Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

2025

Discipline
Institution
Keyword
Publication
Publication Type
File Type

Articles 7621 - 7650 of 8603

Full-Text Articles in Engineering

Data Representation And Preprocessing Effects On S-Parameter Modeling Of High-Speed Channels Using Machine Learning, Hyunwook Park, Davit Kharshiladze, Yifan Ding, Ling Zhang, Natalia Bondarenko, Hanqin Ye, Kaushal Sanjay Mhalgi, Brice Achkir, Chulsoon Hwang Jan 2025

Data Representation And Preprocessing Effects On S-Parameter Modeling Of High-Speed Channels Using Machine Learning, Hyunwook Park, Davit Kharshiladze, Yifan Ding, Ling Zhang, Natalia Bondarenko, Hanqin Ye, Kaushal Sanjay Mhalgi, Brice Achkir, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the effects of data representations and preprocessing on machine learning based S-parameter modeling of high-speed channels are investigated. Using a transformer network as a base model, two S-parameter representations in real/imaginary and magnitude/phase are compared and studied. Considering S-parameter data distributions, various preprocessing techniques including MinMax normalization, standardization, robust scaling, power transformation, and quantile transformation are compared and analyzed to improve accuracy. Moreover, the accuracy results are compared depending on the electrical length of target channels.

Go to article

Obstacles And Mitigations For An Accurate Low Impedance, Low Frequency Measurement, Faye Squires, Yifan Ding, Matthew Doyle, Matteo Cocchini, Samuel Connor, Francesco De Paulis, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang Jan 2025

Obstacles And Mitigations For An Accurate Low Impedance, Low Frequency Measurement, Faye Squires, Yifan Ding, Matthew Doyle, Matteo Cocchini, Samuel Connor, Francesco De Paulis, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

The two-port shunt configuration is often heralded as the gold standard for low-impedance measurements. However, this measurement method is not without its own issues. The shunt configuration inherently creates a ground loop between the measurement device's reference plane and the reference of the device under test (DUT). Additionally, probes often must be oriented in such a way that allows inductive coupling to occur. This work uses microprobes to measure the shunt impedance of a non-ideal short to explore the limitations of this measurement method in terms of both frequency and impedance. It highlights the importance of ground loop isolation and …

Go to article

Multi-Objective Inverse Optimization Of High-Speed Interconnects Using Cascaded Deep Neural Network, Yicheng Zhang, Ling Zhang, Hyunwook Park, Bo Pu, Xiao Ding Cai, Chulsoon Hwang, Bidyut Sen, Jun Fan, Er Ping Li, James L. Drewniak Jan 2025

Multi-Objective Inverse Optimization Of High-Speed Interconnects Using Cascaded Deep Neural Network, Yicheng Zhang, Ling Zhang, Hyunwook Park, Bo Pu, Xiao Ding Cai, Chulsoon Hwang, Bidyut Sen, Jun Fan, Er Ping Li, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a novel multi-objective inverse optimization method for high-speed interconnects based on a cascaded deep neural network (DNN) structure, which can efficiently optimize characteristic impedance, insertion loss, and far-end crosstalk (FEXT) simultaneously. Parameter optimization for high-speed interconnects is essential to the signal integrity and electrical performance of complex designs such as multilayer printed circuit boards (PCBs) and chiplets. Conventional optimization approaches often rely on numerous optimization iterations, which is highly time-consuming, especially in high dimensional parameter spaces. This paper proposes a novel DNN based method by cascading an inverse-prediction network and a forward-prediction network to achieve multi-objective optimization …

Go to article

Differential Via Modeling Using Multilayer Perceptron-Sequential (Mlp-Seq) Neural Network, Hyunwook Park, Shruti Sawant, Bandi Sathvika, Arun Chada, Soumya Singh, Seema Pk, Taein Shin, Haeseok Suh, Junyong Park, Bhyrav Mutnury, Donghyun Kim Jan 2025

Differential Via Modeling Using Multilayer Perceptron-Sequential (Mlp-Seq) Neural Network, Hyunwook Park, Shruti Sawant, Bandi Sathvika, Arun Chada, Soumya Singh, Seema Pk, Taein Shin, Haeseok Suh, Junyong Park, Bhyrav Mutnury, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an encoder-decoder structured multi-layer perceptron-sequential (MLP-SEQ) networks are proposed to model high-speed differential vias for estimating differential insertion loss (IL) and return loss (RL). Sequential neural networks including recurrent neural network (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU) are introduced as the decoder NN to treat frequency responses as sequences. The proposed models are validated by finite element method (FEM) simulation results. The accuracy and training times of MLP-RNN, MLP-LSTM, and MLP-GRU models are compared and analyzed. Based on the MLP-LSTM model, various design of experiments (DoEs) are conducted to enhance the reproducibility and …

