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2026

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First Remi Experiments At A Cryogenic Ion Storage Ring, M. Schulz, F. Herrmann, W. Zhang, A. Dorn, M. Grieser, F. Grussie, H. Kreckel, O. Novotny, A. Wolf, T. Pfeifer, C. D. Schröter, R. Moshammer Jan 2026

First Remi Experiments At A Cryogenic Ion Storage Ring, M. Schulz, F. Herrmann, W. Zhang, A. Dorn, M. Grieser, F. Grussie, H. Kreckel, O. Novotny, A. Wolf, T. Pfeifer, C. D. Schröter, R. Moshammer

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

We have recorded double, triple, and quadruple coincidences between neutralized projectiles, recoiling target ions, and two electrons created in collisions of slow anions with neutral atoms. The experiments were performed at the cryogenic storage ring in Heidelberg. The recoil ions and ejected electrons were momentum-analyzed using a Reaction Microscope (ReMi) spectrometer. Various processes involving electron detachment from the projectile accompanied by various transitions in the target were investigated. Detachment without any transition in the target is qualitatively well described by a quasi-free electron model in the case of an Ar target. In detachment with single target ionization, no signatures of …


A Coupled Thermo-Hydraulic Transfer Model For Soil Freezing, Antai Dong, Xiong Zhang Jan 2026

A Coupled Thermo-Hydraulic Transfer Model For Soil Freezing, Antai Dong, Xiong Zhang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Frost heave is a common challenge in cold regions, threatening infrastructure stability. Despite decades of research, numerical simulation remains difficult due to the complex nature of coupled processes. This study presents a coupled thermo-hydraulic model for soil freezing, developed within the framework of unsaturated soil mechanics. The model uses suction and temperature as primary variables and incorporates a method to estimate ice content. It employs a soil freezing characteristic surface (SFCS), previously developed in related work, to calculate unfrozen water content as a function of both suction and temperature in partially frozen soils. The model is implemented in COMSOL for …


A Four-Step Thermocatalytic Route For Converting Co2 Into High-Purity Oxalic Acid, Hao Feng, Muhammad Kashif Khan, Lei Li, Hongyan Ma, Xinhua Liang Jan 2026

A Four-Step Thermocatalytic Route For Converting Co2 Into High-Purity Oxalic Acid, Hao Feng, Muhammad Kashif Khan, Lei Li, Hongyan Ma, Xinhua Liang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This research outlines a four-step methodology for transforming CO2 into high-purity oxalic acid. CO2 was first sequestered as KHCO3 through its reaction with aqueous KOH, followed by hydrogenation using a supported AgPd/CNT catalyst in a batch reactor at an initial H2 pressure of 60 bar and a temperature of 150°C. The formate yield reached 91.8% at optimum conditions. Potassium formate in the solid state was thermally coupled in the presence of KOH at 400°C under N2 flow, yielding potassium oxalate of up to 76% yield. The final step was the selective precipitation of potassium oxalate with ferrous …


Health Truth To Power: Professional Collaboration To Bolster Trust Against Misinformation, William M. Sage, Keegan D. Warren Jan 2026

Health Truth To Power: Professional Collaboration To Bolster Trust Against Misinformation, William M. Sage, Keegan D. Warren

Faculty Scholarship

This Article is about health, leaving aside more general challenges to shared civic information today. The Article begins by surveying the principal challenges for health information in post-pandemic, arguably post-truth America, and then describes briefly the sources and limits of medical professional authority. Noting the double-edged sword of free speech guarantees under the U.S. Constitution, the Article continues by commenting on speaking truth to government, to industry, and to the crowd. Next, the Article considers the physicians’ role in speaking truth to power from the perspective of standard medical professional ethics and identity, comparing it to that of lawyers. Finally, …


