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Analyzing Characters of Plasma Wake with Method of Chaos Dynamics

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Chinese Physics Letters 1998年第12期15卷 889-891页

作者： CAO Jin-xiang FANG Jian-dong ZHAO Hong-bo LIN Yi-jun ZHANG Jia-xiang WANG Jie-xia dong yong-hui Department of Modern Physics University of Science and Technology of ChinaHefei 230027 Beijing Institute of Aerodynamics Beijing 100074

In this paper,analyzing the experiment data of multiple scanning probes in the arc wind-driven hypersonic plasma flows with the chaos dynamics method,we have obtained the power spectrum,the frequency wavenumber spectral density,the correlation dimension and Kolmogorov entropy of the flows,*** distribution of correlation dimension and Kolmogorov entropy of the blunt cone wakes along the axis and the radius of the flows are presented successfully in the *** distributions clearly show the structure of turbulence and lamination in blunt cone *** the method of minimum Kolmogorov entropy,we observed the structure of the bow shock at far wake region in the blunt cone wakes.

关键词： entropy flows dimension

Remote sensing of air pollution incorporating integrated-path differential-absorption and coherent-Doppler lidar

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Defence Technology（防务技术） 2024年第1期31卷 594-601页

作者： Ze-hou Yang yong Chen Chun-li Chen yong-ke Zhang Ji-hui dong Tao Peng Xiao-feng Li Ding-fu Zhou School of Physics Beijing Institute of TechnologyBeijing 100081China Southwest Institute of Technical Physics Chengdu 610041SichuanChina School of Optics and Photonics Beijing Institute of TechnologyBeijing 100081China

An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and *** system incorporates integrated-path differential absorption lidar(DIAL) and coherent-doppler lidar(CDL) techniques using a dual tunable TEA CO_(2)laser in the 9—11 μm band and a 1.55 μm fiber *** combining the principles of differential absorption detection and pulsed coherent detection,the system enables agile and remote sensing of atmospheric *** static tests validate the system’s real-time detection capabilities,including the measurement of concentration-path-length product(CL),front distance,and path wind speed of air pollution plumes over long distances exceeding 4 *** experiments is conducted with the *** of the pollutant concentration and the wind field is carried out in an approximately 1 km slant range over scanning angle ranges from 45°to 65°,with a radial resolution of 30 m and10 *** test results demonstrate the system’s ability to spatially map atmospheric pollution plumes and predict their motion and dispersion patterns,thereby ensuring the protection of public safety.

关键词： Differential absorption LIDAR Coherent Doppler lidar Remoting sensing Atmospheric pollution

A New Method for Solving Nonlinear Partial Differential Equations Based on Liquid Time-Constant Networks

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Journal of Systems Science & Complexity 2024年第2期37卷 480-493页

作者： SUN Jiuyun dong Huanhe FANG yong College of Mathematics and Systems Science Shandong University of Science and TechnologyQingdao 266590China

In this paper,physics-informed liquid networks(PILNs)are proposed based on liquid time-constant networks(LTC)for solving nonlinear partial differential equations(PDEs).In this approach,the network state is controlled via ordinary differential equations(ODEs).The significant advantage is that neurons controlled by ODEs are more expressive compared to simple activation *** addition,the PILNs use difference schemes instead of automatic differentiation to construct the residuals of PDEs,which avoid information loss in the neighborhood of sampling *** this method draws on both the traveling wave method and physics-informed neural networks(PINNs),it has a better physical ***,the KdV equation and the nonlinear Schr¨odinger equation are solved to test the generalization ability of the *** the best of the authors’knowledge,this is the first deep learning method that uses ODEs to simulate the numerical solutions of PDEs.

关键词： Nonlinear partial differential equations numerical solutions physics-informed liquid networks physics-informed neural networks

Graphitic carbons:preparation,characterization,and application on K-ion batteries

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Rare Metals 2024年第9期43卷 4056-4075页

作者： Kang-Zhe Cao Jia-hui Ma Yu-Lian dong Yu Duan Run-Tian Zheng Dharani Bundhooa hui-Qiao Liu yong Lei College of Chemistry and Chemical Engineering Xinyang Normal UniversityXinyang 464000China Xinyang Key Laboratory of Low-Carbon Energy Materials Xinyang 464000China Fachgebiet Angewandte Nanophysik Institut fur Physik&IMN MacroNanoTechnische Universitat Ilmenau98693 IlmenauGermany Laboratory of Inorganic Materials Chemistry(CMI) University of NamurB-5000 NamurBelgium