Go to article

Coupling Path Analysis Of Data Center Ssd Storage Systems Based On Visualization Technique, Xiangrui Su, Haran Manoharan, Jihun Kim, Lalit Kumar, Heewon Kang, Chunghyun Ryu, Chulsoon Hwang Jan 2025

Coupling Path Analysis Of Data Center Ssd Storage Systems Based On Visualization Technique, Xiangrui Su, Haran Manoharan, Jihun Kim, Lalit Kumar, Heewon Kang, Chunghyun Ryu, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Electrostatic discharge (ESD) is a major source of electromagnetic interference, capable of causing damage, malfunctions, or disruptions in electronic devices. As a result, ESD immunity testing is a critical component of electromagnetic compatibility (EMC) standards. In this study, the radiation emitted from the ESD gun body over 2 GHz is characterized and modeled using Huygens' principle. The equivalent field source was validated across three different environments, demonstrating accuracy with errors of less than 10 dB. A coupling path visualization technique was then employed to identify critical coupling paths, providing guidance for the strategic placement of absorbers. Simulation results showed that …

Go to article

Characterization And Full-Wave Modeling Of Corona Discharge Induced Coupling To Touchscreen Displays, Zhekun Peng, Shubhankar Marathe, Javad Meiguni, Ali Foudazi, Jianchi Zhou, Li Shen, Viswa Pilla, Cheung Wei Lam, Donghyun Kim, David Pommerenke, Daryl G. Beetner Jan 2025

Characterization And Full-Wave Modeling Of Corona Discharge Induced Coupling To Touchscreen Displays, Zhekun Peng, Shubhankar Marathe, Javad Meiguni, Ali Foudazi, Jianchi Zhou, Li Shen, Viswa Pilla, Cheung Wei Lam, Donghyun Kim, David Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

An electrostatic discharge (ESD) to the glass of a touchscreen display can damage capacitive touch sensor circuitry and traces. The ESD creates a sparkless corona discharge on the glass surface, which couples to sense patches on the other side of the glass. Currents induced on sense traces during the corona discharge are measured in an evaluation setup, which resembles the touchscreen design. Waveforms for current induced at different distances from the discharge position are recorded and compared. The induced currents are analyzed by their peak value and the total charge or energy delivered to the sense trace for different discharge …

Go to article

Structural Analysis Of Multi-Domain Dynamic Systems Modeled Via Bond Graphs, Arnold A. Fernandes, Jonathan W. Kimball Jan 2025

Structural Analysis Of Multi-Domain Dynamic Systems Modeled Via Bond Graphs, Arnold A. Fernandes, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

Structural Observability (SO) and Structural Monitorability (SM) are structural properties utilized to determine the state and fault-free operation of components, respectively, in a bond graph (BG) model. BGs enable qualitative system analysis, evaluating whether existing sets of sensors and actuators ensure Structural Observability (SO) and Structural Controllability (SC) without knowledge of parametric values. Furthermore, the analysis determines whether there are sufficient sensors available to identify component faults accurately. This work provides a framework for automated sensor placement in a multi-domain physical system while analyzing the SO and SM properties. The MATLAB Structural Analysis Toolbox (MATSAT) conducts sensor placement in a …

Go to article

Ethics Vs.. Regulation: Converging Frameworks For Trustworthy Human-Centered Ai In Biomedical Research, Tayo Obafemi-Ajayi, Tiffani J. Bright, Emily F. Wong, Donald Wunsch, Joan Peckham, Jason H. Moore Jan 2025

Ethics Vs.. Regulation: Converging Frameworks For Trustworthy Human-Centered Ai In Biomedical Research, Tayo Obafemi-Ajayi, Tiffani J. Bright, Emily F. Wong, Donald Wunsch, Joan Peckham, Jason H. Moore

