bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the application of vertical axis wind turbine in subway tunnel
Authors: Yu Xin , Wang Zheng , Xiang Pei 
Published: December 2022

Abstract
When the subway train is running at high speed in the tunnel, the originally still air in the tunnel is pushed by the train, so that the air in the tunnel is immediately accelerated, and in the same direction as the train travels, which is called the piston effect in the tunnel, also known as Piston wind. The wind speed of the piston wind in the tunnel is 7~9m/s, and the air volume is considerable. The vertical axis wind turbine has the characteristics of small size, low starting wind speed and high wind energy utilization rate, so it can use piston wind to generate electricity to supply power to lighting equipment and advertising lights in the tunnel, so as to achieve the purpose of energy saving and emission reduction.
The silicon-based anode in lithium-ion battery
Authors: Liu Yuyang 
Published: December 2022

AbstractLithium-ion batteries are now widely used in our society. Developing advanced anode material to improve the property of Lithium-ion batteries has aroused more and more attention in recent years. The silicon-based material is one of the most popular materials for the anode owning to the unique advantages of theoretically high capacity, low operating point, rich material resources, and environmental friendliness. However, the decay of capacity fading during the cycling resulting from huge volume change and poor conductivity of this kind of anode material significantly limited the applications. Thus, novel strategies need to be developed urgent. For this scope, the silicon-based components with different materials and structures have been developed. Here we summarized a series of silicon-based components, involving in oxide composite materials, silicon/metal oxide composite materials, Si/Carbon nanotubes composite materials, and graphene composite material, from the aspects of the preparation process, microstructure, and performance of these silicon-based anode materials.
Performance of Lithium Ion Battery with Graphene Microstructure in Cathode
Authors: Ye Zhanqiang 
Published: December 2022

Abstract
Lithium-ion battery is a promising energy source with high output voltage, large energy density, low auto discharge, and no memory effect. Graphene, as a dimensional carbon material, has excellent electrical conductivity, strong mechanical properties, a large specific surface area, which has been widely applied in lithium-ion battery for modifying the cathode material of lithium secondary batteries, thus significantly promoting the flow performance, conductivity, and cycling stability of Li secondary batteries. In this review, we discussed the excellent properties of various cathode materials based on graphene with different microstructures including three dimensional network structure, Core/Shell structure, layered structure, porous structure, and sandwich structure, which could provide motivations for improving the performance of the lithium-ion battery.
Control strategy for grid-connected inverters based on STATCOM reactive power compensation Research
Authors: Li Shuang , Jia Wenchao , Wang Sizhong , Yu Zonglai 
Published: December 2022

Abstract
The problem of grid-connected inverter reactive power compensation becomes a decisive factor for grid-connected power quality. To ensure the system unit power factor operation, this paper designs a reactive power compensation control strategy for grid-connected inverters based on STATCOM. On the basis of detailed analysis of the working principle of STATCOM, the grid-connected inverter model is built with the help of MATLAB simulation environment. The experimental results show that the use of STATCOM for grid-connected inverter reactive power compensation ensures stable grid-side output voltage of the grid-connected inverter and can improve the power factor of the system at the same time, which has certain reference significance for upgrading the grid-connected inverter design.
Research on multi-sensor fusion-based AGV positioning and navigation technology in storage environment
Authors: Yuan Chuanqian , Wang Ye , Liu Jun 
Published: December 2022

Abstract
Aiming at the problems of low positioning accuracy and large trajectory deviation when AGVs work in dynamic storage environments, an AGV positioning and navigation method based on multi-sensor data fusion is studied. The method is based on traceless Kalman filter (UKF) and adaptive Monte Carlo localisation (AMCL) algorithms to fuse three kinds of sensor data, namely LiDAR, inertial guidance system and ultra-wideband positioning system, to finally output the accurate attitude of the AGV [1]. Remoting data communication between the AGV and the host computer through TCP protocol, and the host computer remotely controls the AGV to achieve autonomous positioning and navigation after the sensor data is fused. Experiments are carried out on a MATLAB simulation experiment platform, and the results show that the positioning and navigation system has high positioning accuracy and trajectory fitting, and has certain practicality in dynamic storage environment.
RLS-based BeiDou Satellite High Precision Positioning for Power Device
Authors: Peng Ziping , Guo Kun , Yu Sheng , Ma Tao , Zhang Diecong 
Published: December 2022

