Effects of spot size on the operation mode of Ga As photoconductive semiconductor switch employing extrinsic photoconductivity

To guide the illuminating design to improve the on-state performances of gallium arsenide(GaAs)photoconductive semiconductor switch(PCSS),the effect of spot size on the operation mode of GaAsPCSS based on a semi-insulating wafer with a thickness of 1 mm,triggered by a 1064-nm extrinsic laser beam with the rectangular spot,has been investigated experimentally.It is found that the variation of the spot size in length and width can act on the different parts of the output waveform integrating the characteristics of the linear and nonlinear modes,and then significantly boosts the PCSS toward different operation modes.On this basis,a two-channel model containing the active and passive parts is introduced to interpret the relevant influencing mechanisms.Results indicate that the increased spot length can peak the amplitude of static domains in the active part to enhance the development of the nonlinear switching,while the extended spot width can change the distribution of photogenerated carriers on both parts to facilitate the linear switching and weaken the nonlinear switching,which have been proved by comparing the domain evolutions under different spot sizes.

Energy Storage Operation Modes in Typical Electricity Market and Their Implications for China

As the Chinese government proposes ambitious plans to promote low-carbon transition,energy storage will play a pivotal role in China’s future power system.However,due to the lack of a mature electricity market environment and corresponding mechanisms,current energy storage in China faces problems such as unclear operational models,insufficient cost recovery mechanisms,and a single investment entity,making it difficult to support the rapid development of the energy storage industry.In contrast,European and American countries have already embarked on certain practices in energy storage operation models.Through exploration of key issues such as investment entities,market participation forms,and cost recovery channels in both front and back markets,a wealth of mature experiences has been accumulated.Therefore,this paper first summarizes the existing practices of energy storage operation models in North America,Europe,and Australia’s electricity markets separately from front and back markets,finding that perfect market mechanisms and reasonable subsidy policies are among the main drivers for promoting the rapid development of energy storage markets.Subsequently,combined with the actual development of China’s electricity market,it explores three key issues affecting the construction of costsharing mechanisms for energy storage under market conditions:Market participation forms,investment and operation modes,and cost recovery mechanisms.Finally,in line with the development expectations of China’s future electricitymarket,suggestions are proposed fromfour aspects:Market environment construction,electricity price formation mechanism,cost sharing path,and policy subsidy mechanism,to promote the healthy and rapid development of China’s energy storage industry.

Exploration of Operation and Maintenance Management Mode and Innovation Mechanism of Pilot Base of Chemical Park

Based on the current situation of the operation and maintenance management of the pilot base in many chemical parks in China,this paper conducts an in-depth exploration of the operation and maintenance management and innovation mode of the pilot base from the aspects of the evaluation of the pilot project entering the park,safety and environmental protection supervision,pilot mode,and industrialization mode of the pilot test results,so as to provide solutions for accelerating the process and industrialization of the pilot project and realizing the innovation value of the pilot base.

Key Issues for Modelling, Operation, Management and Diagnosis of Lithium Batteries: Current States and Prospects

1 Introduction.With the continuous growth of the global population,the energy demand continues to increase.However,due to the dominance of fossil fuels in global energy and fossil fuels are non-renewable,it has led to the global energy crisis[1].Besides,the use of fossil fuels will generate a mass of air pollutants(e.g.,carbon dioxide,sulfur dioxide,etc.),which will cause serious environmental pollution,climate change[2],etc.To resolve the aforementioned issues,countries around the world have implemented a variety of measures hoping to fundamentally adjust the global energy structure and achieve sustainable development.Thereinto,“Paris Agreement”reached in 2015 under the framework of“United Nations Framework Convention on Climate Change”aims to control the increase in the average temperature of the globe to within 2°C below preindustrial levels,and thereafter to peak global greenhouse gas emissions as soon as possible,continuously decreasing thereafter[3].United Kingdom plans to reduce the average exhaust emissions of“new cars”to approximately 50–70 g/km by 20230,which is roughly half of what it is now[4].In addition,China proposed a plan at“United Nations General Assembly”in 2020 to peak carbon dioxide emissions by 2030 and strive to achieve carbon neutrality by 2060.It is a fact that the whole world is committed to changing the current energy structure,protecting the Earth’s ecology,and achieving global sustainable development[5].

Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.

Research on the Reform of School-Enterprise Cooperation Teaching and Education Mode for Computer Majors

This paper discusses the innovative methods of school-enterprise cooperation education mode in computer applied talent training.An innovative training model based on school-enterprise cooperation is proposed to promote the cultivation of students’practical and innovative skills,so as to better adapt to the needs of society.By analyzing the key links and influencing factors of the training mode,this paper puts forward some concrete suggestions and measures to provide guidelines for universities and enterprises in personnel training.

Research and Practice of the Blended Teaching Model of BOPPPS Teaching Method Under the Background of Digital Education: Taking Operations Research Course as an Example

The rapid development of digital education provides new opportunities and challenges for teaching model innovation.This study aims to explore the application of the BOPPPS(Bridge-in,Objective,Pre-assessment,Participatory learning,Post-assessment,Summary)teaching method in the development of a blended teaching model for the Operations Research course under the background of digital education.In response to the characteristics of the course and the needs of the student group,the teaching design is reconstructed with a student-centered approach,increasing practical teaching links,improving the assessment and evaluation system,and effectively implementing it in conjunction with digital educational technology.This teaching model has shown significant effectiveness in the context of digital education,providing valuable experience and insights for the innovation of the Operations Research course.

An Improved Multi-Objective Hybrid Genetic-Simulated Annealing Algorithm for AGV Scheduling under Composite Operation Mode

This paper presents an improved hybrid algorithm and a multi-objective model to tackle the scheduling problem of multiple Automated Guided Vehicles(AGVs)under the composite operation mode.The multi-objective model aims to minimize the maximum completion time,the total distance covered by AGVs,and the distance traveled while empty-loaded.The improved hybrid algorithm combines the improved genetic algorithm(GA)and the simulated annealing algorithm(SA)to strengthen the local search ability of the algorithm and improve the stability of the calculation results.Based on the characteristics of the composite operation mode,the authors introduce the combined coding and parallel decoding mode and calculate the fitness function with the grey entropy parallel analysis method to solve the multi-objective problem.The grey entropy parallel analysis method is a combination of the grey correlation analysis method and the entropy weighting method to solve multi-objective solving problems.A task advance evaluation strategy is proposed in the process of crossover and mutation operator to guide the direction of crossover and mutation.The computational experiments results show that the improved hybrid algorithm is better than the GA and the genetic algorithm with task advance evaluation strategy(AEGA)in terms of convergence speed and solution results,and the effectiveness of the multi-objective solution is proved.All three objectives are optimized and the proposed algorithm has an optimization of 7.6%respectively compared with the GA and 3.4%compared with the AEGA in terms of the objective of maximum completion time.

基于主客观环流分型的强降水数值预报MODE检验方法及其在2019年暖季东北地区的应用

本文构建了基于主客观环流分型的强降水数值预报空间检验(MODE)方法框架,并利用该框架对欧洲中期天气预报中心全球模式(ECMWF)和中国气象局区域中尺度数值天气预报模式(CMA_MESO)的2019年暖季东北地区强降水预报进行检验。结果表明,2019年暖季东北地区54个强降水日的环流型可分为:西风槽型(15个)、副热带高压影响型(13个)、急流型(5个)、西部(12个)和东部冷涡型(9个)。其中,西风槽型和急流型以区域性强降水为主,模式对其强降水发生与否的预报能力强,TS评分较高;西部、东部冷涡型强降水的局地性强,模式对其强降水发生与否的预报能力差,TS评分低;副热带高压影响型也以区域性强降水为主,模式对其强降水发生与否的预报能力也比较强,但是对其强降水质心位置、强度、面积等属性预报偏差较大,TS评分也相对较低。另外,从两种模式预报性能对比看,CMA_MESO强降水强度和面积预报较实况普遍偏强,虽然其预报的TS评分一般高于ECMWF,但其对强降水预报的空报率也都比ECMWF大,对强降水的属性预报偏差一致性一般也低于ECMWF,其预报的可订正性整体上不及ECMWF。

