Engineering Commons^™

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

Electrical and Computer Engineering Graduate Research

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

Underwater Nitrate Monitoring With Wireless Flexible Sensor Networks, Shah Zayed Riam

Electrical Engineering Theses

This study introduces a sophisticated sensor array engineered for comprehensive monitoring of water quality, thereby addressing the pressing need for effective environmental conservation and water resource management. The array encompasses sensors for nitrate, pH, and temperature, seamlessly integrated into a unified flexible platform capable of wireless data transmission for real-time monitoring applications. Employing potentiometric detection methods, the nitrate and pH sensors offer robust analytical capabilities, while the temperature sensor operates on resistive principles.

The nitrate sensor, constructed using a novel nanocomposite comprising poly(3-octyl-thiophene) (PoT) and molybdenum disulfide (MoS₂), exhibits a sensitivity of -50 mV against every decade change …

H-Nobs: Achieving Certified Fairness And Robustness In Distributed Learning On Heterogeneous Datasets, Guanqiang Zhou, Ping Xu, Yue Wang, Zhi Tian

Electrical and Computer Engineering Faculty Publications

Fairness and robustness are two important goals in the design of modern distributed learning systems. Despite a few prior works attempting to achieve both fairness and robustness, some key aspects of this direction remain underexplored. In this paper, we try to answer three largely unnoticed and unaddressed questions that are of paramount significance to this topic: (i) What makes jointly satisfying fairness and robustness difficult? (ii) Is it possible to establish theoretical guarantee for the dual property of fairness and robustness? (iii) How much does fairness have to sacrifice at the expense of robustness being incorporated into the system? To …

Towards Explainability Of Dimension Reduction Plots Of Unsupervised Learning Model Outcomes, Tony E.Astuhuaman Davila, Daniel B. Hier, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

Dimension reduction methods are used to visualize the output of unsupervised learning models when applied to complex data. These techniques improve interpretability by transforming a high-dimension space to a lower-dimension space (usually 2D or 3D). The results are typically viewed as 2D scatter plots, and class centroids may be added to increase interpretability. Although useful, the relationship of these class centroids to the underlying feature space remains opaque. The innovative aspect of this work is to create a strong link between the dimension-reduced space and the underlying high-dimension feature space by adding selected feature centroids to the 2D scatter plots. …

Vertical Interconnect Technology In Silicon, Package, And Printed Circuit Board (Pcb) With Coaxial Structure, Junyong Park, Chaofeng Li, Eddie Mok, Joe Dickson, Joan Tourne, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces vertical interconnect technology in silicon, package, and printed circuit board (PCB) levels with a coaxial structure, respectively. The coaxial structure has been known to be advantageous in terms of signal integrity (SI) compared to the non-coaxial structure. The coaxial structure is easy to control the characteristic impedance Z0 and robust to crosstalk. The silicon-level interconnect includes the wire bonding (WB) and through-silicon via (TSV) technology, the package-level interconnect includes an elastomer package test socket. The PCB-level interconnect includes the vias, and vertical conductive structure (VeCS). For each level, the non-coaxial and coaxial interconnects are compared with the …

Novel Formulation For Generalization Of Mixed-Mode S-Parameters For Coupled Differential High-Speed Digital Channels, Manish K. Mathew, Kevin Cai, Chaofeng Li, Mehdi Mousavi, Shameem Ahmed, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

As the demand for higher data rates intensifies, achieving accurate S-parameter calculation becomes increasingly critical. The conventional single-ended to mixed-mode S-parameter conversion formulation assumes uncoupled structures, which may not be true for high-speed digital channels. This work introduces a novel, generalized formulation for mixed-mode S-parameters and their corresponding transformation matrices [M1] and [M2], enabling comprehensive analysis of multi-pair coupled differential traces. An intra-pair crosstalk analysis of a tightly coupled strip line and microstrip line verifies and highlights the difference between the proposed and old formulations. A loosely coupled case is analyzed as an additional validation of the proposed formulation. Finally, …

Coupling-Informed Data-Driven Scheme For Joint Angle And Frequency Estimation In Uniform Linear Array With Mutual Coupling Present, Yanming Zhang, Wenchao Xu, A. Long Jin, Min Li, Peifeng Ma, Lijun Jiang, Steven Gao