Moral Progress In Legal Doctrine, Philip Petrov Jan 2026

Moral Progress In Legal Doctrine, Philip Petrov

Faculty Scholarship

This article integrates the concept of moral progress – here, moral improvement in the thinking and behavior of individuals over time – into the study of legal doctrine. The article first presents a naturalistic account of what moral progress is and describes three of its most historically and analytically important forms: (1) moral circle expansion, (2) moral domain expansion, and (3) increasing sensitivity to proportionality. The article then analyzes three historical developments in U.S. tort law that qualify as instances of moral progress: (1) the partial demise of the “suicide rule” beginning around the 1980s (according to …


Senolytic-Resistant Senescent Cells Have A Distinct Sasp Profile And Functional Impact: The Path To Developing Senosensitizers, Utkarsh Tripathi, Masayoshi Suda, Vagisha Kulshreshtha, Bryan T Piatkowski, Allyson K Palmer, Nino Giorgadze, Christina Inman, Nathan Gasek, Ming Xu, Kurt O Johnson, Tamar Pirtskhalava, Selim Chaib, Larissa P G Langhi Prata, Yi Zhu, Renuka Kandhaya-Pillai, Stefan G Tullius, Saranya P Wyles, Rambabu Majji, Hari Krishna Yalamanchili, David B Allison, Tamar Tchkonia, James L Kirkland Jan 2026

Senolytic-Resistant Senescent Cells Have A Distinct Sasp Profile And Functional Impact: The Path To Developing Senosensitizers, Utkarsh Tripathi, Masayoshi Suda, Vagisha Kulshreshtha, Bryan T Piatkowski, Allyson K Palmer, Nino Giorgadze, Christina Inman, Nathan Gasek, Ming Xu, Kurt O Johnson, Tamar Pirtskhalava, Selim Chaib, Larissa P G Langhi Prata, Yi Zhu, Renuka Kandhaya-Pillai, Stefan G Tullius, Saranya P Wyles, Rambabu Majji, Hari Krishna Yalamanchili, David B Allison, Tamar Tchkonia, James L Kirkland

Faculty, Staff and Students Publications

The senescent cell (SC) fate is linked to aging, multiple disorders and diseases, and physical dysfunction. Senolytics, agents that selectively eliminate 30%-70% of SCs, act by transiently disabling the senescent cell antiapoptotic pathways (SCAPs), which defend those SCs that are proapoptotic and pro-inflammatory from their own senescence-associated secretory phenotype (SASP). Consistent with this, a JAK/STAT inhibitor, Ruxolitinib, which attenuates the pro-inflammatory SASP of senescent human preadipocytes, caused them to become "senolytic-resistant". Administering senolytics to obese mice selectively decreased the abundance of the subset of SCs that is pro-inflammatory. In cell cultures, the 30%-70% of human senescent preadipocytes or human umbilical …


The Words Community Dwelling, Spanish-Preferring Mexican/Mexican American Adults Use To Talk About Alzheimer’S Disease And Genetic Testing: Implications For Education And Outreach, Jamie C Fong, Fatima I Chavez, Karla Silos, Mirna L Arroyo-Miranda, Gabriela Castro Castro, Mark E Kunik, Joshua M Shulman, Luis D Medina Jan 2026

The Words Community Dwelling, Spanish-Preferring Mexican/Mexican American Adults Use To Talk About Alzheimer’S Disease And Genetic Testing: Implications For Education And Outreach, Jamie C Fong, Fatima I Chavez, Karla Silos, Mirna L Arroyo-Miranda, Gabriela Castro Castro, Mark E Kunik, Joshua M Shulman, Luis D Medina

Faculty, Staff and Students Publications

Introduction: Hispanic/Latino (H/L) adults are more likely than non-Hispanic White individuals to have Alzheimer's disease (AD), yet fewer than one in five H/L adults has apolipoprotein E (APOE) Ɛ4, underscoring gaps in understanding genetic risk across H/L heritage groups. H/L adults remain underrepresented in AD research that uses genetic data for participant stratification. To inform culturally appropriate educational materials for 16 million U.S. Spanish speakers, we identified culturally salient words Spanish-preferring H/L adults use to describe AD and genetic testing beyond APOE.

