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Integrated modelling of vacuum flashover development:Above-surface processes and breakdown threshold analyses

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High Voltage 2024年第3期9卷 614-625页

作者： Guangyu Sun Yitong Yao Xiong Yang Baohong Guo Shu Zhang Chao Wang Ruhui Lian Baipeng Song Haibao Mu Guanjun Zhang State Key laboratory of electrical Insulation and Power Equipment Xi'an Jiaotong UniversitySchool of Electrical EngineeringXi'anShaanxiChina

The flashover in vacuum is a rapid interfacial discharge across the insulator surface when subjected to high applied *** a theoretical model covering above-surface processes is *** model calculates the flashover threshold in vacuum,with revised secondary electron emission avalanche theory and improved desorbed neutral transport *** model serves as the first part of an integrated flashover model,aiming for consistent treatment of both above-surface and subsurface processes during the entire flashover *** flashover threshold is obtained by combining the desorbed neutral pressure at given applied voltage and the gas breakdown criterion dictated by the Paschen's *** analytical formula for threshold estimation containing physical parameters,and a simplified formula consisting of empirical coefficients are introduced,catering for both conceptual understanding and practical *** derived formulae are validated by experimental data for a variety of insulator *** theory generalisation for non-uniform electric field distribution is further discussed.

关键词： flash breakdown vacuum

Bayesian ensemble methods for predicting ground deformation due to tunnelling with sparse monitoring data

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Underground Space 2024年第3期16卷 79-93页

作者： Zilong Zhang Tingting Zhang Xiaozhou Li Daniel Dias School of Civil engineering Central South UniversityChangshaHunan 410075China laboratory 3SR Grenoble Alpes UniversityCNRS UMR 5521Grenoble 38000France

Numerous analytical models have been developed to predict ground deformations induced by tunneling,which is a critical issue in tunnel ***,the accuracy of these predictions is often limited by errors and uncertainties resulting from model selection and parameter fittings,given the paucity of monitoring data in field *** paper proposes a novel approach to estimate tunnelling-induced ground deformations by applying Bayesian model averaging to several representative prediction *** accounting for both model and parameter uncertainties,this approach enables more realistic predictions of ground deformations than individual ***,our results indicate that the Gonzalez-Sagaseta model outperforms other models in predicting ground surface settlements,while the Loganathan-Poulos model is most suitable for predicting subsurface vertical and horizontal ***,our analysis reveals that when monitoring data are sparse,model uncertainties may contribute up to 78.7%of the total ***,obtaining sufficient data for parameter fitting is crucial for accurate *** proposed method in this study offers a more realistic and efficient prediction of tunnelling-induced ground deformations.

关键词： Tunnelling-induced ground deformations Sparse data Model uncertainties Bayesian model averaging

Rockburst prediction and prevention in underground space excavation

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Underground Space 2024年第1期14卷 70-98页

作者： Jian Zhou Yulin Zhang Chuanqi Li Haini He Xibing Li School of Resources and Safety engineering Central South UniversityChangsha 410083China laboratory 3SR CNRS UMR 5521Grenoble Alpes UniversityGrenoble 38000France

The technical challenges associated with deep underground space activities have become increasingly *** these challenges,one major concern is the assessment of rockburst risks and the instability of rock *** research has been conducted by numerous scholars to mitigate the risks and prevent occurrences of rockburst through various assessment *** incidents commonly occur during the excavation of hard rock in underground environments,posing severe threats to personnel safety,equipment integrity,and operational ***,it is crucial to systematically document real cases of rockburst,allowing for a comprehensive understanding of the underlying mechanisms and triggering *** understanding will contribute to the advancement of rockburst prediction and prevention *** selection of an appropriate rockburst assessment method is a fundamental aspect in underground ***,there is a limited number of studies that summarize and compare different prediction and prevention methods of *** paper aims to address this gap by analyzing global trends using CiteSpace software since *** discusses rockburst classification and characteristics,comprehensively reviews research findings related to rockburst prediction,including empirical,simulation,mathematical modeling,and microseismic monitoring ***,the paper presents a compilation of current rockburst prevention ***,the paper emphasizes the significance of control strategies,which provide key insights into the effective utilization of stored energy within ***,the paper concludes by suggesting six directions for implementing intelligent management techniques to mitigate hazards during underground operations and reduce the probability of rockburst incidents.

