bluuebunny/crossref_metadata_2025 huggingface dataset:
An Improved Denoising Method for Optical Fiber Signal
Authors: Guoyou Wang , Weijin Xu , Zhipeng Wang , Shunjie Han , Hong Jiang , Tianqi Lu
Published: July 2021

In the large-capacity FBG sensor network demodulation system, the process of collecting the light source is often accompanied by noise interference. Signal denoising is an important factor that affects the accurate demodulation of the FBG sensor system. Aiming at the problem of constant deviation of soft and hard threshold functions in denoising of traditional wavelet threshold algorithm and the shortcomings of modal aliasing easily in empirical mode decomposition, a modified semi-soft threshold-VMD denoising algorithm is proposed. The simulation results show that the function in this paper is better than the traditional threshold function in continuity and signal reduction degree, and has achieved good results.
Research on Gear Signal Fault Diagnosis Based on Wavelet Transform Denoising
Authors: Li Yuan , Wang Zhuojian , Li Zhe , Li Hao
Published: July 2021

As an important part of modern machinery, gears are safe and reliable directly related to the normal operation of the mechanical system, and when the gears are abnormal, it is very important to carry out fault diagnosis in time and effectively. Wavelet transform is effective in signal time-frequency analysis and fault diagnosis. Based on the wavelet analysis method, this paper first filters and de-noises the vibration signal data of a certain type of gear, and then performs fault analysis. Time-frequency analysis of time-domain signals has a better effect on gear fault diagnosis.
Research on the method of data architecture construction for joint intelligent simulation
Authors: Li Suike , Zhao Yongchao , Wang Haijun
Published: July 2021

In view of the data problems restricting the joint intelligent simulation, this paper constructs a data classification system. By mining and sorting the data, rules and models in cases and experiences, and combining with the basic data and ability data of the relevant system simulation model, it carries on the digital and systematic annotation, constructs the conceptual model, establishes the segmentation and part of speech standards, and adopts the methods of concept mining, attribute mining and instance mining. The data system of joint intelligent simulation is established by mining and instance mapping, and the multi-layer logical template and intelligent matching rules are used to solve the data problems of joint intelligent simulation.
Pedestrian Detection Method Based on Deep Convolution Neural Network
Authors: Mengmeng SHEN , Yong WANG , Jiaqi MA , Chuanguo LI , Liangbo HE , Barnawal Gaurav , Wei SHAN
Published: July 2021

Compared with the traditional pedestrian detection technology, the pedestrian detection technology based on deep learning has achieved overwhelming advantages. However, due to the large scale of deep convolution network, the demand for dedicated processor limits the popularization of pedestrian detection system. To solve these problems, this paper proposes a deep convolution network model with moderate network scale, which improves the universality of the detection model on the premise of ensuring the detection accuracy. Based on the low dimensional shallow convolution neural network, the optimal network structure is found from three aspects of network layer number, sensor field size and characteristic graph, and the final network parameters are determined by guiding experimental evaluation. The pedestrian image to be detected is input into the above network model, and the pedestrian detection result is obtained. The pedestrian detection results on several popular pedestrian databases such as Daimler, MIT and INRIA show that the network structure designed in this paper not only has moderate network size, but also has good detection performance. Cross experiments also verify the robustness and generalization of the algorithm. The work of this article is funded by the undergraduate training program for innovation and entrepreneurship (202010373050, 202010373051, 202010373046).
A denoising algorithm for linear frequency modulation signal based on window function and empirical mode decomposition
Authors: Zhang Kuo
Published: July 2021

The linear frequency modulation signal is widely used in radar, sonar detection and communications as a typical non-stationary signal. In order to better analyse the linear frequency modulation signal received by the receiver, it is necessary to perform denoising processing on the received signal. As a new type of time-frequency analysis method, empirical mode decomposition algorithm is very suitable for processing non-stationary signals. However, due to the large bandwidth of the linear frequency modulation signal, more noise will be retained when the traditional empirical mode decomposition algorithm is used to denoise the linear frequency modulation signal. Under above background, this paper proposes a denoising method based on the window function and the empirical mode decomposition to achieve further denoising of the linear frequency modulation signal. According to the simulation results, when the signal-to-noise ratio is about 0dB, the method proposed in this paper improves the signal-to-noise ratio by about 1.5dB compared with the traditional empirical modal decomposition algorithm.
Improved Harris Corner Detection Algorithm Based on Canny Edge Detection and Gray Difference Preprocessing
Authors: Luo Chuan , Sun Xiaoliang , Sun Xiangyi , Song Junyao
Published: July 2021