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a novel coupling-informed data-driven algorithm tailored for the concurrent estimation of frequency and angle within a uniform linear array (ULA), while addressing the complicating influence of mutual coupling. Leveraging the hybrid dynamic mode decomposition (DMD) methodology, termed as averaged DMD, we incorporate moving average techniques to achieve effective denoising. The averaged DMD further decomposes the received signal into eigenvalues and corresponding eigenvectors. The frequency information is derived from the eigenvalues and the corresponding eigenvectors represent the steering vectors of sources. Subsequently, mutual coupling is informed into the calibration of the steering vector for each source. Specifically, the …

High-Speed Channel Simulator Using Neural Language Models, Hyunwook Park, Yifan Ding, Ling Zhang, Natalia Bondarenko, Hanqin Ye, Brice Achkir, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, high-speed channel simulators using neural language models are proposed. Given the input sequence of geometry design parameters of differential channels, the proposed channel simulator predicts SI characteristic sequences such as insertion loss (IL) and far-end crosstalk (FEXT). Sequence-to-sequence (seq2seq) networks using a recurrent neural network (RNN) and a long short-term memory (LSTM) are utilized for the estimator. Moreover, a transformer network which is a recent neural engine of large language models (LLMs) is introduced for the first time. Compared to seq2seq networks, the transformer network-based simulator can achieve shorter computing time due to its parallel computation called …

Experimental Study Of Pcb Vibration Induced By Mlcc Assembly Orientation And Process Variations, Yifan Ding, Ming Feng Xue, Jianmin Zhang, Xin Hua, Benjamin Leung, Eric A. Macintosh, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

The piezoelectric effect will cause the multilayer ceramic capacitor (MLCC) to deform in several directions. When it is soldered to the printed circuit board (PCB) and powered on, these deformations will exert a certain force on the PCB, causing the PCB to vibrate and emit acoustic noise at a certain frequency. Determining the dominant deformation direction that MLCC can affect the PCB is relevant and important for efficiently extracting the equivalent source of noise. This paper provides a method to determine the dominant deformation direction produced by MLCC, explores it through experimental measurement results, and finally provides a conclusion to …

Analytical Modeling Of Partially-Filled Tm010-Mode Dielectric Resonator For Accurate Dk And Df Extraction, Mehdi Mousavi, Chaofeng Li, Reza Asadi, Seyedmostafa Mousavi, Reza Vahdani, Xiaoning Ye, Mina Esmaeelpour, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

In high-speed printed circuit board (PCB) modeling, the accurate determination of the dielectric constant (DK) and dissipation factor (DF) is crucial for signal integrity analysis at design stage. This paper introduces an analytical approach using a partially filled TM010-mode dielectric resonator, an effective tool for DK and DF extraction of PCB material. We begin by discussing the theoretical underpinnings of TM₀₁₀-mode dielectric resonators and their applicability in measuring the DK and DF of the material under test. A mathematical model is then presented, linking the resonant characteristics directly to the DK and DF of the dielectric material. The …

Behavior Model Of A Multiphase Voltage Regulator Module With Rapid Voltage Drop Protection, Junho Joo, Hanyu Zhang, Hanfeng Wang, Wei Shen, Zhigang Liang, Lihui Cao, Seungtaek Jeong, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a modeling method of voltage regulator module (VRM) with rapid voltage drop protection is introduced. The proposed VRM model captures a pulse-width modulation scheme developed to counteract substantial load currents with high di/dt, resulting in a large voltage drop across the power delivery network (PDN). The equations to describe the non-linear behavior associated with the multiphase VRM behavior are proposed and successfully validated for both light and heavy loads, the latter being particularly crucial to trigger the voltage drop protection measures.

Graph Convolutional Neural Network Assisted Genetic Algorithm For Pdn Decap Optimization, Haran Manoharan, Jack Juang, Ling Zhang, Hanfeng Wang, Jingnan Pan, Kelvin Qiu, Xu Gao, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a hybrid algorithm combining reinforcement learning (RL) and a genetic algorithm (GA) for PDN decap optimization. The trained RL agent uses a graph convolutional neural network as a policy network and predicts the decap solution for a given PDN impedance and target impedance, which is seeded as an initial population to the GA. The trained RL agent is scalable regarding the number of decap ports. The main goal is to save computation time and find the near global minimum or global minimum. Generalization of the algorithm to different decap libraries is achieved through transfer learning, eventually reducing …

