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IEEE Texas Power and Energy Conference (TPEC)

作者： Adam King Santiago Grijalva School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta Georgia USA

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

Continuous operation of power systems is critical to modern society, even during unexpected or emergency situations. One method to evaluate the security of power systems is contingency analysis, a computationally-intensive process which considers how a set of possible scenarios would affect the electrical grid. This paper presents a novel security evaluation method which enables a topology- and parameter-free estimation of a system-level security metric, the system aggregate megawatt contingency overload (SysAMWCO), by leveraging a novel deep learning-based approach. Using the results of conventional contingency analysis for a simulated power system, a deep neural network (DNN) is trained to predict the SysAMWCO value using only bus loads as input. Experimentation across different neural network parameters reveals a complex relationship between these parameters and the accuracy of the predicted SysAMWCO value. While each DNN is trained on data generated using conventional contingency analysis methods, fully-trained models achieve R-squared scores in excess of 0.98 without needing electrical grid topology or power device parameter information as input. Given these results, this framework shows promise for potential real-world applications.

关键词： Measurement Network topology Contingency management Power system control Estimation Artificial neural networks Power systems Topology Power system security Load modeling

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A Novel Geometric-Encoded and Feature-Fused Model for Pressure Distribution Prediction on Airfoils 21st

A Novel Geometric-Encoded and Feature-Fused Model for Pressu...

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21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Fang, Shiwei Xiang, Yu Zhang, Jun Wang, Wenyong School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China International Institute of Next Generation Internet Macau University of Science and Technology Macau519020 China

ISBN: (纸本)9789819601219

Predicting the pressure distribution on an airfoil is significantly influenced by the coordinates, flight state, and the geometric shape of the airfoil. Existing methods of geometric shape representation commonly require pre-modeled airfoil data or images, which lack flexibility and overlook the potential relationship with the flight state. To address this challenge, we propose a novel Geometric-Encoded and Feature-Fused Model (GEFF), which achieves airfoil geometric encoding and feature fusion within an end-to-end model and applies it to the prediction of pressure distribution. In the model, considering the positional relationships of samples along the airfoil, we propose a novel distance attention mechanism where physical distance relationships are integrated into the calculations to generate encoded geometric features from coordinates. These encoded features and flight state features are then fused to predict the corresponding pressure distribution. Extensive ablation studies and comparison experiments were performed on GEFF. GEFF demonstrates high accuracy. Compared to Transformer, GEFF reduces the predicted mean square error by an average of 16.0%. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Signal encoding

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Optimally Managing the Impacts of Convergence Tolerance for Distributed Optimal Power Flow

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IEEE Transactions on Power Systems 2025年

作者： Harris, Rachel Alkhraijah, Mohannad Molzahn, Daniel K. Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA United States

The future power grid may rely on distributed optimization to determine the set-points for huge numbers of distributed energy resources. There has been significant work on applying distributed algorithms to optimal power flow (OPF) problems, which require separate controllers to agree on shared boundary variable values. Although controllers find feasible solutions to subproblems which optimize power flow within their region of the network, they must reach consensus on shared variables at tie-lines between regions to find a system-wide feasible solution. While running the distributed algorithm, controllers iteratively compute local subproblem solutions and communicate shared variable information until the mismatches between shared variables fall below a user-selected primal convergence tolerance. Looser tolerances for the mismatches in these shared variables generally yield faster convergence at the expense of exacerbating constraint violations, but there is little quantitative understanding of how the convergence tolerance affects solution quality. To address this gap, we first quantify how convergence tolerance impacts constraint violations when the distributed OPF solution is applied to the power system. Using insights from this analysis, we then develop a bound tightening algorithm which guarantees that operating points from distributed OPF algorithms will not result in violations despite the possibility of shared variable mismatches within the convergence tolerance. We also explore how bounding the cumulative shared variable mismatches can prevent unnecessary conservativeness in the bound tightening. While ensuring feasibility, the proposed approach enables control of the trade-off between computational speed, which improves with looser convergence tolerance, and distributed OPF solution cost, which degrades with looser convergence tolerance due to tightened constraints. © 1969-2012 IEEE.