Methods: Community-residing, Spanish-preferring Mexican/Mexican American adults (n = 14) completed freelisting interviews, a method eliciting …


Mitigating Hysteresis In Metal-Coated Fibers Via Optimized Thermal Treatment For Advanced Distributed High-Temperature Sensing Applications, Koustav Dey, Rony Kumer Saha, Bohong Zhang, S. Narasimman, Farhan Mumtaz, Jeffrey D. Smith, Rex E. Gerald, Ronald J. O'Malley, Jie Huang Jan 2026

Mitigating Hysteresis In Metal-Coated Fibers Via Optimized Thermal Treatment For Advanced Distributed High-Temperature Sensing Applications, Koustav Dey, Rony Kumer Saha, Bohong Zhang, S. Narasimman, Farhan Mumtaz, Jeffrey D. Smith, Rex E. Gerald, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Metal-coated optical fibers are widely employed in sensing applications owing to their superior mechanical strength and corrosion resistance. However, their calibration at elevated temperatures is hindered by hysteresis, manifested as discrepancies between heating and cooling cycles, primarily caused by residual strain from mismatched thermal expansion coefficients (TECs) between the metal coating and silica cladding. This research introduces an optimal heat treatment procedure aimed at minimizing the impact of the mismatch in TECs between the cladding and the coating materials that causes the residual strain in gold (Au) and copper (Cu) coated fibers for achieving reliable distributed high temperature sensing up …


Large Language Models For Neurology: A Mini Review, Donald C. Wunsch, Daniel B. Hier Jan 2026

Large Language Models For Neurology: A Mini Review, Donald C. Wunsch, Daniel B. Hier

Electrical and Computer Engineering Faculty Research & Creative Works

Large language models have the potential to transform neurology by augmenting diagnostic reasoning, streamlining documentation, and improving workflow efficiency. This Mini Review surveys emerging applications of large language models in Alzheimer's disease, Parkinson's disease, multiple sclerosis, and epilepsy, with emphasis on ambient documentation, multimodal data integration, and clinical decision support. Key barriers to adoption include bias, privacy, reliability, and regulatory alignment. Looking ahead, neurology-focused language models may develop greater fluency in biomedical ontologies and FHIR standards, improving data interoperability and supporting more seamless collaboration between clinicians and AI systems. Two future developments have the potential to be particularly impactful: (1) …


Safe Optimal Control Framework For Cooperative Manipulation Of Objects In Human–Robot Teams, Irfan Ganie, Sarangapani Jagannathan Jan 2026

Safe Optimal Control Framework For Cooperative Manipulation Of Objects In Human–Robot Teams, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article introduces a distributed deep neural network (NN)-based adaptive control framework for cooperative object manipulation in human–robot teams with unknown agent dynamics by using three distinct multilayer NN observers (MNNOs). The first observer, termed the reference point estimator, enables each robotic agent to estimate the object's reference center using consensus-based learning, even without direct access to global reference trajectories. The second observer, referred to as the human force-to-trajectory estimator, uses human-applied forces to infer the intended position, velocity, and acceleration of the object, enabling real-time estimation of human intent. Together, these two observers allow distributed estimation of human-intended motion. …


High-Resolution, Fast-Response Optical Fiber Temperature Sensor With A Large Measurement Range Based On Fiber-Tip Alumina Fabry-Pérot Interferometer, Ruimin Jie, Chen Zhu, Robert Abbott, Michael Davis, Xiong Zhang, Jie Huang Jan 2026

High-Resolution, Fast-Response Optical Fiber Temperature Sensor With A Large Measurement Range Based On Fiber-Tip Alumina Fabry-Pérot Interferometer, Ruimin Jie, Chen Zhu, Robert Abbott, Michael Davis, Xiong Zhang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

We present an alumina-tip optical fiber Fabry-Pérot interferometric temperature sensor exhibiting high-temperature performance, rapid response, and high resolution. Fabricated by fusion splicing an alumina micro disk directly to a single-mode fiber, the sensor achieves robust, stable operation without complex fabrication processes or adhesives. Experimental evaluation confirms a measurement range extending to 1000°C, with sensitivity of 28.66 pm/°C, a resolution of 0.042°C, and a rapid response time of approximately 13 ms. Compared to state-of-the-art optical fiber FPI sensors, our alumina-tip sensor offers superior overall performance, effectively addressing critical demands for high-resolution, fast-response temperature measurement in extreme environments including aerospace, structural monitoring, …