Lifelong Safe Optimal Adaptive Tracking Control Of Nonlinear Strict-Feedback Discrete-Time Systems, Behzad Farzanegan, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a comprehensive approach for achieving multi-task safe optimal adaptive tracking (MSOAT) for a class of nonlinear discrete-time systems, particularly those in strict-feedback form, utilizing a multi-layer neural network (MNN)-based framework. To begin, a cost function with a novel Barrier function (BF) term is introduced for each subsystem to address the weak safely reachable problem, serving as a crucial tool for guiding the system's trajectory toward the safe set while avoiding unwanted sets. To deal with the tracking problem, the Hamilton-Jacobi-Bellman (HJB) framework is used through the actor-critic MNN-based backstepping technique to estimate the solution of the value …

In-Plane And Out-Of-Plane 2-D Microdisplacement Sensor Based On A Single Microwave Resonator With Machine Learning, Shiyu Li, Osamah Alsalman, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Microwave displacement sensors have garnered significant research interest in recent years and have found successful applications in industrial automation and aerospace engineering. However, most microwave sensors are limited to measuring in-plane displacement, with the assumption that out-of-plane displacement remains constant during operation. In this work, we propose and experimentally demonstrate a novel concept for 2-D micro displacement sensing that simultaneously measures both in-plane and out-of-plane displacement. We developed a proof-of-concept sensor system based on a custom-made coaxial cable resonator (CCR) serving as the stator and a rubber-metal heterogeneous plate as the movable part. The in-plane and out-of-plane micromovements of the …

Empowering Urban Traffic Management: Elevated 3d Lidar For Data Collection And Advanced Object Detection Analysis, Nawfal Guefrachi, Hakim Ghazzai, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

The 3D object detection capabilities in urban environments have been enormously improved by recent developments in Light Detection and Range (LiDAR) technology. This paper presents a novel framework that transforms the detection and analysis of 3D objects in traffic scenarios by utilizing the power of elevated LiDAR sensors. We are presenting our methodology's remarkable capacity to collect complex 3D point cloud data, which allows us to accurately and in detail capture the dynamics of urban traffic. Due to the limitation in obtaining real-world traffic datasets, we utilize the simulator to generate 3D point cloud for specific scenarios. To support our …

Tightening Qc Relaxations Of Ac Optimal Power Flow Through Improved Linear Convex Envelopes, Mohammad Rasoul Narimani, Daniel K. Molzahn, Katherine R. Davis, Mariesa L. Crow

Electrical and Computer Engineering Faculty Research & Creative Works

AC optimal power flow (AC OPF) is a fundamental problem in power system operations. Accurately modeling the network physics via the AC power flow equations makes AC OPF a challenging nonconvex problem. To search for global optima, recent research has developed various convex relaxations that bound the optimal objective values of AC OPF problems. The QC relaxation convexifies the AC OPF problem by enclosing the non-convex terms within convex envelopes. The QC relaxation's accuracy strongly depends on the tightness of these envelopes. This paper proposes two improvements for tightening QC relaxations of OPF problems. We first consider a particular nonlinear …

Tilted Fiber Bragg Grating Sensors Based On Time-Domain Measurements With Microwave Photonics, Shiyu Li, Ruimin Jie, Osamah Alsalman, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Tilted fiber Bragg gratings (TFBGs) have garnered substantial research attention and have found widespread applications for sensing a diverse array of physical, chemical, and biological parameters based on optical spectrum measurements. The interrogation of a TFBG sensor typically requires a high-resolution bulky optical spectrum analyzer (OSA) due to the extremely narrow dips caused by the resonance of cladding modes. However, high-resolution OSAs can be costly and have limitations on measuring speed, limiting their practicality. In this paper, a new approach to interrogating TFBG sensors is proposed and experimentally demonstrated based on a microwave photonics technique. Instead of measuring the optical …

Simultaneous Frequency Regulation And Active Power Sharing In Islanded Microgrid Using Deep Reinforcement Learning, Oroghene Oboreh-Snapps, Sophia A. Strathman, Jonathan Saelens, Arnold Fernandes, Lauryn Morris, Praneeth Uddarraju, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a novel approach that integrates deep reinforcement learning (DRL) with the conventional virtual synchronous generator (VSG) to address dual objectives of microgrid (MG) control, frequency regulation and precise active power sharing. MGs typically consist of multiple Inverter-Based-Distributed-Generators (IBDGs) connected in parallel through different line impedances. The conventional active power loop (APL) of the VSG encounters significant steady-state frequency errors as load increases/decreases during islanded operation. To mitigate this issue, secondary-level controllers like proportional-integral (PI) control are added to the APL to regulate the frequency of IBDGs. However, PI control compromises power-sharing capabilities when the impedance values of …