Harris corner detection algorithm has been widely used in many computer vision allocations. However, it has low efficiency and accuracy, poor noise immunity and needs to set an artificial threshold. In this paper, an improved algorithm based on Canny edge detection and gray difference preprocessing is proposed. Firstly, Canny edge detection and gray difference preprocessing are used for corner prescreening to improve the detection efficiency, anti-noise, and rotation invariance. Secondly, non-maximum suppression is applied to the screened corners to reduce the number of false corners. Finally, the average of adjacent points method is used to solve the problem of corner cluster, and the detection results are compared the measurement accuracy is improved to sub-pixel level. Experimental results indicate that the proposed algorithm can accurately extract the corners in the image and remove the false corners and corner clusters. It achieves superior performance than existing methods.
Research on CO-word network topic mining and topic differences based on haze microblog data
Authors: Lu Haiyue , Rui Xiaoping , Li Runkui
Published: July 2021

Some studies have shown that haze not only poses a threat to people’s health, but also affects the secretion of human hormones, making people depressed and endangering mental health. Microblog has the advantages of short content, rapid communication and convenient interaction. When the haze comes, a large number of topic microblogs related to the haze will be generated. Mining the topics of concern and psychological reactions contained in these microblogs is helpful for resource allocation and public opinion publicity in the case of haze. At present, the research of microblog topic mining in haze situation only involves a single research area, and few studies discuss the spatial differences of different regions. Based on this, this study collected the microblog data of seven provincial capitals in the severe haze areas in 2017, and used the community-based co word network method to complete a series of experimental steps, such as keyword extraction, co-occurrence matrix construction, co-word network construction and topic community detection. On this basis, we detected the topic community in the microblog data set, and analyzed the horizontal differences of topics in different cities. The results show that different cities have not only the same but also different concerns about haze. The results can provide theoretical guidance for the healthy development of cities.
Semantic query expansion method based on pay-as-yougo fashion for graph model
Authors: Wu Nan , Pan Ying
Published: July 2021

The search requirements of users are usually vague and unclear, and the traditional keyword query method is difficult to obtain satisfactory query results. Therefore, the semantic query expansion technology uses semantic information to modify and extend the initial search requirements of users, to obtain more comprehensive and accurate query results. However, the construction cost of the extended query graph is high, and the existing research is difficult to adjust and optimize the user’s query demand in time, resulting in a poor query effect. To solve the above problems, this paper proposes a semantic expansion method based on pay-as-you-go fashion for graph model: Firstly, the initial query graph is constructed according to the user’s search requirements, and the semantic similarities between the search requirements and knowledge bases are calculated; Then, the extended sets of attribute-values and edges are generate by sorting the similarity value in descending order; Finally, all or part of the elements in the extended set are combined to generate the extended query graph. This method can dynamically adjust and optimize the initial query based on the relevant semantic information in time, and improve the query efficiency and effect.
Identification of Class number of ship radiated noise based on RK-Means algorithm
Authors: Ding Yuanming , Liu Lijia , Yang Yang
Published: July 2021

Ship radiated noise recognition is one of the basic problems in underwater target recognition. To identify the number of ship types according to ship noise, the ship scale can be predicted in advance and the next step of processing can be carried out. Aiming at the problem of identifying the number of ship types based on ship radiated noise, a RK-Means (Recurrent K-Means) is proposed in this paper. According to the short-time energy characteristics of the target signal, the dimension of the feature data is reduced by principal component analysis; The K-Means algorithm is used to cluster and identify the dimension-reduced signals through cyclic iteration; A single connection algorithm is used to determine the appropriate clustering center, which reduces the similarity value of data objects between classes and makes the difference value between classes large. Furthermore, the algorithm can automatically determine the K value, which is the number of ship types. Verified by the experimental data, compared with the contrast algorithm, the K-value recognition result and clustering effect of the RK-Means clustering algorithm are better.
Spectrum Reconstruction Algorithm based on Resource Partition Allocation in Elastic Optical Networks
Authors: Wu Lingyue , Guo Pengfei , Du Li
Published: July 2021

In order to solve the problem of spectrum fragment in elastic optical networks, a spectrum reconstruction algorithm based on resource partition allocation is proposed in this paper. Services are classified according to the different frequency of the services that occupy different number of frequency slots in the networks. Region division of spectrum resources is made according to the type of services and services are allocated in the corresponding spectrum partitions. When defragmenting in the networks, we reconstruct the spectrum for different regions with comprehensively considering the factors in time domain and frequency domain, integrating current resources and preventing the generation of spectrum fragment in the future. Simulation results show that the algorithm can reduce the degree of network fragmentation and reduce traffic blocking.
Color space conversion algorithm and comparison study
Authors: Bi Zhicheng , Cao Peng
Published: July 2021

Purpose The advantages and disadvantages between various conversion algorithms are analyzed, and the relatively optimal conversion algorithm is obtained by comparing color difference, conversion accuracy, and operability. Method Using 729 sets of data from the K = 0% part of the ECI2002 standard color target as samples, experiment 2° was conducted under the D50 light source in the field of view, and the minimum, average, and maximum color differences of C, M, and Y were analyzed and compared by three unused color space conversion algorithms, and the operability of the three algorithms was also analyzed. Phenomenon Of the three algorithms, the polynomial regression algorithm and the neural network algorithm have similar errors, while the Nünchberg equation is less accurate and has a larger error. The operability of each of the three algorithms has advantages and disadvantages. Conclusion The polynomial regression algorithm has the highest accuracy, the lowest error, and the best method.
The research of multi-target tracking based on improved YOLOv3
Authors: Xu Jiawen , Lu Xinbiao , Zhang Chi
Published: July 2021

