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Free vibration analysis of functionally graded porous curved nanobeams on elastic foundation in hygro-thermo-magnetic environment

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Frontiers of Structural and Civil engineering 2023年第4期17卷 584-605页

作者： Quoc-Hoa PHAM Parviz MALEKZADEH Van Ke TRAN Trung NGUYEN-THOI Faculty of Engineering and Technology Nguyen Tat Thanh UniversityHo Chi Minh City 700000Vietnam Department of Mechanical Engineering Persian Gulf UniversityBushehr ***Iran Faculty of Mechanical Engineering Le Quy Don Technical UniversityHanoi 100000Vietnam Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 700000Vietnam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 700000Vietnam Bualuang ASEAN Chair Professor Thammasat School of EngineeringThammasat UniversityPathumtani 12120Thailand

Herein,a two-node beam element enriched based on the Lagrange and Hermite interpolation function is proposed to solve the governing equation of a functionally graded porous(FGP)curved nanobeam on an elastic foundation in a hygro–thermo–magnetic *** material properties of curved nanobeams change continuously along the thickness via a power-law distribution,and the porosity distributions are described by an uneven porosity *** effects of magnetic fields,temperature,and moisture on the curved nanobeam are assumed to result in axial loads and not affect the mechanical properties of the *** equilibrium equations of the curved nanobeam are derived using Hamilton’s principle based on various beam theories,including the classical theory,first-order shear deformation theory,and higher-order shear deformation theory,and the nonlocal elasticity *** accuracy of the proposed method is verified by comparing the results obtained with those of previous reliable ***,the effects of different parameters on the free vibration behavior of the FGP curved nanobeams are investigated comprehensively.

关键词： functionally graded porous material curved nanobeam hygro-thermo-magnetic enriched finite element method

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Ferrite Shielding for Eddy Current Suppression on Inductors and Transformers Using Ribbon-Based Magnetic Cores

Ferrite Shielding for Eddy Current Suppression on Inductors ...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Zihan Gao Fred Wang Min H. Kao Department of Electrical Engineering and Computer Science The University of Tennessee Knoxville Knoxville TN USA Min H. Kao Department of Electrical Engineering and Computer Science The University of Tennessee Knoxville TN USA Oak Ridge National Laboratory Oak Ridge TN USA

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

Ribbon-based magnetic cores, such as nanocrystalline and amorphous cores, have been widely used in inductors and transformers in high power converters. However, unwanted eddy current can be found on the surfaces of the core laminations due to fringing effect and leakage magnetic field. In this paper, a ferrite shielding structure is proposed to create bypass loops for lamination layers to avoid the stray field crossing the lamination layers. The mechanism of the proposed shielding is demonstrated. Simulations and tests have proved the effectiveness for the gapped inductor, as well as core and shell-type transformers.

关键词： Ferrites Surface waves Lamination Simulation Energy conversion Transformer cores Transformers Magnetic fields Inductors Eddy currents

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State-Aware Perturbation Optimization for Robust Deep Reinforcement Learning

arXiv

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arXiv 2025年

作者： Zhang, Zongyuan Duan, Tianyang Lin, Zheng Huang, Dong Fang, Zihan Sun, Zekai Xiong, Ling Liang, Hongbin Cui, Heming Cui, Yong Department of Computer Science The University of Hong Kong Hong Kong Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Department of Computer Science City University of Hong Kong Hong Kong School of Computer and Software Engineering Xihua University Chengdu610039 China National United Engineering Laboratory of Integrated and Intelligent Transportation The National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu611756 China Department of Computer Science and Technology Ts-inghua University Beijing100084 China

Recently, deep reinforcement learning (DRL) has emerged as a promising approach for robotic control. However, the deployment of DRL in real-world robots is hindered by its sensitivity to environmental perturbations. While existing white-box adversarial attacks rely on local gradient information and apply uniform perturbations across all states to evaluate DRL robustness, they fail to account for temporal dynamics and state-specific vulnerabilities. To combat the above challenge, we first conduct a theoretical analysis of white-box attacks in DRL by establishing the adversarial victim-dynamics Markov decision process (AVD-MDP), to derive the necessary and sufficient conditions for a successful attack. Based on this, we propose a selective state-aware reinforcement adversarial attack method, named STAR, to optimize perturbation stealthiness and state visitation dispersion. STAR first employs a soft mask-based state-targeting mechanism to minimize redundant perturbations, enhancing stealthiness and attack effectiveness. Then, it incorporates an information-theoretic optimization objective to maximize mutual information between perturbations, environmental states, and victim actions, ensuring a dispersed state-visitation distribution that steers the victim agent into vulnerable states for maximum return reduction. Extensive experiments demonstrate that STAR outperforms state-of-the-art benchmarks. Copyright © 2025, The Authors. All rights reserved.

关键词： Markov processes

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Grid of Near Future: Impact on (N-1) Contingency Analysis in Presence of Droop-Controlled Grid-Forming Converter-Interfaced Generations

Grid of Near Future: Impact on (N-1) Contingency Analysis in...