关键词： Load flow optimization

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Development of a High-Speed FBG Interrogation System and Investigation of the Dynamic Sensing Characteristics of Metal-Embedded Fiber High-Temperature Sensors

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IEEE Sensors Journal 2025年第10期25卷 17153-17163页

作者： Pan, Xuemei Cui, Chenghao Wang, Longnan Zhou, Feng Liu, Hongbo Chen, Dali Zhang, Chao Nong, Hengchang Xiao, Yang Li, Jie Wei, Xiangning Liang, Qingquan Xu, Wenjie Li, Tao Zhang, Zeting Lu, Jinlong Ouyang, Yongjie Zhang, Zhenrong Liu, Yunyi Yu, Yang Guangxi University School of Computer Electronic and Information Nanning530004 China School of Physics and Optoelectronic Engineering Shandong University of Technology Shandong China AECC Hunan Aviation Powerplant Research Institute Zhuzhou412002 China Zhuhai Wanwei Optoelectronic Technology Company Ltd Zhuhai519000 China National University of Defense Technology College of Sciences Changsha410073 China

To meet the requirements of high-speed Interrogation and dynamic performance testing for metal-embedded fiber high-temperature sensors, this study developed a High-Speed FBG Interrogation System based on a high-speed scanning light source interrogation method and an adaptive peak-finding algorithm. Using laser-heating dynamic calibration techniques, dynamic response calibration and sensing tests were performed on sensors with varying encapsulation materials and metallic coating thicknesses. Experimental results show that the proposed High-Speed FBG Interrogation System achieves a wavelength Interrogation rate of up to 2 kHz and a resolution of 1 pm, meeting high-precision and high-speed interrogation requirements for complex dynamic temperature field applications, such as rapidly varying environments exemplified by engine combustion. © 2001-2012 IEEE.

关键词： Laser heating

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NumScout: Unveiling Numerical Defects in Smart Contracts using LLM-Pruning Symbolic Execution

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IEEE Transactions on Software engineering 2025年第05期51卷 1538-1553页

作者： Chen, Jiachi Shao, Zhenzhe Yang, Shuo Shen, Yiming Wang, Yanlin Chen, Ting Shan, Zhenyu Zheng, Zibin Hangzhou Normal University Intelligent Transportation and Information Security Laboratory Hangzhou311121 China Sun Yat-sen University School of Software Engineering Zhuhai519082 China University of Electronic Science and Technology of China School of Computer Science and Engineering School of Cyber Security Chengdu611731 China Kashi Institute of Electronics and Information Industry Kashi844000 China

In recent years, the Ethereum platform has witnessed a proliferation of smart contracts, accompanied by exponential growth in total value locked (TVL). High-TVL smart contracts often require complex numerical computations, particularly in mathematical financial models used by many decentralized applications (DApps). Improper calculations can introduce numerical defects, posing potential security risks. Existing research primarily focuses on traditional numerical defects like integer overflow, and there is currently a lack of systematic research and effective detection methods targeting new types of numerical defects. In this paper, we identify five new types of numerical defects through the analysis of 1,199 audit reports by utilizing the open card method. Each defect is defined and illustrated with a code example to highlight its features and potential consequences. We also propose NumScout, a symbolic execution-based tool designed to detect these five defects. Specifically, the tool combines information from source code and bytecode, analyzing key operations such as comparisons and transfers, to effectively locate defects and report them based on predefined detection patterns. Furthermore, NumScout uses a large language model (LLM) to prune functions which are unrelated to numerical operations. This step allows symbolic execution to quickly enter the target function and improve runtime speed by 28.4%. We run NumScout on 6,617 real-world contracts and evaluated its performance based on manually labeled results. We find that 1,774 contracts contained at least one of the five defects, and the tool achieved an overall precision of 89.7%. © 2025 IEEE.

