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numerical simulation and analysis of lithium plasma during low-pressure DC arc discharge

Plasma science and technology 2019年第4期21卷 16-21页

作者： Runhui WU Song CHAI Jiaqi LIU Shiyuan CONG Gang MENG National Key Laboratory of Science and Technology on Test Physics&Numerical Mathematics Beijing 100076People's Republic of China School of Physics Dalian University of TechnologyDalian 116024People's Republic of China

Alkali metal DC arc discharge has the characteristics of easy ionization,low power consumption,high plasma temperature and ionization degree,etc,which can be applied in aerospace vehicles in various *** this paper,we calculate the physical property parameters of lithium vapor,one of the major alkali metals,and analyze the discharge characteristics of lithium plasma with the magnetohydrodynamic(MHD)*** discharge effects between constant current and voltage sources are also *** is shown that the lithium plasma of DC arc discharge has relatively high temperature and current *** peak temperature can reach tens of thousands of K,and the current density reaches 6 x 107 A m *** the same rated power,the plasma parameters of the constant voltage source discharge are much higher than those of the constant current source discharge,which can be used as the preferred discharge mode for aerospace applications.

关键词： DC discharge lithium plasma numerical simulation low-pressure arc

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Adaptive-Correlation Back-Projection Imaging Algorithm for Ground Penetrating Radar in Complex Scenes

Adaptive-Correlation Back-Projection Imaging Algorithm for G...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Qianqi Dai Gao Lu Tao Jiang Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin Engineering University Harbin China National Key Laboratory of Science and Technology on Test Physics and umerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China

The current correlation back-projection algorithm can only deal with the imaging of objects at the same buried depth. However, for objects with different depths and different relative permittivity, the electromagnetic wave echo composition is complicated, there is no strong correlation between the time delays of the reflected echoes, the echo signal in the center of the detection area is used as a reference signal to perform consistent correlation processing, which will cause serious suppression. In this paper, an improved adaptive correlation algorithm was proposed. Firstly, the algorithm of maximum variance between clusters (OSTU) is used to extract the horizontal position and number of buried objects, and then the relevant parameters are adaptively adjusted according to the reflected energy and horizontal position of different targets. Finally, back-projection algorithm imaging is performed. Simulation experiments showed that the algorithm proposed in this paper can effectively improve the imaging effect, improve the detection probability of buried objects, and adapt to the variability of detection scenes.

关键词： Adaptation models Correlation Ground penetrating radar Delay effects Computational modeling Electromagnetic scattering Clustering algorithms

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Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

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Advances in Atmospheric sciences 2024年第7期41卷 1299-1312页

作者： Ya WANG Gang HUANG Baoxiang PAN Pengfei LIN Niklas BOERS Weichen TAO Yutong CHEN BO LIU Haijie LI State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China Earth System Modelling School of Engineering and DesignTechnical University of MunichOttobrunn 85521Germany Potsdam Institute for Climate Impact Research Potsdam 14412Germany Department of Mathematics and Global Systems Institute University of ExeterExeter EX44QEUK CMA Earth System Modeling and Prediction Centre(CEMC) Chinese Academy of Meteorological SciencesBeijing 100081China

Climate models are vital for understanding and projecting global climate change and its associated ***,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future *** these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning ***,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST ***,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to ***,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to *** enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales *** study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

关键词： generative adversarial networks model bias deep learning El Niño-Southern Oscillation marine heatwaves

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Cooperative Jamming Resource Allocation Based on Artificial Bee Colony Multi-objective Decomposition

Cooperative Jamming Resource Allocation Based on Artificial ...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Gao Lu Qianqi Dai Jiechen Xia National Key Laboratory of Science and Technology on Test Physics and umerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin Engineering University Harbin China

Electromagnetic countermeasure plays an important role in modern warfare. Cooperative jamming is one of the main means to counter radar network. In order to improve jamming efficiency, a jamming resource allocation algorithm based on artificial bee colony multi-target decomposition is proposed in this paper. The algorithm takes into account the interference effect and cost, and uses the decomposition mechanism to improve the search efficiency. The simulation results show that the allocation solution set obtained by this algorithm has good performance in diversity and spacing.

关键词： Costs Simulation Radar Interference Computational electromagnetics Artificial bee colony algorithm Radar countermeasures

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Intelligent Counter Guidance Regulated by Deep Reinforced Learning

Intelligent Counter Guidance Regulated by Deep Reinforced Le...

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IEEE Metrology for Aerospace

作者： Runle Du Jiaqi Liu Li Zhang Jianhua Li National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (数字)9781728166360

ISBN: (纸本)9781728166377

In the game of pursuit and evasion in outer space, it is of utmost importance for the evader to make appropriate maneuver to survive this challenge. In previous publications, the common approach of guidance behavior recognition and counteracting evasion approach is based on model matching or multi-model matching. In that genre, due to the limitation of approximation from model matching and imperfection of state information, it is very difficult for the evader to take optimal maneuver when the pursuer uses unknown tracking algorithms. To solve this problem, in this article, deep neural network and reinforced learning are applied in counteractive maneuver. In the proposed approach, two networks are applied. Guidance recognition network is a pre-trained deep network able to estimate guidance behavior of pursuer vehicle, and the maneuver control network is trained by deep reinforced learning to perform counteract evading maneuver control. Exploring the policy space with Monte Carlo method, the maneuver controller deep neural network evolved to make optimal control acceleration and succeed in the evasion. Digital simulations confirmed that in the game of pursuit and evasion, deep reinforced learning with Monte Carlo method has the ability to guide the evader during the interception with improved chance of survival.