Multi-target tracking based on detection is a hot topic in the field of computer vision. Aiming at solving the problem of inconvenient application of large network model, this paper proposes a multi-target tracking algorithm based on improved YOLOv3. We use MobileNetV3 to replace the deep network as the backbone of YOLOv3. Compared with Faster R-CNN and YOLOv3, the model of MobileNetV3-YOLOv3 is greatly reduced and the detection speed is improved. Compared with the MobileNetV1-YOLOv3, the accuracy is improved and FPS is higher. The improved YOLOv3 model is used in DeepSORT algorithm for multi-target tracking. The experimental results show that the algorithm used in this paper has the best detecting and tracking effect.
Geographical distribution of liver cancer incidence based on big data analysis
Authors: Tian Yuchi , Huang Qian , Jiang Xiaogang , Chen Guojie , Zheng Chongwei , Yang Xiaodong
Published: July 2021

The liver cancer has become the sixth most common cancer and the second leading cause of cancer deaths worldwide. The incidence of liver cancer has characteristics of the geographical distribution, which vary from region to region. Based on the data from Cancer Incidence in Five Continents, this study analyzed the spatial distribution of liver cancer globally and explored the effect of meteorological factors of surface temperature and wind field on incidence of liver cancer, to find the geographical distribution characteristics of liver cancer and the impact of geographical environmental factors on the incidence of liver cancer, which will be of great significance to the epidemiological study of liver cancer and the prevention of liver cancer. The results show that the humid and hot oceanic climate may be conducive to the development of liver cancer. The environmental factors play an important role in the occurrence of liver cancer.
Research on mutual test method and strategy of bi-directional power grid connected invertert
Authors: Tian Shuowen , Yin Zhongdong
Published: July 2021

In order to improve the utilization rate of grid connected inverter and expand its auxiliary service capacity for power grid, the demand of grid connected inverter supporting V2G, V2B, V2H and other technology applications is increasingly obvious. However, due to its detection technology has not yet carried out systematic research, if the existing detection technology is applied, it will not only follow the shortcomings of the current technology, but also abandon the advantages of bi-directional power control topology. In order to solve this problem, this paper proposes a test method and control strategy for multiple bi-directional power grid connected inverters: Taking two bi-directional power grid connected inverters as examples, the circuit topology of back-to-back mutual test is proposed, and its working mode is analyzed; PID control with coupling inner membrane control is introduced to improve the dynamic response ability; The MATLAB simulation model is built and verified. The results show that the proposed test method and control strategy can effectively realize the test of bi-directional charging facilities, and provide a certain reference for the corresponding industry.
A design of intelligent delivery drone based on BeiDou navigation and visual processing
Authors: Xu Xiaohao
Published: July 2021

This article used automatic control, 5G real-time communication, visual processing and other technologies to design a carbon fiber intelligent delivery drone, based on BeiDou satellite navigation and face recognition. And we proposed a semi-autonomous delivery mode to achieve real-time control of the drone. This mode can reduce flight risks and ensure the safety and accuracy of distribution. The drone can be powered by microcrystalline silicon thin film solar cells. The BeiDou satellite navigation system is used for autonomous positioning, combined with binocular stereo vision technology to observe the surroundings, automatically plan the flight path. On the way, personnel can intervene in real time as needed. Finally, when the drone arrives at the destination, facial recognition technology is used to confirm the identity of the recipient to complete the delivery.
Performance of 2-D inlets with curved compression surface formed by segments with controllable compression angle
Authors: Pan Jin , Jin Feng
Published: July 2021

Suppose that curved surface consists of tiny polylines. Two 2-D inlets with curved surfaces formed by equal compression angles of the micro-element segments and a slight increase in the compression angle of the micro-element segments are designed respectively. The numerical simulation method is used to compare the performance of two curved surface 2-D inlets with the reference three-wedge compression 2-D inlet. Select NASA classic test data, in order to determine the turbulence model and calculation method chosen by the numerical simulation Fluent software. Numerical simulation results show: the pressure ratio of the curved compression system at the place corresponding to the wedge compression second shock wave is only 0.55 of the wedge compression pressure ratio, which is much smaller than the critical pressure ratio of the boundary layer separation; at design point, the performance of three inlets is similar; at non-design points, the 2-D inlets with the curved surface have a higher flow coefficient and total pressure recovery coefficient. The configuration of the small segments compression angles is the key to the performance of the curved surface compression two-dimensional inlet.
Research on cavitation pulsation characteristics under liquid breakdown mechanism
Authors: Huang Xin , Zong Siguang , Liu Tao , Liang Shanyong
Published: July 2021