Waveguide-Assisted Single-Mode Fiber Bragg Gratings In A Highly Multimode Coreless Fiber Via Femtosecond Laser Inscription For Extreme Temperature Quasi-Distributed Thermal Sensing, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang Jan 2026

Waveguide-Assisted Single-Mode Fiber Bragg Gratings In A Highly Multimode Coreless Fiber Via Femtosecond Laser Inscription For Extreme Temperature Quasi-Distributed Thermal Sensing, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This research reports a potential quasi-distributed thermal mapping optical sensing system for extreme temperatures, leveraging femtosecond (fs) laser inscribed single-mode fiber Bragg gratings (FBGs) and a waveguide within coreless, highly multimode optical fiber, resulting in a single-mode structure. Unlike doped single-mode fibers, coreless fibers composed of silica rods prevent issues associated with dopant migration and ensure data accuracy. The strategic placement of point-by-point FBGs in a cascaded formation on the fs-laser inscribed waveguide facilitates localized multipoint sensing. The long-term stability of the proposed waveguide-assisted FBG system was assessed over 24 hours at elevated temperatures (1000°C), showing no hysteresis during heating …


Distributed Temperature Sensing In The Spray-Cooled Shell Of A 150-Ton Dc Electric Arc Furnace Using Brillouin Optical Fiber Technology, Farhan Mumtaz, Yeshwanth Reddy Mekala, Koustav Dey, Rony Kumer Saha, Ogbole Collins Inalegwu, Manoj Kumar Pullagura, Bohong Zhang, Muhammad Roman, Nicholas Dionise, Zane Voss, Jeffrey D. Smith, Ronald J. O'Malley, Rex E. Gerald, Jie Huang Jan 2026

Distributed Temperature Sensing In The Spray-Cooled Shell Of A 150-Ton Dc Electric Arc Furnace Using Brillouin Optical Fiber Technology, Farhan Mumtaz, Yeshwanth Reddy Mekala, Koustav Dey, Rony Kumer Saha, Ogbole Collins Inalegwu, Manoj Kumar Pullagura, Bohong Zhang, Muhammad Roman, Nicholas Dionise, Zane Voss, Jeffrey D. Smith, Ronald J. O'Malley, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the deployment and validation of a Brillouin - distributed temperature sensing (DTS) system for real-time thermal monitoring of the spray-cooled upper shell of a 150-ton direct current Electric Arc Furnace (DC EAF) at Big River Steel Plant, Osceola, AR, USA. A four-channel Brillouin DTS system from OZ Optics was employed, with one active channel instrumented using an in-house-fabricated Brillouin scattering-depressed single-mode optical fiber (SMF28e+). The 60 m optical fiber sensor was fabricated, with 20 m allocated for thermal measurement and 40 m used as lead-in fiber to isolate the interrogator from the furnace environment. The fiber was …


Self-Calibrating Uav Navigation: Reinforcement Learning Approaches For Horizontal Trajectory Estimation, Shirin Nasr-Esfahani, S. Jagannathan Jan 2026

Self-Calibrating Uav Navigation: Reinforcement Learning Approaches For Horizontal Trajectory Estimation, Shirin Nasr-Esfahani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate unmanned aerial vehicle (UAV) trajectory estimation is essential for autonomous navigation, particularly in GPS-denied environments. Visualodometry and simultaneous localization and mapping (SLAM) approaches require precise camera intrinsic parameters, which are typically obtained through predefined or offline calibration. Instead, in this work, we propose a reinforcement learning (RL)-based self-calibration framework that estimates camera intrinsic parameters directly from monocular video sequences, without requiring prior knowledge of the camera, environment, or calibration targets. This intrinsic parameter estimation is then leveraged to achieve robust UAV trajectory estimation using only video data. We formulate the problem as a sequential decision-making task, where an RL …