关键词： Rockburst Underground space Scientometric analysis Characteristic analysis Rockburst prediction Rockburst prevention

Migration time prediction and assessment of toxic fumes under forced ventilation in underground mines

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Underground Space 2024年第5期18卷 273-294页

作者： Jinrui Zhang Tingting Zhang Chuanqi Li School of Resources&Civil engineering Northeastern UniversityShenyang 110819China laboratory 3SR CNRS UMR 5521Grenoble Alpes UniversityGrenoble 38000France

This study aims to predict the migration time of toxic fumes induced by excavation blasting in underground *** reduce numerical simulation time and optimize ventilation design,several back propagation neural network(BPNN)models optimized by honey badger algorithm(HBA)with four chaos mapping(CM)functions(i.e.,Chebyshev(Che)map,Circle(Cir)map,Logistic(Log)map,and Piecewise(Pie)map)are developed to predict the migration time.125 simulations by the computational fluid dynamics(CFD)method are used to train and test the developed *** determination coefficient(R2),the variance accounted for(VAF),the Willmott’s index(WI),the root mean square error(RMSE),the mean absolute percentage error(MAPE),and the sum of squares error(SSE)are utilized to evaluate the model *** evaluation results indicate that the CirHBA-BPNN model has achieved the most satisfactory performance by reaching the highest values of R2(0.9945),WI(0.9986),VAF(99.4811%),and the lowest values of RMSE(15.7600),MAPE(0.0343)and SSE(6209.4),*** wind velocity in roadway(Wv)is the most important feature for predicting the migration time of toxic ***,the intrinsic response characteristic of the optimal model is implemented to enhance the model interpretability and provide reference for the relationship between features and migration time of toxic fumes in ventilation design.

关键词： Migration time Underground mines Honey badger algorithm Chaos mapping Back propagation neural network

Probabilistic analysis of tunnel face seismic stability in layered rock masses using Polynomial Chaos Kriging metamodel

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Journal of Rock Mechanics and Geotechnical engineering 2024年第7期16卷 2678-2693页

作者： Jianhong Man Tingting Zhang Hongwei Huang Daniel Dias Department of Geotechnical engineering Key Laboratory of Geotechnical and Underground Engineering of Ministry of EducationCollege of Civil EngineeringTongji UniversityShanghai200092China grenoble Alpes 3SR LabCNRS UMR 5521Grenoble38000France

Face stability is an essential issue in tunnel design and *** rock masses are typical and ubiquitous;uncertainties in rock properties always *** view of this,a comprehensive method,which combines the Upper bound Limit analysis of Tunnel face stability,the Polynomial Chaos Kriging,the Monte-Carlo Simulation and Analysis of Covariance method(ULT-PCK-MA),is proposed to investigate the seismic stability of tunnel faces.A two-dimensional analytical model of ULT is developed to evaluate the virtual support force based on the upper bound limit *** efficient probabilistic analysis method PCK-MA based on the adaptive Polynomial Chaos Kriging metamodel is then implemented to investigate the parameter uncertainty *** input parameters,including geological strength indices,uniaxial compressive strengths and constants for three rock formations,and the horizontal seismic coefficients,are treated as random *** effects of these parameter uncertainties on the failure probability and sensitivity indices are *** addition,the effects of weak layer position,the middle layer thickness and quality,the tunnel diameter,the parameters correlation,and the seismic loadings are investigated,*** results show that the layer distributions significantly influence the tunnel face probabilistic stability,particularly when the weak rock is present in the bottom *** efficiency of the proposed ULT-PCK-MA is validated,which is expected to facilitate the engineering design and construction.

关键词： Tunnel face stability Layered rock masses Polynomial Chaos Kriging(PCK) Sensitivity index Seismic loadings

Market Equilibrium Based on Cloud-edge Collaboration

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 96-104页

作者： Tong Cheng Haiwang Zhong Qing Xia the State Key laboratory of Power Systems the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

Market participants can only bid with lagged information disclosure under the existing market mechanism,which can lead to information asymmetry and irrational market behavior,thus influencing market *** promote rational bidding behavior of market participants and improve market efficiency,a novel electricity market mechanism based on cloudedge collaboration is proposed in this *** market information,called residual demand curve,is published to market participants in real-time on the cloud side,while participants on the edge side are allowed to adjust their bids according to the information disclosure prior to closure *** proposed mechanism can encourage rational bids in an incentive-compatible way through the process of dynamic equilibrium while protecting participants’*** paper further formulates the mathematical model of market equilibrium to simulate the process of each market participant’s strategic bidding behavior towards equilibrium.A case study based on the IEEE 30-bus system shows the proposed market mechanism can effectively guide bidding behavior of market participants,while condensing exchanged information and protecting privacy of participants.