Mission reliability modeling and evaluation for reconfigurable unmanned weapon system-of-systems based on effective operation loop

The concept of unmanned weapon system-of-systems(UWSoS)involves a collection of various unmanned systems to achieve or accomplish a specific goal or mission.The mission reliability of UWSoS is represented by its ability to finish a required mission above the baselines of a given mission.However,issues with heterogeneity,cooperation between systems,and the emergence of UWSoS cannot be effectively solved by traditional system reliability methods.This study proposes an effective operation-loop-based mission reliability evaluation method for UWSoS by analyzing dynamic reconfiguration.First,we present a new connotation of an effective operation loop by considering the allocation of operational entities and physical resource constraints.Then,we propose an effective operationloop-based mission reliability model for a heterogeneous UWSoS according to the mission baseline.Moreover,a mission reliability evaluation algorithm is proposed under random external shocks and topology reconfiguration,revealing the evolution law of the effective operation loop and mission reliability.Finally,a typical 60-unmanned-aerial-vehicle-swarm is taken as an example to demonstrate the proposed models and methods.The mission reliability is achieved by considering external shocks,which can serve as a reference for evaluating and improving the effectiveness of UWSoS.

Combined hybrid energy storage system and transmission grid model for peak shaving based on time series operation simulation

This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.

一种基于粗糙熵的改进K-modes聚类算法

K-modes聚类算法被广泛应用于人工智能、数据挖掘等领域。传统的K-modes聚类算法有不错的聚类效果,但是存在迭代次数多、计算量大、容易受到冗余属性的干扰等问题,且仅采用简单的0-1匹配的方法来定义2个样本属性值之间的距离,没有充分考虑每个属性对聚类结果的影响。针对上述问题,该文将粗糙熵引入K-modes算法。首先利用粗糙集属性约简算法消除冗余属性,确定各属性的重要程度;然后利用粗糙熵确定每个属性的权重,从而定义新的类内距离。将该文所提算法与传统的K-modes聚类算法分别在4组公开数据集上进行对比试验。试验结果表明,该文所提算法聚类准确率比传统的K-modes聚类算法更高。

UAV-assisted data collection for wireless sensor networks with dynamic working modes

Wireless Sensor Network(WSN)is a cornerstone of Internet of Things(IoT)and has rich application scenarios.In this work,we consider a heterogeneous WSN whose sensor nodes have a diversity in their Residual Energy(RE).In this work,to protect the sensor nodes with low RE,we investigate dynamic working modes for sensor nodes which are determined by their RE and an introduced energy threshold.Besides,we employ an Unmanned Aerial Vehicle(UAV)to collect the stored data from the heterogeneous WSN.We aim to jointly optimize the cluster head selection,energy threshold and sensor nodes’working mode to minimize the weighted sum of energy con-sumption from the WSN and UAV,subject to the data collection rate constraint.To this end,we propose an efficient search method to search for an optimal energy threshold,and develop a penalty-based successive convex approximation algorithm to select the cluster heads.Then we present a low-complexity iterative approach to solve the joint optimization problem and discuss the implementation procedure.Numerical results justify that our proposed approach is able to reduce the energy consumption of the sensor nodes with low RE significantly and also saves energy for the whole WSN.

