot, i.e., instead of a single reflector, the subsets of reflectors are utilized …

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Memory-Based Adaptive Sliding Mode Load Frequency Control In Interconnected Power Systems With Energy Storage, Farhad Farivar, Octavian Bass, Daryoush Habibi Jan 2023

Memory-Based Adaptive Sliding Mode Load Frequency Control In Interconnected Power Systems With Energy Storage, Farhad Farivar, Octavian Bass, Daryoush Habibi

Research outputs 2022 to 2026

This paper presents a memory-based adaptive sliding mode load frequency control (LFC) strategy aimed at minimizing the impacts of exogenous power disturbances and parameter uncertainties on frequency deviations in interconnected power systems with energy storage. First, the dynamic model of the system is constructed by considering the participation of the energy storage system (ESS) in the conventional decentralized LFC model of a multiarea power system. A disturbance observer (DOB) is proposed to generate an online approximation of the lumped disturbance. In order to enhance the transient performance of the system and effectively mitigate the adverse effects of power fluctuations on …

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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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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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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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Averaged Behavior Model Of Current-Mode Buck Converters For Transient Power Noise Analysis, Anfeng Huang, Jingdong Sun, Hongseok Kim, Zhenxue Xu, Shuai Jin, Songping Wu, Zhiping Yang, Kelvin Qiu, Jun Fan, Chulsoon Hwang Jan 2023

Averaged Behavior Model Of Current-Mode Buck Converters For Transient Power Noise Analysis, Anfeng Huang, Jingdong Sun, Hongseok Kim, Zhenxue Xu, Shuai Jin, Songping Wu, Zhiping Yang, Kelvin Qiu, Jun Fan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate Evaluation and Simulation of Power Noise is Critical in the Development of Modern Electronic Devices. However, the Widely Used Target Impedance Fails to Predict the Low-Frequency Noise Generated in a Device Due to the Existence of the Dc–dc Converter, Whose Output Impedance Can Change under Different Loading Conditions. a Physical Circuit Model is Then Desired to Replicate the Behavior of a Voltage Regulator Module, and the Average Technique is an Efficient Method to Estimate the Noise of a Pulse Width-Modulated (PWM) Converter. with the Emergence of Converters with Adaptive On-Time (AOT) Controllers, More Complex Averaging Methods Are Required, But …

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Methodology For Analyzing Coupling Mechanisms In Rfi Problems Based On Peec, Xu Wang, Anfeng Huang, Wei Zhang, Reza Yazdani, Donghyun Kim, Takashi Enomoto, Taketoshi Sekine, Kenji Araki, Jun Fan, Chulsoon Hwang Jan 2023

Methodology For Analyzing Coupling Mechanisms In Rfi Problems Based On Peec, Xu Wang, Anfeng Huang, Wei Zhang, Reza Yazdani, Donghyun Kim, Takashi Enomoto, Taketoshi Sekine, Kenji Araki, Jun Fan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Article, a Method for Analyzing Coupling Mechanisms in Radio Frequency Interference (RFI) Problems is Proposed. the Partial Element Equivalent Circuit (PEEC) Method is First Used to Derive the Retarded Inductances and Capacitances between Different Mesh Cells. with the Introduction of a Novel Partitioning Algorithm, the Capacitive Coupling and Inductive Coupling between Arbitrary Layout Parts Can Be Quantified based on the Magnitude of the Displacement Current and Induced Voltage Drop. the Accuracy of the PEEC Models is Validated by Comparison with Different Commercial Tools. the Proposed Coupling Mechanism Analysis Flow Provides a Useful Prelayout Tool for RFI Risk Analysis.

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Embeddable Soil Moisture Content Sensor Based On Open–End Microwave Coaxial Cable Resonator, Jing Guo, Yan Tang, Yongji Wu, Chen Zhu, Jie Huang Jan 2023

Embeddable Soil Moisture Content Sensor Based On Open–End Microwave Coaxial Cable Resonator, Jing Guo, Yan Tang, Yongji Wu, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Propose and Demonstrate a Novel Corrosion-Resistant, Embeddable Open-End Coaxial Cable Soil Moisture Sensor. This Microwave Resonator is Constructed using Two Reflectors Along the Coaxial Line. the First Reflector is a Metal Post at the Signal Input End, Short-Circuiting the Inner Conductor to the Outer Conductor. the Second Reflector Comprises a Welded Metal Plate Parallel to the Open-End of the Coaxial Line, Maintaining a Fixed Gap. a Moisture-Sensitive Polyvinyl Alcohol (PVA) Film is Inserted into This Gap. the Resonance Frequency of the Open-End Coaxial Cable Resonator is Highly Dependent on the Fringe Capacitance, Which Varies with Soil …