Performance Analysis And Optimization Of Fructose Memristor-Based Neuromorphic Systems, Harshvardhan Uppaluru, Shakil Mahmud Jiban, Shah Zayed Riam, Feng Zhao, Jinhui Wang Jan 2026

Performance Analysis And Optimization Of Fructose Memristor-Based Neuromorphic Systems, Harshvardhan Uppaluru, Shakil Mahmud Jiban, Shah Zayed Riam, Feng Zhao, Jinhui Wang

Electrical and Computer Engineering Faculty Research & Creative Works

Natural organic memristors have demonstrated promising synaptic behavior, positioning them as strong candidates for synaptic devices in neuromorphic systems. This paper presents the fabrication and evaluation of a neuromorphic system based on natural organic 16-level and 32-level fructose memristors. First, the manufacturing process of fructose memristors is described in detail. Second, the nonlinear property associated with fructose memristors is investigated, and an optimization method is applied to address the nonlinear effects. The performance of the fructose memristor-based neuromorphic system on MNIST with a multi-layer perceptron and on CIFAR-10 with VGG-8 is evaluated and reported under various conditions -with/without nonlinearity optimization …


Integrating Optical And Radiofrequency Interferometry For Enhanced Phase Sensing, Ruimin Jie, Zhaopeng Zhang, Chen Zhu, Jie Huang Jan 2026

Integrating Optical And Radiofrequency Interferometry For Enhanced Phase Sensing, Ruimin Jie, Zhaopeng Zhang, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Interferometry is a crucial investigative technique used across diverse fields to achieve high-precision measurements. It works by analyzing the phase difference between two interfering waves, which results from variations in optical path lengths within an interferometer. We introduce a novel method for directly measuring changes in the phase difference within an optical interferometer, importantly, with the added advantage of a controllable enhancement factor. This approach is achieved through a two-step process: first, the optical phase difference is encoded into a sub-GHz radiofrequency (RF) signal using microwave-photonic manipulation; then, RF interferometry-assisted phase amplification is implemented at the destructive interference point. In …


Online Lifelong Optimal Adaptive Control Of Partially Uncertain Strict Feedback Discrete-Time Systems With Application To Quadrotor Uavs, Maxwell Geiger, Sarangapani Jagannathan Jan 2026

Online Lifelong Optimal Adaptive Control Of Partially Uncertain Strict Feedback Discrete-Time Systems With Application To Quadrotor Uavs, Maxwell Geiger, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article considers the infinite time horizon optimal adaptive tracking control of partially uncertain strict feedback discrete-time (DT) systems with application to quadrotor uncrewed aerial vehicles (UAVs). First, the strict feedback DT system is transformed into an equivalent affine nonlinear DT system in terms of the tracking error dynamics. The optimal adaptive tracking control problem is solved using an augmented system approach, where a horizon of future bounded reference trajectory points is used in the augmented state, when compared to using a single point. It is assumed that the internal dynamics of the strict feedback system are unknown, but the …


New Metrics For Disambiguating Feature Overlap And Catastrophic Forgetting In Incremental Learning Contexts, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch Jan 2026

New Metrics For Disambiguating Feature Overlap And Catastrophic Forgetting In Incremental Learning Contexts, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Catastrophic forgetting remains a central challenge in lifelong learning, where newly acquired knowledge interferes with previously learned tasks, degrading performance over time. Mitigation strategies such as rehearsal and regularization have been proposed, but both introduce limitations, either by retaining old data or by constraining model updates in ways that may impair learning. Complicating matters, recent findings show that feature-space overlap between tasks can produce similar performance drops even in models that memorize data, making it difficult to distinguish true forgetting from representational interference. Current accuracy-based metrics fail to disentangle these effects, undermining diagnostic clarity. In this work, we introduce the …


Rf-Attennet: A Hybrid Attention-Enhanced Network For Mixed Signal Classification In Uav Swarm Detection, Prajoy Podder, Mohammad Atikur Rahman, Maciej Zawodniok, Sanjay Madria Jan 2026