The SGR series solid-state laser system with adjustable pulse energy is adopted. The system uses solid-state Nd: YAG laser to generate laser cavitation in distilled water, High speed camera is used to observe the pulsation process of laser cavitation in distilled water, and candy algorithm is used to detect the edge of cavitation, extract the edge features of cavitation, calculate the circumference of the edge of cavitation, and analyze the pulsation characteristics of cavitation in distilled water. The results of laser acoustic signal collected by hydrophone, high-speed photography and MATLAB image analysis are compared, and the initial expansion of cavitation is in different stages It is concluded that the initial expansion rate and the final pulsation rate of the cavity are faster.
Design of online laser marking system by vision guided based on template matching
Authors: Zhang Weichao , Xiao Zhongjun , Yan Zhiguo
Published: July 2021

Industry 4.0 has put forward the requirements of improving the marking efficiency and accuracy of the laser marking industry, and manual placement has been unable to meet the production needs. In this paper, laser marking technology is combined with image recognition technology, and the automation of marking production process is realized by controlling the stepper motor to drive the conveyor belt, and accurate marking of arbitrarily placed workpiece is realized on the conveyor belt. The test results show that this marking system designed by us has high precision, and the yield of finished products reaches 99.5%, which provides a set of efficient and reliable solution for small and medium power laser marking production line to realize online positioning function.
A servo control method of bolt tightening robot for power transmission lines
Authors: Zhang Mingda , Sun Yihui , Wang Sijin , Yang Quan
Published: July 2021

This paper discusses a control method of bolt tightening robot automatically search and tighten. Because of the influence of the wind in the search process, so this paper adopt the servo system to determine the position of the target to complete the bolt docking[1]. Due to the bolt by weathering, corrosion, etc have different situation, so for different years of bolt, the fastening work done by corresponding torque control.
Research on impact characteristics of a new graphite composite earthing device
Authors: Zhao Jianli , Li Yuanjie , Le Wang , Pan Zhuohong
Published: July 2021

For the new type of graphite composite grounding material, there is a lack of generally accepted rules and standards. In this paper, the impact properties of a new type of graphite composite earthing material are studied. The test results show that the new type of composite grounding device always has spark discharge effect. With the increase of impulse current amplitude, the value of impulse coefficient decreases, and the rate of decrease decreases. Increasing the amplitude of the shock current may only increase the electric field strength in the region, but not increase the spark discharge range in the soil, so the shock coefficient tends to be flat. The test results can provide guidance for the selection and application of new grounding materials.
Study on influencing factors of sulfur particle size in chelated iron in oxidation process
Authors: Zhang Wu , Liu Qishong , Liu Ke , Fan Rui , Liu Bo , Xue Jingwen
Published: July 2021

The insoluble elemental sulfur with particle size less than 10 μm is produced in the solution through chelated iron-based method, while the sulfur recovery is generally through the aggregation sedimentation filtration method. In this paper, the influence of desulfurization solution parameters on the size of sulfur are investigated, and the indispensable conditions for the formation of large-size sulfur are discussed. Meanwhile, in order to obtain the conditions for large sulfur particles generation, the influence of the concentration of sulfur modifier on the Zeta potential of desulfurization solution and the change of sulfur particle size were studied.
Research on preparation of low bulk density Claus tail gas hydrogenation catalyst
Authors: Zhang Xiaoxue , Li Jinjin , Liu Zongshe , Zhu Hongyang , Duan Ting
Published: July 2021

With the continuous improvement of national energy conservation and emission reduction requirements, oil and natural gas production industry has increasingly strict requirements for SO2 emission from tail gas. Nowadays, most of large and medium-sized natural gas purification plants and refineries adopt hydrogenation reduction tail gas treatment process to achieve ultra-low SO2 emission, which puts forward high requirements for the activity, stability and economy of tail gas hydrogenation catalyst. In recent years, due to the high price of hydrogenation catalyst, it has become a research hot spot to reduce the cost of catalyst by reducing the bulk density. Traditional catalyst preparation process focused on the types and properties of support and active components, while the influence of alumina powder properties and preparation conditions have not been paid enough attention. With the extensive application of fine characterization methods and the further understanding of catalyst micro-structure, the influence of alumina powder properties and preparation conditions on the performance of catalyst are more and more obvious. In this paper, the Pseudo boehmite was investigated. TG, SEM, XRD and other characterization methods were used to study the preparation method of low bulk density Claus tail gas hydrogenation catalyst.
Design and optimization on training management system of professional classroom
Authors: Sun Xuwen , Qi Lei , Li Shixiong , Shan Hongyan , Ma Siming
Published: July 2021

In order to further enrich the practical guarantee conditions of training theory teaching simulation in the university and improve the level of digital, scientific and information management of professional classrooms, this paper, through analyzing the ideas of system construction, explaining the system composition, structure and system function, designs a professional classroom training management system which integrates the functions of training design, training implementation, training assessment, etc., focally analyzes the key system technology and gives the technology as can be adopted next to further perfect the system function. The research is of great practical significance to improve the level of training information management system development and training management informatization subsequently.
The extended Kano model based on moderated regression analysis: A case study of express delivery service
Authors: Li Zhen , Meng Qingliang
Published: July 2021