K-ion batteries(KIBs)have drawn much attention due to the abundant potassium reserves and wide accessibility as well as high energy density,which can be designed for large-scale energy storage *** the most promising anode materials for KIBs,graphitic carbons,especially those with an intermediate structure between the crystalline graphite and amorphous carbons become a hot research focus because of the improved rate capability and enhanced diffusion-controlled capacity at low voltage ***,we first review the structures of graphitic carbons in the view of graphitic domains and the structure changes in their K-ion intercalation ***,we summarize the preparation mechanisms and characterizations of graphitic carbons and the influence factors in their degree of ***,we illustrate the strategies to optimize their K-ion storage properties from four aspects,namely graphitic domain design,microstructure engineering,electrochemical active component regulation,and defect ***,we propose the issues that urgently need to be solved in graphitic carbons and the possible *** hope that this view could offer some inspiration for the further designing and optimizing of graphitic carbons for practical KIBs.

关键词： Graphitic carbon K-ion battery Anode Graphite Structure design

Significantly Enhanced Energy Storage Performances of PEI-based Composites Utilizing Surface Functionalized ZrO_(2) Nanoparticles for High-Temperature Application

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Chinese Journal of Polymer Science 2024年第3期42卷 322-332,I0006页

作者： Qing-Qing Liu Qiu-Hao Lin Xiao-dong Qi Nan Zhang Ting Huang Jing-hui Yang yong Wang School of Chemistry Southwest Jiaotong UniversityChengdu 610031China Key Laboratory of Advanced Technologies of Materials Ministry of Education of ChinaSouthwest Jiaotong UniversityChengdu 610031China

Polymer dielectrics with a high energy density and an available energy storage capacity have been playing an important role in advanced electronics and power systems. Nevertheless, the use of polymer dielectrics in harsh environments is limited by their low energy density at high temperatures. Herein, zirconium dioxide(ZrO_(2)) nanoparticles were decorated with amino group utilizing 4,4-methylenebis(phenyl isocyanate)(AMEO) and successfully incorporated into polyetherimide(PEI) matrix. The dielectric properties, breakdown strength, and energy storage performances of PEI/ZrO_(2)-AMEO nanocomposites were investigated from 25 ℃ to 150 ℃. It is found that the combination of moderate bandgap ZrO_(2) with modest dielectric constant and polar groups at interface with deep trap can offer an available strategy to simultaneously increase the dielectric constant and breakdown strength of polymer dielectrics. As a result, the composites containing ZrO_(2)-AMEO exhibit excellent energy storage performance at elevated temperatures. Specially, the PEI-based composites with 3 vol% ZrO_(2)-AMEO display a maximum discharged energy density(U_(d)) of 3.1 J/cm^(3) at 150 ℃, presenting 90% higher than that of neat PEI. This study may help to better develop the polymer-based dielectric composite applied at elevated temperatures.

关键词： Polyetherimide High temperature dielectric ZrO_(2) Interface

Identification of Motor Nuclei in the Medulla Oblongata of Carp for Biological Control

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Journal of Bionic Engineering 2024年第2期21卷 842-851页

作者： Yang Zhao yong Peng Yudong Wen Lingjun Han Yanhong Yan Xueying dong hui Zhang Zheng Zhao Xiaoyue Liu School of Electrical Engineering Yanshan UniversityQinhuangdao066004China School of Mechanical Engineering Yanshan UniversityQinhuangdao066004China Key Laboratory of National Defense of Mechanical Structure and Material Science Under Extreme Conditions Yanshan UniversityQinhuangdao066004China Institute of Marine Science and Engineering Yanshan UniversityQinhuangdao066004China Shijiazhuang University Shijiazhuang050035China

Brain-controlled technology is the key technology in biological control,and the corresponding relationship between animal brain nuclei and motor behavior is the *** purpose of this study was to explore the motor nuclei of the medulla oblongata in *** carps were subjected to electrical stimulation and chemical stimulation experiments,respectively,in the water-free state,and the effective chemical stimulation sites were injected with the pontamine sky blue *** brain tissue sections were obtained by paraffin tissue section technology and the neutral red staining *** comparing the positions of the brain nuclei shown in earlier studies,the motor nerve nuclei in the medulla oblongata were *** brain electrode was implanted into the motor nucleus of the medulla oblongata,and the underwater control experiment and behavioral tests were carried out with different electrical stimulation *** results showed that the abducens nucleus(NVI)was the motor nucleus that controls the ipsilateral steering,and the facial nucleus(NVII)was the motor nucleus that controls the forward *** adjusting the stimulation voltage and the stimulation pulse number,the carp can be stably controlled to achieve a left–right steering motion of 30°–180°and a forward motion of more than 80 cm/*** study indicated that the quantitative control of the steering and forward behavior of the carp can be achieved by electrical stimulation of the NVI and NVII,which provided a certain experimental basis for the accurate control of the carp robot.