Rf-Attennet: A Hybrid Attention-Enhanced Network For Mixed Signal Classification In Uav Swarm Detection, Prajoy Podder, Mohammad Atikur Rahman, Maciej Zawodniok, Sanjay Madria

Electrical and Computer Engineering Faculty Research & Creative Works

The continuous increase of UAVs, particularly in swarms, creates significant challenges for security and airspace regulation. Traditional RF fingerprinting methods struggle to detect and classify UAV swarms due to overlapping signals and interference. This study introduces RF-AttenNet, a hybrid deep learning model designed to classify mixed UAV signals by analyzing composite RF spectrograms. RF-AttenNet uses dual attention mechanisms, channel and spatial attention to focus on critical spectral features, enabling the model to effectively separate and identify overlapping UAV signals. We have developed custom composite UAV datasets that simulate real-world swarm interference, incorporating both single and mixed UAV classes. RF-AttenNet achieves …


Fixed-Time Consensus Tracking For Nonlinear Multi-Agent Systems Under Aperiodically Intermittent Control, Lei Xue, Tong Wu, Wenwen Jia, Donald C. Wunsch Jan 2026

Fixed-Time Consensus Tracking For Nonlinear Multi-Agent Systems Under Aperiodically Intermittent Control, Lei Xue, Tong Wu, Wenwen Jia, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article explores the problem of fixed-time consensus tracking (FT-CT) for nonlinear multi-agent systems utilizing the a periodically intermittent control (AIC) strategy. In contrast to existing control algorithms, the proposed algorithm utilizes the AIC strategy instead of the conventional continuous-time control strategy, effectively reducing the consumption of communication resources. Moreover, the problem of intermittent FT-CT is well handled by proposing the average control rate of the AIC strategy. Two theorems based on the cases of directed and undirected graphs are proposed, respectively. Finally, the validity of these results is confirmed through numerical simulations on a general nonlinear system and a …


Honey-Cnt Memristive Artificial Synaptic Device For Sustainable Neuromorphic Computing System, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru, Jinhui Wang, Kuan Yew Cheong, Feng Zhao Jan 2026

Honey-Cnt Memristive Artificial Synaptic Device For Sustainable Neuromorphic Computing System, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru, Jinhui Wang, Kuan Yew Cheong, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

Brain-inspired neuromorphic computing systems require hardware components analogous to biological neurons and synapses. Honey based natural organic memristor has demonstrated promising nonvolatile memristive behaviors, with the advantages of sustainability, environmentally friendliness, and low-cost manufacturing. In this study, carbon nanotubes (CNTs) are added in honey to fabricate honey-CNT memristive artificial synaptic devices. Honey-CNT film is characterized by micro-Raman spectroscopy and the distribution of CNT bundles embedded in the honey-CNT composite layer by cross-sectional scanning electron microscopy for the first time. Critical synaptic functions of the honey-CNT memristor, including spike-rate-dependent plasticity, spike voltage dependent plasticity, learn-forget-relearn, and supralinear spatial summation are revealed, …


Nash Equilibrium Strategies For Multicluster Pursuit–Evasion Game With Disturbances: A Prescribed-Time Convergence Approach, Lei Xue, Xian Yu, Yongbao Wu, Jian Liu, Changyin Sun, D. C. Wunsch Jan 2026

Nash Equilibrium Strategies For Multicluster Pursuit–Evasion Game With Disturbances: A Prescribed-Time Convergence Approach, Lei Xue, Xian Yu, Yongbao Wu, Jian Liu, Changyin Sun, D. C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article investigates the problem of prescribed-time Nash equilibrium (NE) seeking for a multicluster pursuit–evasion game (PEG) subject to external disturbances. To mitigate the impact of disturbances and reach the NE within a user-defined prescribed time, a prescribed-time disturbance observer (PTDO) is devised to estimate and compensate for them. Based on this observation, a novel control algorithm is developed, which facilitates collaboration among multiple pursuers to capture multiple evaders within the prescribed time. It is theoretically demonstrated that the designed algorithm ensures prescribed-time convergence to the NE of the multicluster PEG with disturbances. Finally, numerical simulations are conducted to verify …