Electrical and Computer Engineering Faculty Research & Creative Works

The accelerating impact of AI in biomedical research is driving significant advances in precision medicine. As these systems increasingly shape health outcomes, the imperative to develop trustworthy, reliable, and ethically grounded AI becomes more pressing, particularly in addressing concerns related to data integrity, patient safety, and equitable outcomes. While the potential of AI to transform biomedical research is clear, its responsible integration depends on more than technological capability. Ensuring that these systems are aligned with societal values requires a dual commitment: the operationalization of ethical principles throughout the AI life cycle and the establishment of robust regulatory mechanisms. Ethics provides …

Go to article

Honey-Reram Enabled Sustainable Edge Ai System For Iot Applications, Jinhui Wang, Feng Zhao, Mohammad Rafeeq Khan, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru Jan 2025

Honey-Reram Enabled Sustainable Edge Ai System For Iot Applications, Jinhui Wang, Feng Zhao, Mohammad Rafeeq Khan, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru

Electrical and Computer Engineering Faculty Research & Creative Works

This paper is toward a promising solution to address the environmental sustainability challenge in computing by building brain-inspired and green non-Von Neumann systems with Resistive Random-Access Memory (ReRAM) made from natural organic materials, honey, for energy-efficient operation, renewable material resources, sustainable device manufacturing, and environmentally-friendly disposal. In this paper, honey-ReRAM and its arrays are firstly manufactured and tested. The resistance modulation mechanism of honey-ReRAM is analyzed and investigated. Then a Computing-in-Memory (CIM) architecture based on honey-ReRAM for edge AI and IoT applications is proposed and evaluated. The experimental results indicate that the proposed edge AI systems with the VGG8 and …

Go to article

Spin Mechanisms In Gd-Doped Gan Implanted With Oxygen Carbon At Room Temperature, Vishal Saravade, Amirhossein Ghods, Chuanle Zhou, Ian Ferguson Jan 2025

Spin Mechanisms In Gd-Doped Gan Implanted With Oxygen Carbon At Room Temperature, Vishal Saravade, Amirhossein Ghods, Chuanle Zhou, Ian Ferguson

Electrical and Computer Engineering Faculty Research & Creative Works

Gadolinium-doped gallium nitride implanted with oxygen and carbon show carrier-mediated spin mechanisms at room temperature. As-grown Gd-doped GaN grown by metal-organic chemical vapor deposition using a tris(cyclopentadienyl) gadolinium precursor shows Ordinary Hall Effect and no ferromagnetism at room temperature. Upon O or C implantation in Gd-doped GaN, Anomalous Hall Effect that is indicative of carrier-mediated spin and ferromagnetism is observed. A good crystal quality is maintained even after implantation. O and C favor interstitial sites and occupy deep-level acceptor-type states in Gd-doped GaN. Room-temperature spin and ferromagnetism that is induced by gadolinium in Gd-doped GaN is activated by O and …

Go to article

Sift Feature-Based Relative Altitude Estimation Enhanced With Siamese Network, Shirin Nasr-Esfahani, S. Jagannathan Jan 2025

Sift Feature-Based Relative Altitude Estimation Enhanced With Siamese Network, Shirin Nasr-Esfahani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In GPS-denied environments or when GPS signals are unreliable or unavailable, alternative methods of accurate localization with coordinate generation become critical. To address localization, the scale-invariant feature transform (SIFT) algorithm, along with its numerous adaptations, is extensively utilized in computer vision and remote sensing for matching image features to identify objects and perform localization. This article presents a novel approach for estimating the relative altitude of unmanned aerial vehicles (UAVs) using SIFT features' scale (size), omitting the need for additional data like camera intrinsic parameters, as well as extensive image datasets are also required for training. Furthermore, the approach enhances …

Go to article

Quality Factor Estimation Of Additively Manufactured Frequency Selective Surfaces Via Active Microwave Thermography, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Doyle T. Motes, Cody Morrow, Kristen M. Donnell Jan 2025

Quality Factor Estimation Of Additively Manufactured Frequency Selective Surfaces Via Active Microwave Thermography, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Doyle T. Motes, Cody Morrow, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Additive manufacturing (AM) has increased in popularity in recent years due to improvements in efficiency over traditional manufacturing methods. Furthermore, the availability of electrically conductive fused deposition modeling (FDM) filaments has opened the door to the manufacture of conductive structures, including frequency selective surfaces (FSSs). Traditionally, the performance of an FSS is verified experimentally through electromagnetic (EM) measurement of the FSS's reflection and/or transmission response. However, this verification approach is not ideal for rapid, in situ inspections due to the time-consuming measurement process, expensive and complicated equipment, and difficult to interpret results. To this end, active microwave thermography (AMT), a …