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Electromagnetic Transmit Array With Optical Control For Beamforming, Wei Zhang, Javad Meiguni, Yin Sun, Muqi Ouyang, Xin Yan, Xu Wang, Reza Yazdani, Daryl G. Beetner, Donghyun Kim, David Pommerenke Jan 2023

Electromagnetic Transmit Array With Optical Control For Beamforming, Wei Zhang, Javad Meiguni, Yin Sun, Muqi Ouyang, Xin Yan, Xu Wang, Reza Yazdani, Daryl G. Beetner, Donghyun Kim, David Pommerenke

Electrical and Computer Engineering Faculty Research & Creative Works

This Proof-Of-Concept Paper Demonstrates the Feasibility of using a Slide Projector to Steer the Beam of a Transmit Array by Adding Solar Cells and Varactor Diodes to Each Unit Cell. by Irradiating Each Solar Cell with the Light of Different Intensities from a Slide Projector, the Measured Phase of the Wave Transmitted by the 4x4 Transmit Array Shifts within 92° at 4.26 GHz, While the Variation in Magnitude is Measured within 4 DB. Different Light Configurations Are Identified Via a Searching Algorithm to Achieve Peak/null Beamforming in a Particular Direction. the Beam of the Prototypical 4x4 Transmit Array Can Be …

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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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Real-Time Air Gap And Thickness Measurement Of Continuous Caster Mold Flux By Extrinsic Fabry-Perot Interferometer, Abhishek Prakash Hungund, Hanok Tekle, Bohong Zhang, Ronald J. O'Malley, Jeffrey D. Smith, Rex E. Gerald, Jie Huang Jan 2023

Real-Time Air Gap And Thickness Measurement Of Continuous Caster Mold Flux By Extrinsic Fabry-Perot Interferometer, Abhishek Prakash Hungund, Hanok Tekle, Bohong Zhang, Ronald J. O'Malley, Jeffrey D. Smith, Rex E. Gerald, Jie Huang

Materials Science and Engineering Faculty Research & Creative Works

Mold Flux plays a critical role in continuous casting of steel. Along with many other functions, the mold flux in the gap between the solidifying steel shell and the mold serves as a medium for controlling heat transfer and as a barrier to prevent shell sticking to the mold. This manuscript introduces a novel method of monitoring the structural features of a mold flux film in real-time in a simulated mold gap. A 3-part stainless-steel mold was designed with a 2 mm, 4 mm and, 6 mm step profile to contain mold flux films of varying thickness. An Extrinsic Fabry-Perot …

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Managing Reserve Deliverability Risk Of Integrated Electricity-Heat Systems In Day-Ahead Market: A Distributionally Robust Joint Chance Constrained Approach, Yang Chen, Jianxue Wang, Siyuan Wang, Rui Bo, Chenjia Gu, Qingtao Li Jan 2023

Managing Reserve Deliverability Risk Of Integrated Electricity-Heat Systems In Day-Ahead Market: A Distributionally Robust Joint Chance Constrained Approach, Yang Chen, Jianxue Wang, Siyuan Wang, Rui Bo, Chenjia Gu, Qingtao Li

Electrical and Computer Engineering Faculty Research & Creative Works

The integrated electricity and heat system (IEHS) is an emerging demand-side flexible resource for power systems. IEHS operators participating in electricity markets considering their capabilities in reserve provision will face the reserve deliverability risk due to the energy-limited storage nature of heat systems. To address this challenge and increase profitability, a distributionally robust joint chance-constrained mechanism with enhanced quantifications is adopted for the heating system and reserve deployment uncertainties. Detailed pipeline storage representation for thermal networks and integrated demand response are incorporated into this strategic participation model. A two-stage distributionally robust joint chance constrained program is then incorporated to effectively …

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Observer-Based Model Predictive Control With Continuous Control Set For Single-Phase Rectifiers, Milad Dehghanzadeh, Rui Bo, Kamal Al-Haddad Jan 2023