Abstract
The BeiDou-3 navigation satellite system (BDS-3) has been officially put into use, which will provide wider, more accurate, and smarter industrial applications. BDS-3 positioning has advantages of stability, economical reliability and most importantly, high positioning accuracy, which is widely used in power systems, covering power dispatching, energy management, data acquisition, and system monitoring. However, in the positioning process of BDS-3, positioning accuracy will be affected by spatial and temporal interference factors. This paper addresses the problem of poor positioning accuracy under the interference influence of BDS-3, and proposes a Recursive Least Squares (RLS)-based adaptive high-precision positioning scheme to effectively reduce the influence of interference factors.
Open Capacity Model of Medium Voltage Transmission Line in Distribution Network Based on Load Data
Authors: Zhang Wei , Meng Xiaoli , Li Rui , Chen Hai , Gu Yi , Zhang Yi , Zhang Jialei 
Published: December 2022

Abstract
Due to the influence of load fluctuation, the power supply stability of distribution network is insufficient. Therefore, the open capacity model of medium voltage lines in the distribution network is constructed by using load data. Based on the introduction of time parameter, the load pressure of the distribution network is calculated by using the peak load of distribution network. According to the relationship between the pressure value of sustainable load of the distribution network and the pressure value under the actual power load, the open capacity model of medium voltage lines is constructed. The test results show that when the design model is used to set the open capacity of medium voltage lines, the fluctuation of the expected outage time and frequency of the distribution network system is small, which indicates that the stable power supply can be realized
Technical research of the Intelligent substation’s secondary maintenance safety measure system
Authors: Dong Haitao , Xu Yingjie , Wang Tao , Lin Guihua , Wang Yuying , Gao Zhanjun 
Published: December 2022

Abstract
Major changes have taken place during the secondary equipment maintenance and isolation of the intelligent substation and conventional substation in that the physical connection of the conventional cable has become invisible and not to be touched. This change, no undoubtedly, has added the difficulty for the relay protection staff to operate. The secondary maintenance safety measure system of the intelligent substation described in this thesis can automatically complete the writing and implementation of the secondary safety measure sheet by adopting Groovy rules and self-learning fuzzy inference mechanism. The safety measure system expert data base has been continuously improved through manual correction and self-learning technology, which has greatly improved the work efficiency of the site operators, and reduced the impact of the wrong implementation of the secondary safety measures on the normal operation of the power system.
Application of IEC60870-5-101 in distribution automation terminal remote operation and maintenance
Authors: Li Kewen , Chen Qianyi , Ou Shifeng , Chen Shaonan , Zhang Wei 
Published: December 2022

Abstract
The characteristics, structure of extended remote operation and maintenance protocol based on IEC60870-5-101, the normal or abnormal communication process of remote maintenance are introduced, and the transmission of operation and maintenance data between distribution master stations and distribution terminal units is effectively standardized. This paper expounds some common problems and solutions of remote maintenance under current wireless public network communication mode.
Research on emergency repair strategy based on load grade and economy
Authors: Sun Xiaoguang , Geng Jianyu , Geng Bin , Liu Kai , Hou Xu , Wang Yuanzhi 
Published: December 2022

Abstract
Distribution network plays the role of distributing electric energy in the power system, whether it can run normally relates to people’s production and life. In recent years, frequent natural disasters have caused large-scale failures of distribution networks, resulting in the interruption of a large number of load power supply, which has a huge impact on people’s lives and post-disaster recovery work. Therefore, it is very important to formulate scientific and efficient emergency repair strategies. This paper will study the power supply recovery and multi-fault rush repair of distribution network respectively from the two aspects of load grade and the economy of power grid operation, establish mathematical model, and use particle swarm optimization algorithm to solve, so as to provide a more efficient emergency plan for power supply recovery after disaster.
Research of 3D trajectory Hovering Points Determination Method of UAV Patrol Inspection Transmission Tower
Authors: Xu Li , Guo Hao , Fu Yanyi , Wang Zhigang , Li Zhihui , Hua Zoude , Li Peng , Luo Changhong , Wang Peng , Wei Yi , Chen Bin , Liu Shushan 
Published: December 2022

Abstract
It is necessary to set UAV hovering points before programming the trajectory of a UAV patrol inspection transmission tower body and accessories such as fittings and insulators. The choice of the hover point will affect the work safety and inspection efficiency of the UAV. Therefore, a 500kV UHV AC double-drum tower and UAV three-dimensional simulation model are established and Electromagnetic field is emulated at first. Finally, UAV hovering points are determined by considering the simulation results and functional parameters of UAV. The research method is of great significance for the determination of 3D trajectory Hovering Point Determination Method of UAV Patrol Inspection Transmission Tower.
Research on transformer fault voiceprint recognition based on Mel time-frequency spectrum-convolutional neural network
Authors: Wang Sen , Zhao Bingnan , Du Jianmin 
Published: December 2022