Not all product and service quality are equally important to customers. Several studies have applied regression analysis to identify the key elements affecting customer satisfaction. This paper used an extended Kano model based on the moderated regression analysis to improve the defects of the traditional Kano model. The model is validated using data collected from express delivery service. And the empirical results show that the method produces more accurate classification. Overall, this study makes contributions to both Kano model improvement and express delivery service quality optimization.
Effect of fiber reinforcement on mechanical properties of flow solidification of silt
Authors: Ding Jihui , Wang Haochen , Han Shouxin , Yu Zenghui , Yan Shengkang
Published: July 2021

In order to solve the brittle failure of cement flowing solidified sludge, basalt fiber and cement are mixed to prepare flowing solidified sludge. The fluidity and unconfined compressive strength tests of fluid solidified sludge with different cement and fiber content have been carried out. The results show that mixing basalt fiber into cement solidified fluid sludge will reduce its fluidity and increase its unconfined resistance Compressive strength; there is an optimal amount of basalt fiber, and its optimal amount is affected by the amount of cement; with the increase of curing age, the compressive strength of the sludge solidified with fiber cement increases gradually; the solidified sludge is unconfined for 14d and 28d The unconfined compressive strength has a linear relationship with the 7d unconfined compressive strength.
Fractional fourier series and its applications
Authors: Yu Chiihuei
Published: July 2021

In this article, we use a new multiplication to propose a definition of fractional Fourier series, regarding the Jumarie type of modified Riemann-Liouville fractional derivatives. Furthermore, several examples are provided to illustrate the applications of fractional Fourier series.
Molecular dynamics study on the deformation of void single crystal magnesium under uniaxial stress
Authors: Tang Jinqi , Yao Junping
Published: July 2021

The uniaxial tension and compression process of single crystal magnesium model with voids along [0001] direction was simulated by using embedded atom potential and molecular dynamics method, and the micro plastic deformation mechanism of voids under tension and compression was studied. The results show that the elastic modulus of the single crystal magnesium model under compression is greater than the elastic modulus under tension, indicating that compression deformation is more difficult; In the process of plastic deformation, the dislocation, stacking fault and twin will be produced in the single crystal magnesium model under tension and compression, but the emission mechanism of dislocation is different. Tension will make the dislocation slip to the edge of the model along the direction of 45 ° and produce four symmetrical slip bands, while compression will produce an annular defect band near the cavity; In addition, the stacking fault area and twin type produced are also different. This asymmetry is mainly caused by the different initial deformation mechanisms under the two loading conditions.
The existence of underground gas storage causes geomagnetic anomaly in this area?
Authors: Wang Zhendong , Su Shupeng , Yuan Jiehao
Published: July 2021

When the stress state of the rock changes, its permeability will also change accordingly, which is the so-called piezomagnetic effect. The piezomagnetic characteristics of rocks are an important and reliable physical basis for the seismomagnetic effect. Based on the experiments of rock magnetism, many scholars have carried out targeted experiments on the relationship between stress and rock magnetism, and achieved many important experimental understandings. As the largest underground gas storage (UGS) in operation in China, the Hutubi UGS has a design storage capacity of 10 billion cubic meters. It is operated periodically every year by gas injecting in summer and gas extracting in winter. During the process of gas injection and gas extraction in Hutubi UGS, the gas well pressure changes up to more than 10 MPa. Periodic injection and extraction operations will induce variations in the in-situ stress field in local areas. Whether these variations can cause local crustal magnetic anomalies is the focus of this paper. An observation network composed of 63 total geomagnetic intensity measuring stations was established in the Hutubi UGS and its surrounding areas, and the geomagnetic anomalies have been systematically observed. Based on the two phases of field observation data in October 2016 and October 2018, a polynomial fitting method was used to obtain the crustal magnetic anomalies in the UGS area. Results show that the existence of the Hutubi UGS has indeed caused the geomagnetic anomaly changes in this areas, the maximum value of the magnetic anomaly is 19 nT. The results of this field observation further confirmed the existence of the piezomagnetic effect in the laboratory and established the internal connection between the meso-scale crustal magnetic anomalies and the underground stress variations.
Study on the stability of artificial vibration points with internal resonance in solar sail dynamics
Authors: Diao Zhenbao
Published: July 2021

In this paper, the linear and stability of solar sail spacecraft at the libration point of artificial balance is studied. The stability has been analyzed for the linear cases and nonresonance cases. The changing law of artificial balance point is found when the attitude angle of solar sail is fixed. The linear stability region of the solar sail spacecraft at L4 was found. Based on the circular restricted three-body problem, the dynamic model of the continuous solar sail spacecraft is established. The variation law of the position of manual translational point with the β parameters is analyzed. The condition and existence range of linear stability of artificial translational point are given. The influence of thrust parameters on the system and manual translational point is analyzed. The dynamics equation of the solar sail spacecraft near the linearly stable artificial translational point and the nonlinear vibration theory, the range of the system mass parameters and thrust parameters when the system has 1:2 and 1:3 internal resonance is obtained. Using the multi-scale method, the stability of the long and short period motion of the detector is analyzed, and the boundedness of motion is proved.
First-principles study of the effect of vacancies on the interface stability of 3C-SiC/Mg composites based on theoretical physical method
Authors: Lv Zhao , Yao Junping
Published: July 2021