Go to article

Enhanced Multidimensional Harmonic Retrieval In Mimo Wireless Channel Sounding, Yanming Zhang, Wenchao Xu, A. Long Jin, Tianquan Tang, Min Li, Peifeng Ma, Lijun Jiang, Steven Gao Jan 2025

Enhanced Multidimensional Harmonic Retrieval In Mimo Wireless Channel Sounding, Yanming Zhang, Wenchao Xu, A. Long Jin, Tianquan Tang, Min Li, Peifeng Ma, Lijun Jiang, Steven Gao

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces a recursive parallel dynamic mode decomposition (RPDMD) scheme tailored for multidimensional harmonic retrieval (MHR), specifically applied to MIMO wireless channel sounding. The RPDMD algorithm is devised to address the complexities inherent in multidimensional scenarios, leveraging the dynamic mode decomposition (DMD) framework within a recursive parallel structure. Initially, the observed tensorial multidimensional harmonic data is transformed into a two-dimensional matrix format along the r-th dimension. Subsequently, DMD dissects this matrix data into eigenvalues and their associated modes. The real and imaginary components of the DMD eigenvalues yield damping factors and frequencies in the r-th dimension, respectively. Furthermore, recursive …

Go to article

A Low-Frequency-Stable Higher-Order Isogeometric Discretization Of The Augmented Electric Field Integral Equation, Maximilian Nolte, Riccardo Torchio, Sebastian Schöps, Jürgen Dölz, Felix Wolf, Albert E. Ruehli Jan 2025

A Low-Frequency-Stable Higher-Order Isogeometric Discretization Of The Augmented Electric Field Integral Equation, Maximilian Nolte, Riccardo Torchio, Sebastian Schöps, Jürgen Dölz, Felix Wolf, Albert E. Ruehli

Electrical and Computer Engineering Faculty Research & Creative Works

This contribution investigates the connection between Iso geometric analysis (IGA) and integral equation (IE) methods for full-wave electromagnetic problems up to the low-frequency limit. The proposed spline-based IE method allows for an exact representation of the model geometry described in terms of nonuniform rational B-splines (NURBS) without meshing. This is particularly useful when high accuracy is required or when meshing is cumbersome, for instance, during the optimization of electric components. The augmented electric field IE (EFIE) is adopted, and the deflation method is applied, so the low-frequency breakdown is avoided. The extension to higher-order basis functions is analyzed and the …

Go to article

Component Level Em Emission Assessment And Management For Rf Desensitization, Xiangrui Su, Wenchang Huang, Junghee Cho, Joonki Paek, Chulsoon Hwang Jan 2025

Component Level Em Emission Assessment And Management For Rf Desensitization, Xiangrui Su, Wenchang Huang, Junghee Cho, Joonki Paek, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Radio frequency (RF) desensitization is a common issue caused by high-speed components in modern electronic devices. Consequently, numerous studies have focused on characterizing and quantifying electromagnetic (EM) emission sources by using near field scanning to detect EM noise sources. However, before near field scanning, no predetermined threshold is available to quickly assess whether an EM noise source will pose RF desensitization risks in the receiving antenna. This article presents a method to optimize near field scanning settings through EM emission management analysis. Drawing on experience from numerous EM emission studies, we introduce an EM emission management procedure for two common …

Go to article

Discrimination Of Temperature And Strain By Characterizing Two Femtosecond Laser-Written Coincident Sapphire Fiber Bragg Gratings For Harsh Environment Applications, Farhan Mumtaz, Bohong Zhang, Koustav Dey, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang Jan 2025

Discrimination Of Temperature And Strain By Characterizing Two Femtosecond Laser-Written Coincident Sapphire Fiber Bragg Gratings For Harsh Environment Applications, Farhan Mumtaz, Bohong Zhang, Koustav Dey, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In this study, two co-incident sapphire fiber Bragg gratings (SFBGs) were successfully inscribed utilizing a femtosecond (fs) laser to achieve a high fringe contrast interferogram. These two SFBGs employ a unique configuration, one parallel to the center axis, called p-SFBG, and the other forming an angle from the center-axis, called a-SFBG, allowing for simultaneous strain and temperature measurements with low crosstalk. As a proof of concept, p-SFBG and a-SFBG using line-by-line method are characterized, which are shorter in length (i.e., 1.5 mm), producing reflectivity of ~3dB. This effort demonstrates the use of two coincident SFBGs forming an angle of 2.29° …