Abstract
A series of faults will occur during the operation of the transformer, which will aggravate its vibration and noise signals to a certain extent. In order to realize the detection and recognition of transformer related faults during uninterrupted operation, a voiceprint recognition model based on Mel time spectrum convolution neural network is proposed in this paper. According to the sound signal collected by the transformer in actual operation, Mel time domain spectrum as a data set of deep learning model can be obtained through feature extraction preprocessing and Mel filter dimensionality reduction. On this basis, the Mel time domain spectrum convolution neural network deep learning model is constructed, and Adam is used as the optimizer to optimize the data set through the super parameter optimization combination with multi classification cross entropy as the loss function, so as to realize the voiceprint recognition under four different operating faults of the transformer. The simulation results show that the identification model proposed in this paper is feasible and effective in fault identification.
Optimization and application of parameter identification error algorithm for steam turbine governing system
Authors: Zhu Longfei , Si Paiyou , Liu Shuangbai , Mei Long , Xie Changya , Zhang Teng , Hu Yuou 
Published: December 2022

Abstract
The parameter identification of the steam turbine speed governing system needs to be realized by the fitting of the measured response curve of the steam turbine active power. The national standard puts forward strict requirements on the error of the identification result. At present, error calculation is often realized by manual punctuation, which is a complicated process and greatly influenced by human judgment. Hence it needs to be improved urgently. In this paper, polynomial fitting and improved sliding window method are used to optimize the error identification algorithm of the steam turbine active power response curve. The visualization of the program is realized based on the Python language. The algorithm improves the data processing efficiency and reduces the influence of human judgment. The calculation results meet the standard requirements.
Short-term photovoltaic power generation power prediction method based on SOA-BP neural network
Authors: Wang Zeliang , Liang Huang 
Published: December 2022

Abstract
The size of photovoltaic power generation has a certain uncertainty, which affects the quality of photovoltaic power generation, and affects the safety and stable operation of the power grid. By predicting the photovoltaic power generation, this problem can be better solved. A photovoltaic power generation power prediction method combining SOA (Seagull optimization algorithm) and BP neural network is proposed. The convergence speed of BP neural network prediction model is relatively slow, and it is easy to fall into local optimum. Optimizing its weights and thresholds through SOA can improve these situations. Through experiments, Through experimental comparison, it is found that the BP neural network method optimized by seagull algorithm has higher accuracy in predicting photovoltaic power generation.
Single-phase Grounding Fault Location Technology Based on Edge Calculation of Fault Components of the Positive-sequence Current
Authors: E Zhenwei , Liu Jiulong , Wu Yingming , Yu Zhengzhi , Zhao Chuanzong , Yu Chunyan , Yuan Chengye 
Published: December 2022

Abstract
In the one-phase-to-ground fault of the distribution network, due to the difference in the distribution of the positive sequence current constituents of each line, the information contained in the fault path and the non-fault path also has a certain difference. On this basis, the edge of the fault constituent in the positive sequence current is used to locate the one-phase grounding. The method first uses phase current subtraction to multiply the period difference before and after the fault, and then uses the inverse transformation before and after the fault to determine the positive and null sequence constituents of the fault. Symmetrical composition. By analysing the amplitudes of the positive sequence and null sequence currents of the three-phase fault constituents, and according to the corresponding relationship between the amplitudes and the adaptive threshold, the location of the fault section is realized. A specific fault point location criterion and steps are given in this paper, and it is verified by ATP simulation software.
Improving the quality of fur semi-finished products due to improving the retanning process
Authors: Garifullina A R , Latfullin I I , Antonova M V , Abdullina V H 
Published: December 2022

Abstract
The article deals with information about the main studies with the identification of the process of retanning using plasma treatment of skin tissues of rabbit skins and non-isocyanate urethanes containing products in order to improving the quality of semi-finished products. The results of research in the chemistry field of tanning compounds and their influence on the characteristic properties and physical and mechanical parameters are given.
Application of high-frequency plasma modification to obtain protective materials with improved sorption properties
Authors: Morozova I I , Tikhonova N V , Timoshina Y A , Voznesensky E F , Faskhutdinova A F 
Published: December 2022

Abstract
In sorption technologies, surface modification of coals is widely used in order to increase their sorption capacity. The most promising method for improving the properties of materials of various structures is high-frequency plasma treatment. It was revealed that after the treatment of sorbents with low-pressure high-frequency capacitive plasma, materials are obtained with properties different from the original sorbent, characterized by increased sorption properties. Processes that affect the kinetics of adsorption and increase the sorption activity of activated carbon have been studied by FTIR spectroscopy.
Optimizing microhardness testing of metallic glasses
Authors: Đulbegović Alem Ben , Bilić Krešimir , Fetić Amra Salčinović 
Published: December 2022