Real-Time Multiregional Market-To-Market Congestion Management Through Exchange Of Relief Cost Curve, Haotian Chen, Yonghong Chen, Jose Daniel Lara, Jarrad Wright, Matthew Bossart, Sebastian De Jesus Machado, Rui Bo Jan 2026

Real-Time Multiregional Market-To-Market Congestion Management Through Exchange Of Relief Cost Curve, Haotian Chen, Yonghong Chen, Jose Daniel Lara, Jarrad Wright, Matthew Bossart, Sebastian De Jesus Machado, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces a novel method for multiregional market-to-market (M2M) coordinated congestion management. It identifies shortcomings in existing M2M approaches, where Regional Transmission Organizations (RTOs) exchange shadow prices and relief requests to optimize congestion relief allocations across interconnected regions. Two methods are proposed to enhance flow and price convergence. The first method proposes that both Regional Transmission Organizations (RTOs) use state-estimator flows directly to determine relief requirements, eliminating delays and potential oscillations caused by using market flows calculated from the prior period under existing M2M approach. The second method involves exchanging transmission relief cost curves, enabling each RTOs to integrate …


Transformer-Customer Relationship Identification Based On Load-Switching Fluctuation Characteristics Considering Same-Feeder-Adjacent-Transformer Condition, Yanan Zhang, Gan Zhou, Yuyuan Liu, Wei Gu, Yanjun Feng, Yujue Wang, Rui Bo Jan 2026

Transformer-Customer Relationship Identification Based On Load-Switching Fluctuation Characteristics Considering Same-Feeder-Adjacent-Transformer Condition, Yanan Zhang, Gan Zhou, Yuyuan Liu, Wei Gu, Yanjun Feng, Yujue Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Accurately identifying the connectivity between transformers and downstream three-phase customers in low-voltage distribution networks is challenging, because voltage curves of different phases and nearby nodes can be weakly distinguishable, especially when adjacent transformers on the same feeder serve geographically close customers with highly similar voltage curves. This paper proposes a novel method based on load-switching fluctuation characteristics recorded by smart meters. By extracting localized current and voltage fluctuations and establishing correlation matching, the method overcomes the limited discriminability using steady-state measurements. The method operates in two stages: first, switching-induced fluctuation characteristics are extracted and matched to cluster customers by the …


Multi-Agent Reinforcement Learning Driven Package Pdn Design Automation, Haran Manoharan, Chulsoon Hwang Jan 2026

Multi-Agent Reinforcement Learning Driven Package Pdn Design Automation, Haran Manoharan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

The design of package-level power delivery networks (PDNs) has become increasingly challenging as modern high-performance systems demand higher currents. Existing PDN design flows treat ball map assignment, stackup selection, and power plane routing as separate, largely manual steps, leading to long iteration times and limited scalability. This work proposes a unified and automated package PDN design framework based on multi-agent reinforcement learning (MARL). Each power domain is modeled as an agent, with specialized agents responsible for ball map assignment, routing layer selection, and power plane synthesis. A central controller coordinates agent decisions using a global reward that captures electrical and …


Deep Learning Based High-Resolution Electromagnetic Inversion Imaging Using Deep Convolutional Double-Module Structure, He Ming Yao, Shiji Song, Lijun Jiang, Michael Ng Jan 2026

Deep Learning Based High-Resolution Electromagnetic Inversion Imaging Using Deep Convolutional Double-Module Structure, He Ming Yao, Shiji Song, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel deep learning (DL) approach has been proposed to realize high-resolution electromagnetic (EM) inversion imaging. The newly proposed approach is based on the deep convolutional double-module structure (DCDMS), consisting of the pixel-interpolating module and the corresponding quality-improving module. While the pixel-interpolating module roughly increases the 'resolution' of the initial input, the following quality-improving module realizes quantitative EM imaging in high resolution. The input of the proposed DCDMS adopts the mixed input scheme, consisting of the received EM scattered field and the initial reconstruction in much low resolution computed from Gauss-Newton method. The output of the proposed …