Go to article

Simultaneous Measurement Of Early-Stage Corrosion And Strain Levels In Steel Rebar Based On Graphene Oxide-Coated Ncf-Fbg Fiber Optic Sensor, Fujian Tang, Baihe Qu, Hong Nan Li, Jie Huang Jan 2025

Simultaneous Measurement Of Early-Stage Corrosion And Strain Levels In Steel Rebar Based On Graphene Oxide-Coated Ncf-Fbg Fiber Optic Sensor, Fujian Tang, Baihe Qu, Hong Nan Li, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Rebar corrosion significantly reduces the lifespan of reinforced concrete structures. The value of rebar strain, especially for some key structural components, indicates the safety margin of structures. In this study, a graphene oxide (GO) coated no-core fiber-fiber Bragg grating (NCF-FBG) fiber optic sensor is proposed for simultaneously measuring strain values and early-stage corrosion of steel rebar for the first time. The impact of GO coating thickness on the monitoring sensitivity is considered. A setup was manufactured to simultaneously perform tension, optical, and corrosion tests. The strain was applied up to 1200 μϵ. The rebar corrosion was assessed using electrochemical method …

Go to article

Safe Optimal Control Of Quadrotor Formations Using Multilayer Neural Networks And Continual Learning, Ehsan Soleimani, Irfan Ahmad Ganie, S. Jagannathan Jan 2025

Safe Optimal Control Of Quadrotor Formations Using Multilayer Neural Networks And Continual Learning, Ehsan Soleimani, Irfan Ahmad Ganie, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents an integral reinforcement learning-based optimal formation tracking scheme for multiple quadrotors unmanned aerial vehicles (QUAVs) experiencing nonlinear coupled dynamics and subject to constraints. We use multilayer neural networks (MNN) within an actor-critic framework where the MNN weights are tuned using singular value decomposition (SVD) of the activation function gradient to approximate optimal control policy via backstepping. Additionally, barrier Lyapunov functions (BLF) are introduced to ensure set invariance, thereby maintaining the quadrotors within a defined safety space due to constraints. A novel weight update law for each layer is derived using the HJB approximation error and control input …

Go to article

Explainable And Safety Aware Deep Reinforcement Learning-Based Control Of Nonlinear Discrete-Time Systems Using Neural Network Gradient Decomposition, Behzad Farzanegan, S. Jagannathan Jan 2025

Explainable And Safety Aware Deep Reinforcement Learning-Based Control Of Nonlinear Discrete-Time Systems Using Neural Network Gradient Decomposition, Behzad Farzanegan, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents an explainable deep-reinforcement learning (DRL)-based safety-aware optimal adaptive tracking (SOAT) scheme for a class of nonlinear discrete-time (DT) affine systems subject to state inequality constraints. The DRL-based SOAT utilizes a multilayer neural network (MNN)-based actor-critic to estimate the cost function and optimal policy while the MNN update laws are tuned both using the singular value decomposition (SVD) of activation function gradient in order to mitigate the vanishing gradient issue and safety-aware Bellman error at each layer. An approximate safety-aware optimal policy is developed using Karush–Kuhn–Tucker (KKT) conditions by incorporating the higher-order control barrier function (HOCBF) into the …

Go to article

Adaptive Nussbaum Design For Nonholonomic Systems With Asymptotic Stabilization Against False Data Injection, Guilong Liu, Yongliang Yang, Weinan Gao, Donald C. Wunsch Jan 2025

Adaptive Nussbaum Design For Nonholonomic Systems With Asymptotic Stabilization Against False Data Injection, Guilong Liu, Yongliang Yang, Weinan Gao, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article addresses the stabilization challenges of nonholonomic systems under the threat of false data injection (FDI) attacks, which compromise the integrity of state information. A novel adaptive control strategy using Nussbaum-type gains is proposed to ensure the asymptotic stability of the closed-loop system while maintaining signal boundedness. The approach extends conventional Nussbaum designs to handle multiple unknown control directions. It integrates online learning mechanisms to mitigate the impact of FDI attacks. Additionally, adaptive backstepping and fuzzy-logic systems are utilized to approximate and compensate for unknown nonlinear dynamics. The methodology transforms nonholonomic systems into equivalent cascade structures to address inherent …