Abstract
There are common protocols and standards for measuring the microhardness of materials. However, measuring this property requires special attention when the materials are tens of microns thick. In this paper, we present the results of measuring the Vickers microhardness of three samples of metallic glasses of significantly different thicknesses. We varied the force and the loading time. In addition, we investigated the influence of mechanical surface treatment on microhardness results. By analyzing the results, we determined the optimal conditions for measuring the microhardness of samples of this geometry.
Joint theoretical and experimental study on elastic electron scattering from a methane molecule
Authors: Vukalovic J , Maljkovic J B , Tökési K , Predojevic B , Marinkovic B P 
Published: December 2022

Abstract
We report on a combined experimental and theoretical study of elastic differential cross section DCS (E, θ) from methane molecule in the intermediate energy range (50-300eV), with experimental results limited to an angle interval of 25 to 125 degrees. Theoretical results are acquired using two approximations: a simple sum of individual atomic cross sections and the other with molecular effect taken into the account. The experimental setup based on a crossed beam technique comprising of an electron gun, a single capillary gas needle, and a detection system with a channeltron was used to measure differential cross sections. The absolute scale for the cross sections is obtained by a relative-flow method using argon gas as a reference. The dependence of DCS on the energy of incident electrons has been considered in detail. The results are analysed and compared with available theoretical and experimental data.
Augmented reality in teaching about physics: first findings from a systematic review
Authors: Vidak A , Movre Šapić I , Mešić V 
Published: December 2022

Abstract
Augmented reality (AR) makes it possible to overlay digital content onto our view of real-world phenomena. This potentially facilitates learning of physics by visualizing connections between concrete physics phenomena and abstract physics formalism. Here we present a part of our systematic review of earlier research on the use of augmented reality (AR) in school and university teaching physics topics. Our systematic review includes 60 articles published between 2012 and 2020, indexed in the Scopus and Eric databases. We analyzed the technological properties of AR for different content areas of physics as well as various methodological aspects of earlier AR research in physics education (e.g., educational level of participants, sample size, and research design). It has been shown that AR becomes increasingly popular in the physics education research community.
Effects of technologically-rich physics homework: findings from an experimental study
Authors: Simić B , Halilović A , Mešić V 
Published: December 2022

AbstractStudents’ learning outcomes in physics are significantly affected by the quality of outside-of-classroom learning experiences. A rich source of these experiences may be the physics homework. In this study, the effects of technologically-rich physics homework were evaluated. To that end a pretest-posttest experimental design has been used. 67 first-year students from the First Bosniak Gymnasium were randomly assigned to one of the three homework approaches. In the control group students received conventional homework about work and energy. Within the simulation-based approach students were expected to interact with simulations to investigate work and energy phenomena, whereas in the video-based approach students learned by analyzing a video in which the teacher interacted with the same simulations as mentioned above. Based on analysis of covariance we could find that the between-group differences on the conceptual posttest were not statistically significant,F(2, 47)=0.59,p=0.56. At the same time, students who learned by interacting with simulations expressed significantly more positive attitudes towards homework, compared to students from the video-based group (mean difference=1.88, p=0.038), as well as compared to students from the conventional group (mean difference=2.02, p=0.03). Simulation-based physics homework may be a powerful tool for helping the students to reach important affective learning outcomes.
An integrative analytical framework and evaluation system of water environment security in the context of agricultural non-point source perspective
Authors: Chen Shouji , Wang Jiayang 
Published: December 2022

Abstract
Agricultural non-point source pollution (ANPSP) caused a contradiction between economic growth and water environmental security protection. In order to understand the trade-off between social-economic development and water environmental security in the context of agricultural non-point source pollution, a Driving force-Agricultural non-point source pollution-Pressure-State-Response (DAPSR) model framework was proposed, and 23 indicators were selected to construct the evaluation system of water environment security in this study. And we take Ya’an City, China as case study from 2017 to 2019, the characteristics of water pollution was analyzed, and the water environment security was evaluated by method of particle swarm projection pursuit. The results show that: (1) Agricultural non-point source pollutant discharge in Ya’an generally shows a decreasing trend. (2) The agricultural non-point source pollution subsystem and the response subsystem have a great impact on water environment security. (3) According to the values of water environment security, Yucheng, Hanyuan, Tianquan and Lushan are basically safe in level III, Mingshan is unsafe in level IV, Yingjing is safe in level II, Shimian and Baoxing are safe in level II. (4) The degree of agricultural non-point sources is highly correlated with the water environment security. This study shows that the DAPSR model is feasible and practical, and can provide a scientific basis for the decision-making of regional agricultural non-point source pollution prevention and water environmental security protection.