In this paper, the first principles calculation method based on theoretical physics method was used to optimize the structure of 3C-SiC(111)/Mg(0001) interface model with vacancies. The interface adhesion work, vacancy formation energy and electronic structure were calculated and analyzed. The results show that the interface adhesion work of 3C-SiC/Mg-VMg
−1、3C-SiC/Mg-VMg
−2、3C-SiC/Mg-VMg
−3 is greater than that of 3C-SiC/Mg which indicates that Mg vacancy have a certain promoting effect on the interface bonding of 3C-SiC/Mg, and the interface adhesion work of 3C-SiC/Mg- VMg
−
1 is the largest. Because after the presence of Mg vacancy, the number of wavelet peaks increases and the pseudo-energy gap increases, so that the covalent bond increases and the interface adhesion work increases. Their vacancy defect formation energies are not much different, which are 1.1057eV, 1.0584eV, 1.2299eV, respectively. After the presence of C vacancy and Si vacancy, the interface adhesion work of 3C-SiC-VC
−
1/Mg 、3C-SiC-VC
−
3/Mg、3C-SiC-VSi
−
2/Mg and 3C-SiC-VSi
−4/Mg is smaller than that of 3C-SiC/Mg, which indicates that C vacancy and Si vacancy have no effect on the interface bonding. Among them, the interface adhesion work of 3C-SiC-VC
−1/Mg is greater than that of 3C-SiC-VC
−3/Mg, and the interface adhesion work of 3C-SiC-VSi
−4/Mg is greater than that of 3C-SiC-VSi
−2/Mg. After the presence of vacancy, the number of small wave peaks in the density of states map becomes less, the distribution of the density of states near the Fermi level becomes narrower, the metallicity is enhanced, and the bond strength decreases. In terms of the formation energy of vacancy defects, the formation energy of 3C-SiC-VC
−
1/Mg is less than that of 3C-SiC-VC
−
3/Mg, and the formation energy of 3C-SiC-VSi
−
2/Mg is less than that of 3C-SiC-VSi
−
4/Mg.
Vibration characteristic analysis for emulsion droplet excited by chaotic frequency pulsed electric field
Authors: Peng Y , Zhang Y Y , Liao Z X
Published: July 2021

In this paper, taking single emulsion droplet as the research object, the vibration characteristics of emulsion droplet in chaotic electric field is explored. The fixed amplitude and equal pulse width chaotic frequency pulsed electric field is constructed by using the Chaotic-Pulse-Position Modulation method, the vibration dynamics model of emulsified oil droplet in chaotic electric field is established, and the chaotic electric field parameters and vibration response of droplet are solved. Results show that the optimal pulse width is 0.009s, the optimal chaotic boundary of pulse electric field frequency is 170 rad/s to 690 rad/s, the droplet is excited into chaotic vibration, and there is resonance. Besides, the droplet vibration in chaotic pulsed electric field is unsteady, but the droplet will enters the steady state vibration from the second same pulse.
Study on enlarging chaos frequency in two coupled lasers using both optoelectronic cross-feedback and self-feedback
Authors: Chen Mengmeng , Yan Senlin
Published: July 2021

This paper presents an optoelectronic delayed time cross-feedback and self-feedback method to enlarge chaotic frequencies of two semiconductor lasers as two chaotic signal oscillators and to enhance the oscillation behaviours of the lasers. The technical solution of enlarging-frequency of two lasers is that the light from one laser is converted into a photocurrent by the photoelectric converter, and then the delayed time photocurrent is divided into two currents. One is cross fed to another laser while the other photocurrent is fed to self-laser, which can result in enhancing chaos oscillation to realize enlargement of chaotic frequency of two semiconductor lasers. We adjust the feedback levels or the delayed time to realize enlargement of chaotic frequency of two semiconductor lasers. When the feedback level increased, enlargement of the chaotic frequency of the two semiconductor lasers is obviously enhanced. When a feedback is performed, enlargement of chaotic frequency of one laser is obviously enhanced. When the two feedbacks are performed, enlargements of chaotic frequencies of two lasers are obviously enhanced. These results illustrate that enlargement of chaotic frequency of two laser can be effectively obtained via the optoelectronic delayed time cross-feedback and self-feedback method. The research result of this paper is a reference value for enlargement of chaotic frequency, chaos communization, and laser technology etc.
A numerical method for the solid mechanics with Euler variables
Authors: Liu Junchen , Li Shihai , Wang Ling , Feng Chun , Qian Feng , Wang Junfu , Zhu Xinguang
Published: July 2021