Go to article

An Extensive Analysis Of Match-Tracking Methods For Artmap, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch Jan 2025

An Extensive Analysis Of Match-Tracking Methods For Artmap, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This paper identifies and studies five match-tracking (MT) methods in the adaptive resonance theory (ART) literature and conducts a detailed comparative analysis of these in ARTMAP applications. We focus on model performance for each MT method with respect to time and space efficiency as well as classification accuracy. Experimental results indicate that one MT variant, used in ARTMAP applications for the first time in this work, provides significant improvements in computational efficiency: depending on the ARTMAP variant, it was able to achieve up to one order of magnitude reduction in both time and space requirements, albeit with a compromise in …

Go to article

Active And Reactive Power Flow Control Of The Dual Active Bridge Converter, Lauryn Morris, Thomas W. Francois, Jonathan Saelens, Oroghene Oboreh-Snapps, Arnold Fernandes, Praneeth Uddarraju, Sophia A. Strathman, Jonathan W. Kimball Jan 2025

Active And Reactive Power Flow Control Of The Dual Active Bridge Converter, Lauryn Morris, Thomas W. Francois, Jonathan Saelens, Oroghene Oboreh-Snapps, Arnold Fernandes, Praneeth Uddarraju, Sophia A. Strathman, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

The Dual Active Bridge (DAB) is a reliable and efficient converter capable of providing bi-directional power transfer and galvanic isolation. An ac-ac DAB can control both active and reactive power flow. The present work introduces a combined feedback/feed-forward current control system, utilizing the calculated and measured converter currents translated into the dq reference frame, to control the output power. The system was simulated in PLECS to demonstrate the control algorithm's ability to track the dq currents and provide the necessary output power.

Go to article

Print Quality Assessment Of Additively Manufactured Resonant Structures, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Cody Morrow, Doyle T. Motes, Kristen M. Donnell Jan 2025

Print Quality Assessment Of Additively Manufactured Resonant Structures, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Cody Morrow, Doyle T. Motes, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Due to the increased popularity of additive manufacturing (AM) and availability of electrically conductive filaments, the potential for using AM to fabricate high frequency resonant structures has been realized. As these structures require specific operating conditions to provide the desired resonant response (such as substrate/superstrate material, operating frequency, polarization, etc.), print quality validation through an assessment of the resonant response can be difficult to accomplish. To this end, active microwave thermography (AMT) is proposed as an alternative technique to assess and validate an AM resonant structure. Two AM resonant structures were manufactured using fused deposition modeling (FDM) and the resonant …

Go to article

Training Neural Networks With A Self-Adaptive Ant Colony Algorithm, Ashraf M. Abdelbar, Donald C. Wunsch Jan 2025

Training Neural Networks With A Self-Adaptive Ant Colony Algorithm, Ashraf M. Abdelbar, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

ACOR is a well-established ant colony optimization algorithm that has been applied to neural network training. We present an approach for the dynamic adaptation of the ACOR algorithm's search intensification/diversification parameter q, based on using several pre-specified parameter configurations, which we call personalities. Before an ant begins to generate a candidate solution, it stochastically adopts a personality based on the relative past success of the different personalities. The success of a personality is measured, in turn, by the relative quality of previous solutions generated by ants adopting that personality. The premise of our approach is that some personalities will be …

Go to article

Design And Numerical Investigation Of Surface Plasmon Resonance–Based Refractive Index Sensor, Inamullah Sario, Ghulam Abbas Lashari, Abdul Aziz Memon, Farhan Mumtaz Jan 2025

Design And Numerical Investigation Of Surface Plasmon Resonance–Based Refractive Index Sensor, Inamullah Sario, Ghulam Abbas Lashari, Abdul Aziz Memon, Farhan Mumtaz

Electrical and Computer Engineering Faculty Research & Creative Works

A photonic crystal fiber–surface plasmon resonance (PCF-SPR)-based refractive index (RI) sensor with a novel design is presented in this paper. This sensor detects the anomalies in the sample analyte by detecting the change in its RI. Silver (Ag) is used as a plasmonic material with a unique terracotta structure to sense the RI variations in the surrounding medium, also called an analyte or sample. A thin layer of titanium dioxide (TiO2) measuring 10 nm is applied on top of the plasmonic material to prevent the oxidation of silver. The designed sensor detected a good range of analyte RI from 1.31 …