关键词： Neural networks Training Acceleration Monte Carlo methods Kinematics Games Space exploration

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Modulation recognition of emitter signals based on SDAE-ODCNN 5

Modulation recognition of emitter signals based on SDAE-ODCN...

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IET International Radar Conference 2020, IET IRC 2020

作者： Wang, Xu Gao, Jingpeng Gao, Lu Wang, Fu College of Information and Communication Engineering Harbin Engineering University Harbin China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China

ISBN: (纸本)9781839535635

In order to improve the recognition rate of emitter signals modulation under low signal noise ratio (SNR), an end-to-end method based on the stacked denoising autoencoder (SDAE) - one dimensional convolutional neural network (ODCNN) is proposed in this paper. The SADE-ODCNN is designed in this method and trained through a two-step training. In the SDAE-ODCNN model, the encoder of the SDAE can extract the denoised and compressed features of the received emitter signals. Then the ODCNN can further extract features to realize the recognition. The simulation results show that the average recognition rate of the method can reach 0.94 under 0dB. Thus the proposed method has a good application in the field of emitter signals modulation recognition. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Modulation

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A unified back-projection correction algorithm for squint SAR based on SPECAN processing

A unified back-projection correction algorithm for squint SA...

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2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019

作者： Wang, Chao Sun, Heng Zhang, Xin-Yu Zhang, Ran National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (纸本)9781728123455

The missile-borne or airborne synthetic aperture radar (SAR) usually adopts the squint mode and subaperture to satisfy maneuvering and the real-time processing. A realtime imaging algorithm of squint SAR based on SPECAN processing is presented. It has high computational efficiency in low resolution. A unified back-projection algorithm is proposed to solve the problem of fan-shaped distortion and geometric distortion. Simulation results validate the effectiveness of the proposed method. © 2019 IEEE.

关键词： Computational efficiency

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Intelligent Assignment Strategy for Multi-Target Adversarial Interception

Intelligent Assignment Strategy for Multi-Target Adversarial...

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Chinese Automation Congress (CAC)

作者： Yang Yu Yizhong Fang Han Wu Tuo Han Qinglei Hu School of Automation Science and Electrical Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China School of Aeronautic Science and Engineering Beihang University Beijing China Beihang Hangzhou Innovation Institute (Yuhang) Hangzhou China

The multi-missile confront multi-target is a classic target allocation issue in the combat scenario of multiple missiles intercepting multiple maneuvering targets. Traditional algorithms lack environmental assessment model, train quality, and indicator function in the adversarial environment. To this end, this paper aims to propose an intelligent assignment strategy which contains indicator function and evaluation model. Then, an indicator function and an evaluation model considering the miss distance, threat situation, and the number of specified interception targets are introduced into the reinforcement learning algorithm. The local and global reward functions are introduced to improve the training convergence and efficiency in the multi-missile multi-target confrontation scenario. Finally, simulation results are designed to check on advantage of intelligent allocation strategy.

关键词： Training Missiles Analytical models Automation Simulation Reinforcement learning Resource management

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A Triple-layer Frequency Selective Surface with Flat Wide Passband 5

A Triple-layer Frequency Selective Surface with Flat Wide Pa...

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5th IEEE International Conference on Computational Electromagnetics, ICCEM 2019

作者： Cui, Yichun Zhang, Shengjun Wang, Mingliang National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (纸本)9781538671115

In this paper, a novel triple-layer band-pass Frequency selective surface (FSS) with wide passband and low insertion loss is proposed. The proposed FSS is composed of three FSS layers and two dielectric substrates which are symmetric vertically. This structure realizes a three-order response and wide stop band with steep falling edge. Equivalent circuit analysis indicates that the three-order response is generated by resonance of FSS layers and coupling between layers, respectively. After optimization, the passband of proposed FSS ranges from 7.728GHz to 12.31GHz, whose fractional bandwidth reaches 44.5% with -0.044dB insertion loss. Meanwhile, this FSS has stable performance for TE polarization under oblique incidence. © 2019 IEEE.

关键词： Frequency selective surfaces

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Perturbation Estimated Incremental Guidance for Exo-Atmospheric Interception

Perturbation Estimated Incremental Guidance for Exo-Atmosphe...

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Chinese Automation Congress (CAC)

作者： Yuting Lu Peng Liu Tuo Han Qinglei Hu School of Automation Science and Electrical Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China School of Aeronautic Science and Engineering Beihang University Beijing China Beihang Hangzhou Innovation Institute (Yuhang) Hangzhou China

In order to meet the requirement of accurate intercept against the increased target maneuverability and external disturbance, a second-order inertial delay based incremental guidance law (IDIASMG) is proposed for an exo-atmospheric interceptor. Specifically, a three-dimensional guidance model is transformed into an incremental version. As a guidance design benchmark, a conventional sliding mode guidance law (SMG) is presented, and a sliding mode incremental guidance law (ISMG) is designed with gain adaptation. Moreover, a second-order inertial delay filter is utilized to estimate and compensate guidance perturbation including the target maneuver, system uncertainty, and external disturbance. Theoretical analysis shows that the incremental guidance requires smaller gains to ensure smaller system residual than the conventional SMG. Extensive numerical simulations validate the effectiveness and robustness of IDIASMG.

关键词： Solid modeling Uncertainty Adaptive systems Upper bound Navigation Perturbation methods numerical simulation

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