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2022 IEEE Power and Energy Society General Meeting, PESGM 2022

作者： Karunaratne, Lilan Yogarathnam, Amirthagunaraj Ray Chaudhuri, Nilanjan Yue, Meng Pennsylvania State University School of Electrical Engineering and Computer Science University ParkPA United States Brookhaven National Laboratory Interdisciplinary Science Department UptonNY United States

ISBN: (数字)9781665408233

ISBN: (纸本)9781665408233

Similar to the traditional ac grids, a secure operation of near future grids with high penetration of converter-interfaced generations (CIGs) including grid-forming converters (GFCs) following a single-point failure, i.e., an (N-1) contingency, is a fundamental problem during the contingency screening and ranking. The increasing CIGs introduce dynamics of different time scales and may change the dynamic behaviors of the grid under (N-1) contingencies. This paper focuses on the contingency analysis of such grids following synchronous generator (SG) outages i.e., the impact of GFCs following a SG outage on such analysis due to their dc-side current limits. To this end, an averaged model of GFCs is developed, and the dc side dynamics and the current limits are also modeled. Then, a revised online/offline generator outage contingency screening and ranking approach to take into account the effect of dc-link voltage collapse of GFCs is proposed. Finally, the proposed approach is validated using the time-domain simulation on a modified 2-area 4-machine test system with a GFC. © 2022 IEEE.

关键词： Time domain analysis

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Learning-based Solar Power and Load Forecasting in DC Net-zero Energy Building with Incomplete Data 7

Learning-based Solar Power and Load Forecasting in DC Net-ze...

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7th IEEE International Conference on Power and Renewable Energy, ICPRE 2022

作者： Iao, Hou-Wang Lao, Keng-Weng Kang, Jing University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering China Shenzhen Institute of Building Research Co . Ltd. Shenzhen China

ISBN: (数字)9781665450638

ISBN: (纸本)9781665450638

To cope with global climate change and carbon emission reduction, net-zero energy building (NZEB) was advocated in the building industries in these years, which aims to minimize energy needs and achieve zero-energy balance through renewables generation. Practically, because of the increasing energy demand and uncertainty in renewables generation, the building microgrid mostly relies on grid supply for daily usage instead of renewables generation, which violates the intention of zero energy. Thus, accurate load and PV power forecasting are imperative for NZEB power system planning. However, data-driven forecasting requires high volume of complete dataset. This paper compares load and PV power forecasting performance by learning-based models with incomplete data based on a demonstration NZEB project. The result highlights that Gated Recurrent Unit (GRU) and Bidirectional Long Short Term Memory (BiLSTM) with K-nearest neighbors (KNN) interpolation on improvement of weekly load and PV power forecasting RMSE by 10.132 kW and 6.650 kW respectively. © 2022 IEEE.

关键词： Climate change

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An Optimized Ensemble Model for Prediction the Bandwidth of Metamaterial Antenna

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computers, Materials & Continua 2022年第4期71卷 199-213页

作者： Abdelhameed Ibrahim Hattan F.Abutarboush Ali Wagdy Mohamed Mohamad Fouad El-Sayed M.El-kenawy Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Electrical Engineering Department College of EngineeringTaibah UniversityMedina42353Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyEgypt

Metamaterial Antenna is a special class of antennas that uses metamaterial to enhance their *** size affects the quality factor and the radiation loss of the *** antennas can overcome the limitation of bandwidth for small *** learning(ML)model is recently applied to predict antenna *** can be used as an alternative approach to the trial-and-error process of finding proper parameters of the simulated *** accuracy of the prediction depends mainly on the selected *** models combine two or more base models to produce a better-enhanced *** this paper,a weighted average ensemble model is proposed to predict the bandwidth of the Metamaterial *** base models are used namely:Multilayer Perceptron(MLP)and Support Vector Machines(SVM).To calculate the weights for each model,an optimization algorithm is used to find the optimal weights of the *** Group-Based Cooperative Optimizer(DGCO)is employed to search for optimal weight for the base *** proposed model is compared with three based models and the average ensemble *** results show that the proposed model is better than other models and can predict antenna bandwidth efficiently.

关键词： Metamaterial antenna machine learning ensemble model multilayer perceptron support vector machines

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Ensuring the Data Security and Integrity over Cloud Computing Environment using Novel Cipher Strategy

Ensuring the Data Security and Integrity over Cloud Computin...