Cascaded Weak Reflector Coaxial Cable Structure For Point And Distributed Large-Strain Sensing, Chen Zhu, Osamah Alsalman, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we present a truly distributed sensing modality based on a cascaded weak reflector coaxial cable structure (CWR-CCS) for large strain measurements. Compared to an optical fiber, a coaxial cable is much more robust and has a larger strain capability to survive harsh conditions, which may enable important applications in structural health monitoring. By drilling serial shallow holes into a commercial flexible coaxial cable perturbing the local impedance along its axial direction, CWRs along the coaxial cable are introduced due to impedance mismatch, forming the CWR-CCS. Gating a certain number of sequential reflectors in the time-domain reflection signal …

Segmented Fiber Optic Sensors Based On Hybrid Microwave-Photonic Interrogation, Wassana Naku, Osamah Alsalman, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we propose and demonstrate a novel concept of segmented fiber optic sensors by integrating the fiber Bragg grating (FBG) reflector modality and a hybrid interrogation technique enabled by microwave photonics. As a proof of concept, a radiofrequency Fabry-Perot interferometer (FPI) based on an optical fiber with two FBGs as the two reflectors of the Fabry-Perot (FP) cavity is constructed. By measuring the frequency response of the FPI device followed by a joint-time-frequency-domain analysis, the interferogram of the FPI in the microwave domain and the time-domain signal of the FBGs can be unambiguously reconstructed. Thus, the two elements …

A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes a new physics-assisted genetic algorithm (PAGA) for decoupling capacitor (decap) optimization in power distribution networks (PDNs), which is a highly efficient approach to minimizing the number of decaps within an enormous search space. In the proposed PAGA method, the priority of the decap ports is first determined based on their physical loop inductances. Then, an initial solution is quickly obtained by placing decaps sequentially on the port with the highest priority. Subsequently, a GA with prior physical knowledge is developed to find better decap solutions progressively. A port removal scheme that eliminates the low-priority ports and a …

Adaptive Resilient Control For A Class Of Nonlinear Distributed Parameter Systems With Actuator Faults, Hasan Ferdowsi, Jia Cai, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a new model-based fault resilient control scheme for a class of nonlinear distributed parameter systems (DPS) represented by parabolic partial differential equations (PDE) in the presence of actuator faults. A Luenberger-like observer on the basis of nonlinear PDE representation of DPS is developed with boundary measurements. A detection residual is generated by taking the difference between the measured output of the DPS and the estimated one given by the observer. Once a fault is detected, an unknown actuator fault parameter vector together with a known basis function is utilized to adaptively estimate the fault dynamics. A novel …

Multimode Fiber-Based Interferometric Sensors With Microwave Photonics, Chen Zhu, Shuaifei Tian, Lingmei Ma, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Interferometry is one of the most widely used investigative techniques in various fields. With the implementation of interferometry on optical fibers, fiber optic interferometers (FOIs) have gained tremendous growth and advancement in the past four decades and have been explored for measurements of a diverse array of physical, chemical, and biological parameters. FOIs are typically constructed using single-mode fibers (SMFs) and are interrogated in the optical domain using probing light with a tightly controlled state of polarization (SOP), to ensure high-quality interference signals that facilitate sensing applications. The stringent requirement on the single-mode operation, as well as SOP, has hindered …

Enhanced Sensitivity And Robustness In An Embeddable Strain Sensor Using Microwave Resonators, Yan Tang, Yizheng Chen, Qi Zhang, Biyao Shi, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Introduces A Novel, Cost-Effective, And Durable Strain Sensor With Exceptional Sensitivity And Resolution, Utilizing An Open-Ended Hollow Coaxial Cable Resonator (OE-HCCR). The OE-HCCR Is Characterized By Two Reflective Elements: A Metal Post That Connects The Inner And Outer Conductors At The Signal's Entrance, And A Terminal Flange Near The Coaxial Line's End, Establishing A Variable Gap. The Sensor Employs A Paired Anchor Ring In Conjunction With The Terminal Flange To Transduce And Direct Strain. Variations In The Gap Alter The Resonant Frequency By Modulating The Phase Of The Reflection Coefficient At The Cable's Terminus. Initial Calibration Revealed A …

Investigation Of Intermodal Four-Wave Mixing For Continuous-Wave Photon-Pair Generation, Seyedehnajmeh Montazeri, Md Abu Zobair, Mina Esmaeelpour