Event-Based Predefined-Time Synchronization For Complex Networks With Deception Attacks: An Asynchronously Intermittent Strategy, Lei Xue, Jiong Yu, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch Jan 2026

Event-Based Predefined-Time Synchronization For Complex Networks With Deception Attacks: An Asynchronously Intermittent Strategy, Lei Xue, Jiong Yu, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article studies the practical predefined-time synchronization (PPTS) for complex networks (CNs) under deception attacks based on the asynchronously intermittent event-triggered control (AIE-TC). Notably, AIE-TC effectively integrates the advantages of asynchronously intermittent control (AIC) and event-triggered control, where AIC provides each subsystem node with independent control and rest intervals. Besides, all synchronization errors of the CNs converge to an adjustable neighborhood within the predefined time by designing a bounded time-varying function into the controller. Moreover, this article considers that the transmission network is subjected to stochastic deception attacks modeled by a Markov process, which captures the state-driven dynamic transition characteristics …


Effect Of Sample Properties On Short-Circuited Waveguide Measurements For Materials Characterization, Alexander Hook, Jared Sinkey, Kristen M. Donnell Jan 2026

Effect Of Sample Properties On Short-Circuited Waveguide Measurements For Materials Characterization, Alexander Hook, Jared Sinkey, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Microwave materials characterization measurements can be performed using a number of well-established approaches. One such approach, the filled transmission line approach featuring a short-circuited rectangular waveguide (SC-RWG) sample holder, is known to have sample placement restrictions related to measurement viability. This work focuses on this approach and addresses the measurement restrictions within the context of sample length and dielectric properties. The complex reflection properties, S11, of a sample placed in a SC-RWG sample holder are studied to quantitively define when a sample must be offset from the SC-end. The impact of the sample holder is also studied from a measurement …


Atomized Oxidative Polymerization As A 3d Printing Platform For Binder-Free, Bulk Conductive Polymer Architectures, Tazdik Patwary Plateau, Hiep Pham, Jonghyun Park Jan 2026

Atomized Oxidative Polymerization As A 3d Printing Platform For Binder-Free, Bulk Conductive Polymer Architectures, Tazdik Patwary Plateau, Hiep Pham, Jonghyun Park

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Translating the ultrahigh intrinsic conductivity of conjugated polymers into bulk 3D architectures remains a formidable challenge due to the fundamental dichotomy between rheological printability and electronic purity. Existing strategies necessitate a compromise: solution-processing requires insulating binders that degrade charge transport, while binder-free vapor-phase polymerization (VPP) is kinetically confined to surface-limited thin films by diffusion constraints. Here, we introduce atomized oxidative polymerization (AOP), a manufacturing paradigm that overcomes these kinetic barriers via active, layer-by-layer monomer atomization. This approach ensures stoichiometric reaction conditions throughout the printed volume, driving a structural transition toward highly conductive quinoid-dominant chains with enhanced π-π stacking. The resulting …


2-Point Focused Laser Differential Interferometry Measurements Of A Parallel Jet In Supersonic Flow, Joshua Gary, Joseph Villarreal, Davide Vigano Jan 2026

2-Point Focused Laser Differential Interferometry Measurements Of A Parallel Jet In Supersonic Flow, Joshua Gary, Joseph Villarreal, Davide Vigano

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Turbulence in compressible flows plays a central role in applications such as air-fuel mixing in supersonic combustors and is significantly more complex than incompressible turbulence due to the presence of fluctuating thermodynamic quantities. As such, models like the Strong Reynolds Analogy (SRA) are used to relate these quantities. However, SRA validity has been examined primarily in boundary-layer flows. In this work, a newly developed Two-Point Focused Laser Differential Interferometry (2-FLDI) system is implemented in a two-dimensional parallel supersonic jet. The diagnostic is described in detail, including optical alignment procedures, calibration methods, and data analysis techniques. Measurements acquired at multiple streamwise …