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2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent systems, AICERA/ICIS 2023

作者： Praveen Kumar, E. Yasotha, B. Narmadha, P.G. Chandrakala, P. Ushapriya, C. Chamundeeswari, G. Tamil Nadu Coimbatore India Srmist Department of Data Science and Business Systems Tamil Nadu kattankulathur India Panimalar Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India St. Martin's Engineering College Department of Artificial Intelligence and Machine Learning Telangana India Saveetha Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350303452

The advent of cloud computing has revolutionized the Internet. Users may effortlessly collaborate, back up, and access their information from any location thanks to cloud computing. When it comes to providing IT enabled services via the internet, cloud computing is the clear winner. Cloud computing allows a large number of people to share resources like computers, programs, and servers. Users of cloud services often have no idea where their data actually resides or where it came from. Users of cloud computing services are understandably concerned about the safety of their data once it has been uploaded to the cloud with respect to service providers. Privilege control, comprehensive encryption algorithms, management of keys, provenance instances and global consistency verification are only some of the numerous data privacy and security issues that occur as a result. This study introduces a novel cloud security strategy, Cloud based Novel Cipher Strategy (CNCS), and analyzes issues related to the safety and integrity of data stored in the cloud. We're looking into many data safety related factors here. In this article, we'll look closely at a selection of data protection strategies now in use throughout the globe to guarantee the highest level of security possible. Later, the study delves into the various methods of cloud based data security. To prevent unwanted access, alteration, or deletion of dynamic as well as static information, a procedure for validating their integrity is outlined. The proposed system CNCS efficiency is evaluated in the resulting section through the following metrics such as: integrity level, data storage efficiency and security level. All these metrics are evaluated based on the size of data, in which it is tested with respect to number of days the proposed scheme is tested over the industrial environment to prove the performance and efficiency of the proposed approach. © 2023 IEEE.

关键词： Cloud security

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Addressing Economic Dispatch Problem with Multiple Fuels Using Oscillatory Particle Swarm Optimization

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computers, Materials & Continua 2021年第12期69卷 2863-2882页

作者： Jagannath Paramguru Subrat Kumar Barik Ajit Kumar Barisal Gaurav Dhiman Rutvij HJhaveri Mohammed Alkahtani Mustufa Haider Abidi KIIT University BhubaneswarOdishaIndia Department of Electrical Engineering CETBhubaneswarOdishaIndia Department of Computer Science Government Bikram College of CommercePatialaIndia Department of Computer Science&Engineering Pandit Deendayal Petroleum UniversityGandhinagarIndia Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

Economic dispatch has a significant effect on optimal economical operation in the power systems in industrial revolution 4.0 in terms of considerable savings in *** non-linearity are added to make the fossil fuel-based power systems more *** order to achieve an accurate economical schedule,valve point loading effect,ramp rate constraints,and prohibited operating zones are being considered for realistic *** this paper,an improved,and modified version of conventional particle swarm optimization(PSO),called Oscillatory PSO(OPSO),is devised to provide a cheaper schedule with optimum *** conventional PSO is improved by deriving a mechanism enabling the particle towards the trajectories of oscillatory motion to acquire the entire search space.A set of differential equations is implemented to expose the condition for trajectory motion in *** adaptive inertia weights,this OPSO method provides an optimized cost of generation as compared to the conventional particle swarm optimization and other new meta-heuristic approaches.

关键词： Economic load dispatch valve point loading industry 4.0 prohibited operating zones ramp rate limit oscillatory particle swarm optimization

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High-Impedance Non-Linear Fault Detection via Eigenvalue Analysis with low PMU Sampling Rates

High-Impedance Non-Linear Fault Detection via Eigenvalue Ana...

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Innovative Smart Grid Technologies (ISGT)

作者： Gian Paramo Arturo Bretas Sean Meyn Electrical and Computer Engineering University of Florida Gainesville FL USA Distributed Systems Group Pacifc Northwest National Laboratory Richland WA USA

This work presents a hybrid data-driven and physics-based framework for high-impedance fault detection in power systems. An innovative method based on eigenvalue analysis is expanded and validated. Phasor Measurement Unit data is used to estimate eigenvalues corresponding to the powerlines being monitored. Eigenvalue statistics are then tracked and evaluated. Faults are detected as they drive eigenvalues outside of their normal zones. This technique holds several advantages over contemporary techniques: It utilizes technology that is already deployed in the field, it offers a significant degree of generality, and so far it has displayed a very high-level of sensitivity without sacrificing accuracy. Validation is performed in the form of simulations based in the IEEE 13 Node System and non-linear fault models. Test results are encouraging, indicating potential for real-life applications.

关键词： Sensitivity Measurement units Impedance measurement Fault detection Energy measurement Eigenvalues and eigenfunctions Phasor measurement units

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Optical Fiber Tip Learns to Identify Liquids 27

Optical Fiber Tip Learns to Identify Liquids

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27th International Conference on Optical Fiber Sensors, OFS 2022

作者： Zhu, Chen Naku, Wassana Nambisan, Anand K. Gerald, Rex E. Huang, Jie Research Center for Optical Fiber Sensing Zhejiang Laboratory Hangzhou311100 China Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO65409 United States

We propose and demonstrate an extremely simple fiber-optic tip sensor system to identify liquids through droplet evaporation events on the fiber tip, analyzed using machine learning techniques. © 2022 The Author(s).

ISBN: (纸本)9781957171142

关键词： Optical fibers

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