Electrical and Computer Engineering Faculty Research & Creative Works

We Experimentally Demonstrate the Various Intermodal and Intramodal Four-Wave Mixing Processes in a Few-Mode Fiber with Three Modes using Non-Degenerate Pumps. We Distinguish the Processes by Calculating their Phase Mismatch and Identify the Intermodal Spontaneous Four-Wave Mixing Process that Generates Entangled Photon Pairs in Various Modes. We Achieve This using Continuous-Wave Beams and the Seeding Technique Due to the Low Efficiency of the Spontaneous Four-Wave Mixing Effect in the Fiber. We Seeded the Stokes and Anti-Stokes Waves and Measured the Spectral Content of Each Mode While Moving the Seed Away from the Perfect Phase-Matched Condition in the Fiber under Test. …

A Robust Demand Regulation Strategy For Ders In A Single-Controllable Active Distribution Network, Shah Fahad, Arman Goudarzi, Rui Bo, Muhammad Waseem, Rashid Al-Ammari, Atif Iqbal

Electrical and Computer Engineering Faculty Research & Creative Works

Over the past decade, pq regulation schemes for a single-controllable active distribution network (adn) using coordination among a network of virtual synchronous generators (vsgs) have been proposed. However, considering the variable nature of intermittent renewable energy sources (iress), coupling a cluster of iress with the point of common coupling (pcc) of adn could inflict transient issues for the power management of the whole adn. To counter these challenges, the proposed study has three main objectives: 1) to propose a modified mathematical model that represents the apparent resistance-reactance at the pcc of adn in relation to the pq coordination among the …

Energy Efficiency In Additive Manufacturing: Condensed Review, Ismail Fidan, Vivekanand Naikwadi, Suhas Alkunte, Roshan Mishra, Khalid Tantawi

Engineering Technology Faculty Publications

Today, it is significant that the use of additive manufacturing (AM) has growing in almost every aspect of the daily life. A high number of sectors are adapting and implementing this revolutionary production technology in their domain to increase production volumes, reduce the cost of production, fabricate light weight and complex parts in a short period of time, and respond to the manufacturing needs of customers. It is clear that the AM technologies consume energy to complete the production tasks of each part. Therefore, it is imperative to know the impact of energy efficiency in order to economically and properly …

Federated Learning: Overview, Strategies, Applications, Tools And Future Directions, Betul Yurdem, Murat Kuzlu, Mehmet Kemal Gullu, Maliha Tabassum

Engineering Technology Faculty Publications

Federated learning (FL) is a distributed machine learning process, which allows multiple nodes to work together to train a shared model without exchanging raw data. It offers several key advantages, such as data privacy, security, efficiency, and scalability, by keeping data local and only exchanging model updates through the communication network. This review paper provides a comprehensive overview of federated learning, including its principles, strategies, applications, and tools along with opportunities, challenges, and future research directions. The findings of this paper emphasize that federated learning strategies can significantly help overcome privacy and confidentiality concerns, particularly for high-risk applications.

A Chinese Power Text Classification Algorithm Based On Deep Active Learning, Song Deng, Qianliang Li, Renjie Dai, Siming Wei, Di Wu, Yi He, Xindong Wu

Computer Science Faculty Publications

The construction of knowledge graph is beneficial for grid production, electrical safety protection, fault diagnosis and traceability in an observable and controllable way. Highly-precision text classification algorithm is crucial to build a professional knowledge graph in power system. Unfortunately, there are a large number of poorly described and specialized texts in the power business system, and the amount of data containing valid labels in these texts is low. This will bring great challenges to improve the precision of text classification models. To offset the gap, we propose a classification algorithm for Chinese text in the power system based on deep …

Mosaic: A Prune-And-Assemble Approach For Efficient Model Pruning In Privacy-Preserving Deep Learning, Yifei Cai, Qiao Zhang, Rui Ning, Chunsheng Xin, Hongyi Wu

Computer Science Faculty Publications

To enable common users to capitalize on the power of deep learning, Machine Learning as a Service (MLaaS) has been proposed in the literature, which opens powerful deep learning models of service providers to the public. To protect the data privacy of end users, as well as the model privacy of the server, several state-of-the-art privacy-preserving MLaaS frameworks have also been proposed. Nevertheless, despite the exquisite design of these frameworks to enhance computation efficiency, the computational cost remains expensive for practical applications. To improve the computation efficiency of deep learning (DL) models, model pruning has been adopted as a strategic …