关键词： Smart contract

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Parallel Welch–Berlekamp Algorithm

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IEEE Transactions on Information Theory 2025年第5期71卷 3473-3488页

作者： Chen, Chao Han, Yunghsiang S. Tang, Nianqi Ma, Xiao Bai, Baoming Xidian University State Key Laboratory of ISN Xi’an710071 China University of Electronic Science and Technology of China Shenzhen Institute for Advanced Study Shenzhen518000 China Sun Yat-sen University School of Computer Science and Engineering Guangzhou510006 China

This paper presents new variants of the Welch-Berlekamp algorithm that are favorable to hardware implementation. First, we derive the parallel Welch-Berlekamp (PWB) algorithm in a constructive manner based on the properties of solutions to the rational interpolation problem. The algorithm features the simultaneously performed discrepancy computation and polynomial update. Second, we explore the early-termination mechanism of the PWB algorithm for decoding of Reed-Solomon (RS) codes. By introducing the concept of incomplete error locator polynomial, we show that if e ≤ t (where e is the number of errors and t is the error correction capability), the PWB algorithm can be terminated at latest at the completion of the (t+ e) -th iteration. This leads to the early-terminating PWB (EPWB) algorithm. Finally, we develop frequency-domain versions of the PWB and EPWB algorithms, namely, FPWB and FEPWB. The key point toward the two algorithms is to replace the update of polynomial coefficients with the update of polynomial evaluations. It is worth noting that the FEPWB algorithm applies only to shortened RS codes. Furthermore, an efficient systolic architecture for the FPWB algorithm is designed, which is easily adapted for the FEPWB algorithm. © 1963-2012 IEEE.

关键词： Reed-Solomon codes

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Lensless efficient snapshot hyperspectral imaging using dynamic phase modulation

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Photonics Research 2025年第2期13卷 511-526页

作者： CHONG ZHANG XIANGLEI LIU LIZHI WANG SHINING MA YUANJIN ZHENG YUE LIU HUA HUANG YONGTIAN WANG WEITAO SONG Beijing Engineering Research Center of Mixed Reality and Advanced Display School of Optics and Photonics Beijing Institute of Technology Zhengzhou Research Institute Beijing Institute of Technology State Key Laboratory of Radio Frequency Heterogeneous Integration College of Physics and Optoelectronic Engineering Shenzhen University School of Computer Science and Technology Beijing Institute of Technology School of Electrical and Electronic Engineering Nanyang Technological University School of Artificial Intelligence Beijing Normal University

Snapshot hyperspectral imaging based on a diffractive optical element(DOE) is increasingly featured in recent progress in deep optics. Despite remarkable advances in spatial and spectral resolutions, the limitations of current photolithography technology have prevented the fabricated DOE from being designed at ideal heights and with high diffraction efficiency, diminishing the effectiveness of coded imaging and reconstruction accuracy in some bands. Here, we propose, to our knowledge, a new lensless efficient snapshot hyperspectral imaging(LESHI)system that utilizes a liquid-crystal-on-silicon spatial light modulator(LCoS-SLM) to replace the traditionally fabricated DOE, resulting in high modulation levels and reconstruction accuracy. Beyond the single-lens imaging model, the system can leverage the switch ability of LCoS-SLM to implement distributed diffractive optics(DDO)imaging and enhance diffraction efficiency across the full visible spectrum. Using the proposed method, we develop a proof-of-concept prototype with an image resolution of 1920 × 1080 pixels, an effective spatial resolution of 41.74 μm, and a spectral resolution of 10 nm, while improving the average diffraction efficiency from 0.75 to0.91 over the visible wavelength range(400–700 nm). Additionally, LESHI allows the focal length to be adjusted from 50 mm to 100 mm without the need for additional optical components, providing a cost-effective and timesaving solution for real-time on-site debugging. LESHI is the first imaging modality, to the best of our knowledge,to use dynamic diffractive optics and snapshot hyperspectral imaging, offering a completely new approach to computational spectral imaging and deep optics.