Observer-Based Model Predictive Control With Continuous Control Set For Single-Phase Rectifiers, Milad Dehghanzadeh, Rui Bo, Kamal Al-Haddad

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a model predictive controller (MPC) is designed for a single-phase rectifier. The proposed MPC works with a continuous control set (CCS) that addresses variable switching issues in finite control set (FCS) MPCs. The observe-ability of the rectifier enables the design of a full-state observer to measure only output voltage in which the AC current of the rectifier is estimated. Both the proposed controller and observer are assessed with simulation studies and the results show the acceptable performance of the observer and CCS-MPC as well as good disturbance rejection in load and network parameter variations.

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Dipole-Moment-Based Reciprocity For Practical Desensitization Identification And Mitigation, Shengxuan Xia, Hanfeng Wang, Yansheng Wang, Zhonghua Wu, Chulsoon Hwang, Jun Fan Jan 2023

Dipole-Moment-Based Reciprocity For Practical Desensitization Identification And Mitigation, Shengxuan Xia, Hanfeng Wang, Yansheng Wang, Zhonghua Wu, Chulsoon Hwang, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

Radio frequency interference can degrade the receiving sensitivity of antennas. The interference is usually caused by certain coupling structures, such as layouts without adequate grounding for the radio frequency signal return path. Those structures can be modeled as a set of equivalent dipole moments when they are electrically small. Herein, the dipole moment model-based coupling framework is applied to a practical cellphone design case to devise an engineering solution. The coupling framework incorporates dipole moments as radiation sources and a coupling model based on the reciprocity theorem. Unfortunately, near-field scan probes often lack access to all locations, owing to the …

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Sample Considerations For Short-Circuited Filled Transmission Line Measurements, Jared Sinkey, Alexander Hook, Kristen M. Donnell Jan 2023

Sample Considerations For Short-Circuited Filled Transmission Line Measurements, Jared Sinkey, Alexander Hook, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Microwave materials characterization can be performed using a number of well-established measurement approaches. One such approach, the short-circuited rectangular waveguide (SC-RWG) filled transmission line approach, is known to have sample placement restrictions related to measurement reliability. This work focuses on this approach as a viable solution for microwave materials characterization of liquid materials and addresses the measurement restrictions within the context of sample length and dielectric properties. It is shown via simulation and measurement that samples of length greater than g/6 (where g is the wavelength in the RWG) do not have the reported measurement restrictions, nor do materials with …

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A Methodology For Predicting Acoustic Noise From Singing Capacitors In Mobile Devices, Xin Yan, Jianmin Zhang, Songping Wu, Ming Feng Xue, Chi Kin Benjamin Leung, Eric A. Macintosh, Daryl G. Beetner Jan 2023

A Methodology For Predicting Acoustic Noise From Singing Capacitors In Mobile Devices, Xin Yan, Jianmin Zhang, Songping Wu, Ming Feng Xue, Chi Kin Benjamin Leung, Eric A. Macintosh, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Multilayer ceramic capacitors (MLCCs) connected to a power distribution network (PDN) can create acoustic noise through a combination of the power rail noise at the MLCCs and the piezoelectric effect of the capacitor's ceramic material. The deformation of the MLCCs brought on by power supply noise creates vibrations which cause the printed circuit board (PCB) to vibrate and generate the audible acoustic noise. In the following paper, a simulation methodology is presented to analyze the acoustic noise created by MLCCs on a PCB. A simulation model for the PCB vibration modal response is built and the modal superposition method is …

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Distributed Detection Over Blockchain-Aided Internet Of Things In The Presence Of Attacks, Yiming Jiang, Jiangfan Zhang Jan 2023

Distributed Detection Over Blockchain-Aided Internet Of Things In The Presence Of Attacks, Yiming Jiang, Jiangfan Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

Distributed detection over a blockchain-aided Internet of Things (BIoT) network in the presence of attacks is considered, where the integrated blockchain is employed to secure data exchanges over the BIoT as well as data storage at the agents of the BIoT. We consider a general adversary model where attackers jointly exploit the vulnerability of IoT devices and that of the blockchain employed in the BIoT. The optimal attacking strategy which minimizes the Kullback-Leibler divergence is pursued. It can be shown that this optimization problem is nonconvex, and hence it is generally intractable to find the globally optimal solution to such …

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