关键词： Biological control Carp Medulla oblongata motor nucleus Electrical stimulation technique Chemical stimulation technique

Machine learning for carbonate formation drilling: Mud loss prediction using seismic attributes and mud loss records

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Petroleum Science 2024年第2期21卷 1241-1256页

作者： hui-Wen Pang Han-Qing Wang Yi-Tian Xiao Yan Jin Yun-Hu Lu yong-dong Fan Zhen Nie National Key Laboratory of Petroleum Resources and Engineering China University of Petroleum(Beijing)Beijing102249China College of Science China University of Petroleum-BeijingBeijing102249China Petroleum Exploration and Production Research Institute SINOPECBeijing102206China College of Petroleum Engineering China University of Petroleum-BeijingBeijing102249China Research Institute of Petroleum Exploration and Development CNPCBeijing100083China

Due to the complexity and variability of carbonate formation leakage zones, lost circulation prediction and control is one of the major challenges of carbonate drilling. It raises well-control risks and production expenses. This research utilizes the H oilfield as an example, employs seismic features to analyze mud loss prediction, and produces a complete set of pre-drilling mud loss prediction solutions. Firstly, 16seismic attributes are calculated based on the post-stack seismic data, and the mud loss rate per unit footage is specified. The sample set is constructed by extracting each attribute from the seismic trace surrounding 15 typical wells, with a ratio of 8:2 between the training set and the test set. With the calibration results for mud loss rate per unit footage, the nonlinear mapping relationship between seismic attributes and mud loss rate per unit size is established using the mixed density network ***, the influence of the number of sub-Gausses and the uncertainty coefficient on the model's prediction is evaluated. Finally, the model is used in conjunction with downhole drilling conditions to assess the risk of mud loss in various layers and along the wellbore trajectory. The study demonstrates that the mean relative errors of the model for training data and test data are 6.9% and 7.5%, respectively, and that R2is 90% and 88%, respectively, for training data and test data. The accuracy and efficacy of mud loss prediction may be greatly enhanced by combining 16 seismic attributes with the mud loss rate per unit footage and applying machine learning methods. The mud loss prediction model based on the MDN model can not only predict the mud loss rate but also objectively evaluate the prediction based on the quality of the data and the model.

关键词： Lost circulation Risk prediction Machine learning Seismic attributes Mud loss records

Physical informed memory networks for solving PDEs:implementation and applications

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Communications in Theoretical Physics 2024年第2期76卷 51-61页

作者： Jiuyun Sun Huanhe dong yong Fang College of Mathematics and Systems Science Shandong University of Science and TechnologyQingdao 266590China

With the advent of physics informed neural networks(PINNs),deep learning has gained interest for solving nonlinear partial differential equations(PDEs)in recent *** this paper,physics informed memory networks(PIMNs)are proposed as a new approach to solving PDEs by using physical laws and dynamic behavior of *** the fully connected structure of the PINNs,the PIMNs construct the long-term dependence of the dynamics behavior with the help of the long short-term memory ***,the PDEs residuals are approximated using difference schemes in the form of convolution filter,which avoids information loss at the neighborhood of the sampling ***,the performance of the PIMNs is assessed by solving the Kd V equation and the nonlinear Schr?dinger equation,and the effects of difference schemes,boundary conditions,network structure and mesh size on the solutions are *** show that the PIMNs are insensitive to boundary conditions and have excellent solution accuracy even with only the initial conditions.

关键词： nonlinear partial differential equations physics informed memory networks physics informed neural networks numerical solution

On hypersurfaces of H2×H2

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Science China Mathematics 2024年第2期67卷 339-366页

作者： dong Gao hui Ma Zeke Yao School of Science Beijing University of Civil Engineering and Architecture Department of Mathematical Sciences Tsinghua University

In this paper, we study hypersurfaces of H2× H2. We first classify the hypersurfaces with constant principal curvatures and constant product angle functions. Then we classify homogeneous hypersurfaces and isoparametric hypersurfaces, respectively. Finally, we classify the hypersurfaces with at most two distinct constant principal curvatures, as well as those with three distinct constant principal curvatures under some additional conditions.

关键词： constant principal curvature homogeneous hypersurface isoparametric hypersurface 53C42 53B25 53C40