Based on the requirement of field engineering, we proposed a new numerical method for analyzing the solid mechanics with Euler variables. By replacing the Lagrange variables with the Euler variables, there will be three new items appearing in the equation. We use the fixed Euler grid to calculate solid mechanics, and use the boundary of material regiment to describe the movement of the boundary of material, after the boundary of material regiment moves beyond the Euler element grid size, new Euler element grids will appear and the corresponding old Euler element grids which have been out of the region of material will disappear. By this way, the movement of solid could be calculated in the Euler fixed grids. Then we did some test cases, we get the result that the new method is right and could be used to calculate the solid mechanic problems.
US residential heat pumps: the private economic potential and its emissions, health, and grid impacts
Authors: Deetjen Thomas A , Walsh Liam , Vaishnav Parth
Published: July 2021

To explore electrification as a climate change mitigation strategy, we study US residential heat pump adoption, given the current US housing stock. Our research asks (a) how the costs and benefits of heat pump adoption evolve with increased penetration, (b) what rate of heat pump adoption is economic given today’s housing stock, electric grid, energy prices, and heat pump technology, and (c) what effect changing policies, innovations, and technology improvements might have on heat pump adoption. We answer these research questions by simulating the energy consumption of 400 representative single-family houses in each of 55 US cities both before and after heat pump adoption. We use energy prices, CO2emissions, health damages from criteria air pollutants, and changes in peak electricity demand to quantify the costs and benefits of each house’s heat pump retrofit. The results show that 32% of US houses would benefit economically from installing a heat pump, and 70% of US houses could reduce emissions damages by installing a heat pump. We show that the potential for heat pump adoption varies depending on electric grid, climate, baseline heating fuel, and housing characteristics. Based on these results we identify strategic, technology, and policy insights to stimulate high heat pump adoption rates and deep electrification of the US residential heating sector, which reduces CO2emissions and the impacts of climate change.
Spatial covariation between solar-induced fluorescence and vegetation indices from Arctic-Boreal landscapes
Authors: Maguire Andrew J , Eitel Jan U H , Magney Troy S , Frankenberg Christian , Köhler Philipp , Orcutt Erica L , Parazoo Nicholas C , Pavlick Ryan , Pierrat Zoe A
Published: July 2021

The Arctic-Boreal Zone (ABZ) is characterized by spatially heterogeneous vegetation composition and structure, leading to challenges for inferring patterns in vegetation productivity. A mechanistic understanding of the patterns and processes underlying spectral remote sensing observations is necessary to overcome these challenges. Solar-induced chlorophyll fluorescence (SIF), near-infrared reflectance of vegetation (NIRv), and chlorophyll/carotenoid index (CCI) show promise for tracking productivity and disentangling links to the activity and distribution of chlorophyll at coarse spatial scales (e.g. 0.5°), but their effectiveness for studying mixed landscapes characteristic of the ABZ remains unclear. Here, we use airborne observations collected during NASA’s Arctic-Boreal Vulnerability Experiment to examine the spatial covariation between SIF, NIRv, and CCI at a scale (30 m) commensurate with the best available landcover products across interior Alaska. Additionally, we compare relationships among SIF and vegetation indices from spaceborne observations (TROPOMI and MODIS) resampled to a 0.01° (∼1000 m) scale. We find that the strength of the SIF-NIRv linear relationship degrades when compared from the spaceborne to the airborne scale (R
2 = 0.50 vs. 0.26) as does the strength of the SIF-CCI linear relationship (R
2 = 0.30 vs. 0.18), though the degradation of SIF-CCI is less severe than that of SIF-NIRv. The relationship of SIF with either vegetation index is strongly dependent on landcover class at both airborne and spaceborne scales. We provide context for how further work could leverage SIF with reflectance indices measurable from a variety of platforms to improve mapping of vegetation dynamics in this ecoregion.
Interdecadal variation of summer rainfall in the Greater Mekong Subregion and its possible causes
Authors: Wen Dayong , Cao Jie , Zhao Chenxi , Masiri Itsara , Buntoung Sumaman
Published: July 2021

This paper investigates the interdecadal variation in summer rainfall over the Greater Mekong Subregion (GMS) during 1981–2020 and its possible causes, using Climate Hazards Group Infrared Precipitation with Station rainfall datasets, European Centre for Medium-range Weather Forecasts Reanalysis fifth generation data and the atmospheric general circulation model ECHAM6. The dominant mode of summer rainfall in the GMS features a seesaw pattern with an increase in rainfall over the central–southern GMS and a decrease in rainfall in northwestern Myanmar–Yunnan. The dominant mode of the GMS summer rainfall shows a change in regime around 2001/2002. Interdecadal variability in rainfall is largely related to sea surface temperature anomalies (SSTAs) over the Western Pacific Warm Pool (WPWP). Warmer SSTAs in the WPWP lead to interdecadal variation in summer rainfall in the GMS by exciting an anomalous cyclone in the lower troposphere over the southern GMS–South China Sea. This is accompanied by anomalous ascending motions in the central–southern GMS and anomalous descending motions in northern Myanmar–Yunnan. The Matsuno–Gill mechanism, which links SSTAs with interdecadal variations in the GMS summer rainfall, is further confirmed by numerical experiments.
Global risks of infectious disease outbreaks and its relation to climate
Authors: Franzke Christian L E , Czupryna Marcin
Published: July 2021