关键词： Diffraction efficiency Diffractive optical elements Imaging systems Phase modulation Spatial light modulators Spatial resolution

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Artificial sensory neurons and their applications

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Journal of Semiconductors 2025年第1期46卷 108-128页

作者： Jiale Shao Hongwei Ying Peihong Cheng Lingxiang Hu Xianhua Wei Zongxiao Li Huanming Lu Zhizhen Ye Fei Zhuge Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingbo 315201China School of Electronic and Information Engineering Ningbo University of TechnologyNingbo 315211China State Key Laboratory of Environment-friendly Energy Materials Southwest University of Science and TechnologyMianyang 621010China Institute of Wenzhou Zhejiang UniversityWenzhou 325006China State Key Laboratory of Silicon Materials School of Materials Science and EngineeringZhejiang UniversityHangzhou 310027China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghai 200072China

With the rapid development of artificial intelligence(AI)technology,the demand for high-performance and energyefficient computing is increasingly *** limitations of the traditional von Neumann computing architecture have prompted researchers to explore neuromorphic computing as a *** computing mimics the working principles of the human brain,characterized by high efficiency,low energy consumption,and strong fault tolerance,providing a hardware foundation for the development of new generation AI *** neurons and synapses are the two core components of neuromorphic computing *** perception is a crucial aspect of neuromorphic computing,where artificial sensory neurons play an irreplaceable role thus becoming a frontier and hot topic of *** work reviews recent advances in artificial sensory neurons and their ***,biological sensory neurons are briefly ***,different types of artificial neurons,such as transistor neurons and memristive neurons,are discussed in detail,focusing on their device structures and working ***,the research progress of artificial sensory neurons and their applications in artificial perception systems is systematically elaborated,covering various sensory types,including vision,touch,hearing,taste,and ***,challenges faced by artificial sensory neurons at both device and system levels are summarized.

关键词： artificial sensory neurons artificial perception systems neuromorphic computing artificial intelligence

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Architecture Decisions for Supporting Web-based Visualization of Distribution System Operating Envelopes

Architecture Decisions for Supporting Web-based Visualizatio...

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IEEE Texas Power and Energy Conference (TPEC)

作者： Jorge Fernandez Santiago Grijalva School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta USA

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

Operating envelopes are dynamic limits on power injections, computed in advance based on the operational con-ditions of the network, such as load profiles. These dynamic limits can unlock the full potential of distributed energy resources (DERs) by maximizing the use of existing infrastructure while ensuring a reliable power supply. Visualizing operating envelopes presents a significant challenge, it requires effectively conveying spatio-temporal information for multiple connection sites simultaneously. This paper discusses, demonstrates, and evaluates a set of software architecture decisions to support web-based visualization of distribution system operating envelopes. We propose a microservice-oriented architecture with two processing modules: one for time series power flow and another for three-phase unbalanced multi-period optimal power flow (also known as energy scheduling) computations. Both modules are con-tainerized, ensuring strong separation of duties and portability. Additionally, a web-based visualization interface is developed to incorporate advanced interactive visualization techniques to support the analysis of complex spatio-temporal relationships and “what if” scenarios. The performance of the approach is evaluated by measuring processing time and size from responses considering various distribution feeders, including the 3- Bus, IEEE 4-Bus, IEEE 13-Bus, and IEEE 123-Bus test feeders.

关键词： Visualization Time series analysis Microservice architectures computer architecture Telecommunication traffic Containers Time measurement Time factors Usability Load flow

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A Model-Free Optimal Control Method with Fixed Terminal States

A Model-Free Optimal Control Method with Fixed Terminal Stat...

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IEEE Southeastcon

作者： Mi Zhou Erik Verriest Chaouki Abdallah School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

Optimal control of state-dependent switched systems and time-delay systems is a challenge in the control community. Classical optimality conditions-based methods rely on heavy mathematical analysis for time-delay systems or prior knowledge of switching sequences. To solve this problem, model-free algorithms are brought into the control system's research with the emergence of reinforcement learning algorithms. However, there are two practical challenges of reinforcement learning-based methods. First, learning by interacting with the environment is a highly complex process. Second, constraints on the states (boundary conditions) require additional care since the state trajectory is implicitly defined from the inputs and system dynamics. To address these problems, this paper proposes a new model-free algorithm based on basis functions, gradient estimation, and the Lagrange method. The favorable performance of the proposed algorithm is shown using several examples under state-dependent switches and/or time delays.

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