Go to article

High-Frequency Accurate Dual-Side Equivalent Circuit Model For Transformers, Reza Vahdani, Junyong Park, Manish Kizhakkeveettil Mathew, Zhekun Peng, Chiuk Song, Hyucksu Kweon, Jiang Lijun, Donghyun Kim Jan 2025

High-Frequency Accurate Dual-Side Equivalent Circuit Model For Transformers, Reza Vahdani, Junyong Park, Manish Kizhakkeveettil Mathew, Zhekun Peng, Chiuk Song, Hyucksu Kweon, Jiang Lijun, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This study delves into the modeling of a transformer in the frequency range of 100 KHz to 30 MHZ. The coupling coefficient was considered as a function of leakage and self-inductance and incorporated in the optimization process of transformer modeling in the proposed method. The equivalent circuit focused on the critical aspects of leakage inductance, parasitic capacitance, and winding effects. At first, the winding effect of an air-core inductor over wide frequency range with both single-layer and double-layer windings was shown. Then an equivalent circuit was proposed to model a transformer over this frequency range. The comparison between the measured …

Go to article

Effects Of Chain Length, Saturation, And Bases On Saponification, Sarah Fenik Jan 2025

Effects Of Chain Length, Saturation, And Bases On Saponification, Sarah Fenik

Williams Honors College, Honors Research Projects

This project will analyze the effects of chain length and saturation of fatty acids on saponification processes, as well as the effects of the base used in the reaction. Stearic acid, lauric acid, and oleic acid will be used for the fatty acid comparisons, and sodium hydroxide and potassium hydroxide will be used for the base comparisons. Stearic acid is considered a long chain fatty acid, while lauric acid is considered a short chain fatty acid. Oleic acid is a monounsaturated fatty acid. Five soap products are be made: sodium stearate, sodium laurate, sodium oleate, potassium stearate, and potassium oleate. …

Go to article

Anti-Icing Properties Of 3d-Printed Superhydrophobic Surfaces, Nathan Kling Jan 2025

Anti-Icing Properties Of 3d-Printed Superhydrophobic Surfaces, Nathan Kling

Williams Honors College, Honors Research Projects

This project aims to investigate how textured microscopic surfaces can reduce ice adhesion, utilizing 3D-printed resin materials. By varying the size and shape of these surface imperfections, the research seeks to identify configurations that minimize ice formation and facilitate easier ice removal. The trapped air between the imperfections is expected to hinder water droplet adhesion, promoting detachment through gravity or motion. The study’s applications could extend to preventing icing on power lines, roads, and aircraft. Methodologically, the project will build on prior research, applying water to textured surfaces under controlled temperature conditions to assess ice formation and removal efficiency. Key …

Go to article

Corrosion Of Pipes In Soil Under Cathodic Protection, Ashley Chow Jan 2025

Corrosion Of Pipes In Soil Under Cathodic Protection, Ashley Chow

Williams Honors College, Honors Research Projects

This research project focuses on understanding how various soil properties affect the corrosion of buried pipelines that are protected by cathodic protection (CP) systems. Specifically, the study seeks to evaluate key soil characteristics, including resistivity, moisture content, and pH levels to determine their influence on the efficiency of CP systems in mitigating corrosion. Through controlled laboratory experiments, carbon steel specimens were exposed to a range of simulated soil conditions to mimic real-world environments. Corrosion rates were assessed using advanced electrochemical techniques, such as linear polarization resistance (LPR) and Tafel slopes, along with traditional mass loss methods. The primary objectives of …

Go to article

Prediction Of Glass Transition Temperature Of Polymers Using Structure-Based Models, Nicholas Wolfe Jan 2025

Prediction Of Glass Transition Temperature Of Polymers Using Structure-Based Models, Nicholas Wolfe

Williams Honors College, Honors Research Projects

The focus for this study is prediction of glass transition temperatures of polymers using machine learning models. The preprocessing of the data included the generation of descriptors, the scaling of the data, the principal component analysis for dimensionality reduction, and the clustering of the data. Three methods of property predictions were utilized including Linear Regression, Random Forest, and a Feedforward Neural Network. The dataset consisted of over 7000 polymers each with their respective glass transition temperatures. This study found that the Random Forest model returned the best results followed by the Feedforward Neural Network then the Linear Regression model. Each …

Go to article

First Prev Next Last