关键词： Cloud-edge collaboration market mechanism residual demand curve strategic bidding

Sensing the heavy water concentration in an H_(2)O-D_(2)O mixture by solid-solid phononic crystals

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Chinese Physics B 2024年第4期33卷 493-498页

作者： Mohammadreza Rahimi Ali Bahrami Optoelectronic and Nanophotonics Research laboratory(ONRL) Faculty of Electrical EngineeringSahand University of TechnologyTabrizIran

A new method based on phononic crystals is presented to detect the concentration of heavy water(D_(2)O)in an H_(2)O-D_(2)O *** have been obtained and analyzed in the concentration range of 0%-10%and 90%-100%D_(2)O.A proposed structure of tungsten scatterers in an aluminum host is *** order to detect the target material,a cavity region is considered as a sound wave resonator in which the target material with different concentrations of D_(2)O is *** changing the concentration of D_(2)O in the H_(2)O-D_(2)O mixture,the resonance frequency undergoes a frequency *** 1%change in D_(2)O concentration in the H_(2)O-D_(2)O mixture causes a frequency change of about 120 *** finite element method is used as the numerical method to calculate and analyze the natural frequencies and transmission spectra of the proposed *** performance evaluation index shows a high Q factor up to 1475758 and a high sensitivity up to 13075,which are acceptable values for sensing *** other figures of merit related to the detection performance also indicate high-quality performance of the designed sensor.

关键词： phononic crystals sensor H_(2)O-D_(2)O mixture cavity

Data-driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 874-885页

作者： Wenlong Liao Dechang Yang Qi Liu Yixiong Jia Chenxi Wang Zhe Yang Wind engineering and Renewable Energy laboratory Ecole Polytechnique Federale de Lausanne(EPFL)Lausanne 1015Switzerland the College of Information and electrical engineering China Agricultural UniversityBeijing 100083China the College of electrical engineering and Automation Shandong University of Science and TechnologyQingdao 266590China the Department of electrical and Electronic engineering(Energy Digitalization laboratory) The University of Hong KongHong KongChina the Department of electrical engineering The Hong Kong Polytechnic UniversityHong KongChina

Reactive power optimization of distribution networks is traditionally addressed by physical model based methods,which often lead to locally optimal solutions and require heavy online inference time *** improve the quality of the solution and reduce the inference time burden,this paper proposes a new graph attention networks based method to directly map the complex nonlinear relationship between graphs(topology and power loads)and reactive power scheduling schemes of distribution networks,from a data-driven *** graph attention network is tailored specifically to this problem and incorporates several innovative features such as a self-loop in the adjacency matrix,a customized loss function,and the use of max-pooling ***,a rulebased strategy is proposed to adjust infeasible solutions that violate *** results on multiple distribution networks demonstrate that the proposed method outperforms other machine learning based methods in terms of the solution quality and robustness to varying load ***,its online inference time is significantly faster than traditional physical model based methods,particularly for large-scale distribution networks.

关键词： Reactive power optimization graph neural network distribution network machine learning data-driven

A Least-squares-based Iterative Method with Better Convergence for PF/OPF in Integrated Transmission and Distribution Networks

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 953-962页

作者： Kunjie Tang Shufeng Dong Yonghua Song College of electrical engineering Zhejiang UniversityHangzhou 310027China State Key laboratory of Internet of Things for Smart City and Department of electrical and Computer engineering University of MacaoMacao SARChina IEEE

The limitations of the conventional master-slavesplitting(MSS)method,which is commonly applied to power flow and optimal power flow in integrated transmission and distribution(I-T&D)networks,are first *** that the MSS method suffers from a slow convergence rate or even divergence under some circumstances,a least-squares-based iterative(LSI)method is *** with the MSS method,the LSI method modifies the iterative variables in each iteration by solving a least-squares problem with the information in previous iterations.A practical implementation and a parameter tuning strategy for the LSI method are ***,a LSI-PF method is proposed to solve I-T&D power flow and a LSIheterogeneous decomposition(LSI-HGD)method is proposed to solve optimal power *** experiments demonstrate that the proposed LSI-PF and LSI-HGD methods can achieve the same accuracy as the benchmark ***,these LSI methods,with appropriate settings,significantly enhance the convergence and efficiency of conventional ***,in some cases,where conventional methods diverge,these LSI methods can still converge.

关键词： Fixed-point theory integrated transmission and distribution networks least-squares-based iterative method master-slave-splitting method optimal power flow power flow