Infectious disease outbreaks are recurring events which can lead to a large number of fatalities every year. Infectious disease outbreaks occur infrequently and the role of global warming and modes of climate variability for those outbreaks is not clear. Here we use an extreme value statistics approach to examine annual spatially aggregated infectious disease fatality data to compute their probability to occur using generalized Pareto distribution (GPD) models. The GPD provides a good model for modeling the fatality data and reveals that the number of fatalities follows a power-law. We find that the magnitude of Covid-19 is of an expected level given previous fatality data over the period 1900–2020. We also examined whether including co-variates in the GPD models provide better model fits. We find evidence that a pure linear trend is the best co-variate and, thus, has increased the propensity of large outbreaks to occur for most continents and world-wide. This suggests that mainly non-climate factors affect the likelihood of outbreaks. This linear trend function provides a crude representation of socio-economic trends such as improved public health. However, for South America the Atlantic multidecadal oscillation modulates the outbreak propensity as the best co-variate, showing that climate can play some role in infectious disease outbreaks in some regions.
Evaluation of river flood extent simulated with multiple global hydrological models and climate forcings
Authors: Mester Benedikt , Willner Sven Norman , Frieler Katja , Schewe Jacob
Published: July 2021

Global flood models (GFMs) are increasingly being used to estimate global-scale societal and economic risks of river flooding. Recent validation studies have highlighted substantial differences in performance between GFMs and between validation sites. However, it has not been systematically quantified to what extent the choice of the underlying climate forcing and global hydrological model (GHM) influence flood model performance. Here, we investigate this sensitivity by comparing simulated flood extent to satellite imagery of past flood events, for an ensemble of three climate reanalyses and 11 GHMs. We study eight historical flood events spread over four continents and various climate zones. For most regions, the simulated inundation extent is relatively insensitive to the choice of GHM. For some events, however, individual GHMs lead to much lower agreement with observations than the others, mostly resulting from an overestimation of inundated areas. Two of the climate forcings show very similar results, while with the third, differences between GHMs become more pronounced. We further show that when flood protection standards are accounted for, many models underestimate flood extent, pointing to deficiencies in their flood frequency distribution. Our study guides future applications of these models, and highlights regions and models where targeted improvements might yield the largest performance gains.
Increasing population exposure to global warm-season concurrent dry and hot extremes under different warming levels
Authors: Liu Wenbin , Sun Fubao , Feng Yao , Li Chao , Chen Jie , Sang Yan-Fang , Zhang Qiang
Published: July 2021

Projecting future changes in concurrent dry and hot extremes (CDHEs) and the subsequent socio-economic risks (e.g. population exposure) is critical for climate adaptation and water management under different warming targets. However, to date, this aspect remains poorly understood on both global and regional scales. In this study, the changes in future CDHEs and their population exposures under 1.5 °C, 2 °C, and 3 °C warming were quantified using a Standardized Dry and Hot Index calculated based on the newly released Coupled Model Intercomparison Project Phase 6 climate model outputs and global population datasets. It was found that relative to the baseline period (1986–2005), the severity of CDHEs would increase on the global scale and in most regions, such as in Southern Europe, the Mediterranean, Sahara, West Africa, Central America, Mexico, the Amazon, and the west coast of South America under 1.5 °C, 2 °C, and 3 °C of warming. Stabilizing the warming at 1.5 °C would constrain the adverse influence of CDHEs on the population suffering from severe CDHEs in most regions (especially in Central Europe, Southern Europe, the Mediterranean, Eastern North America, West Asia, East Asia, and Southeast Asia). Globally, the population impacted by severe CDHEs (with a constant 2000 population) would increase by 108 and 266 million (149 and 367 million when constant 2080 population is applied) for 2 °C and 3 °C increase compared to a 1.5 °C increase. These findings provide scientific evidence of the benefit of limiting anthropogenic warming to 1.5 °C in terms of the socio-economic risks related to CDHEs.
Tuning the optical response of Nano dipole antenna by using plasmonic materials as a load in the gap
Authors: Zarezadeh Esmail , Ghorbani Ayaz
Published: July 2021

Possibility of tuning the optical response of a Nano dipole antenna by using various plasmonic based materials is demonstrated. By incorporating various load geometry in Nano dipole antenna’s gap, different optical characteristics of Nano dipole antennas, e.g. extinction cross section (ECS), input impedance, scattering cross section (SCS), has been numerically investigated. It is shown that by properly design, based on desired goal, tunable and broadband absorption cross section can be achieved. In addition, a graphene based load is also incorporated, and multiple peaks for ESC at THz band was showed.