Fractal Fractional Order Operators in Computational Techniques for Mathematical Models in Epidemiology

New fractional operators, the COVID-19 model has been studied in this paper. By using different numericaltechniques and the time fractional parameters, the mechanical characteristics of the fractional order model areidentified. The uniqueness and existence have been established. Themodel’sUlam-Hyers stability analysis has beenfound. In order to justify the theoretical results, numerical simulations are carried out for the presented methodin the range of fractional order to show the implications of fractional and fractal orders.We applied very effectivenumerical techniques to obtain the solutions of themodel and simulations. Also, we present conditions of existencefor a solution to the proposed epidemicmodel and to calculate the reproduction number in certain state conditionsof the analyzed dynamic system. COVID-19 fractional order model for the case of Wuhan, China, is offered foranalysis with simulations in order to determine the possible efficacy of Coronavirus disease transmission in theCommunity. For this reason, we employed the COVID-19 fractal fractional derivative model in the example ofWuhan, China, with the given beginning conditions. In conclusion, again the mathematical models with fractionaloperators can facilitate the improvement of decision-making for measures to be taken in the management of anepidemic situation.

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

Multimode Design and Analysis of an Integrated Leg-Arm Quadruped Robot with Deployable Characteristics

To improve locomotion and operation integration, this paper presents an integrated leg-arm quadruped robot(ILQR) that has a reconfigurable joint. First, the reconfigurable joint is designed and assembled at the end of the legarm chain. When the robot performs a task, reconfigurable configuration and mode switching can be achieved using this joint. In contrast from traditional quadruped robots, this robot can stack in a designated area to optimize the occupied volume in a nonworking state. Kinematics modeling and dynamics modeling are established to evaluate the mechanical properties for multiple modes. All working modes of the robot are classified, which can be defined as deployable mode, locomotion mode and operation mode. Based on the stability margin and mechanical modeling, switching analysis and evaluation between each mode is carried out. Finally, the prototype experimental results verify the function realization and switching stability of multimode and provide a design method to integrate and perform multimode for quadruped robots with deployable characteristics.

Real-Time 4-Mode MDM Transmission Using Commercial 400G OTN Transceivers and All-Fiber Mode Multiplexers

Weakly-coupled mode division multiplexing(MDM)technique is considered a promising candidate to enhance the capacity of an optical transmission system,in which mode multiplexers/demultiplexers(MMUX/MDEMUX)with low insertion loss and modal crosstalk are the key components.In this paper,a low-modal-crosstalk 4-mode MMUX/MDEMUX for the weakly-coupled triple-ring-core few-mode fiber(TRC-FMF)is designed and fabricated with side-polishing processing.The measurement results show that a pair of MMUX/MDEMUX and 25 km weakly-coupled TRC-FMF MDM link achieve low modal crosstalk of lower than−17.5 dB and insertion loss of lower than 11.56 dB for all the four modes.Based on the TRC-FMF and all-fiber MMUX/MDEMUX,an experiment for 25 km real-time 4-mode 3-λwavelength division multiplexing(WDM)-MDM transmission is conducted using commercial 400G optical transport network(OTN)transceivers.The experimental results prove weakly-coupled MDM techniques facilitate a smooth upgrade of the optical transmission system.

Novel Investigation of Stochastic Fractional Differential Equations Measles Model via the White Noise and Global Derivative Operator Depending on Mittag-Leffler Kernel

Because of the features involved with their varied kernels,differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world issues.In this paper,we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler kernels.In this approach,the overall population was separated into five cohorts.Furthermore,the descriptive behavior of the system was investigated,including prerequisites for the positivity of solutions,invariant domain of the solution,presence and stability of equilibrium points,and sensitivity analysis.We included a stochastic element in every cohort and employed linear growth and Lipschitz criteria to show the existence and uniqueness of solutions.Several numerical simulations for various fractional orders and randomization intensities are illustrated.

Control method based on DRFNN sliding mode for multifunctional flexible multistate switch

To address the low accuracy and stability when applying classical control theory in distribution networks with distributed generation,a control method involving flexible multistate switches(FMSs)is proposed in this study.This approach is based on an improved double-loop recursive fuzzy neural network(DRFNN)sliding mode,which is intended to stably achieve multiterminal power interaction and adaptive arc suppression for single-phase ground faults.First,an improved DRFNN sliding mode control(SMC)method is proposed to overcome the chattering and transient overshoot inherent in the classical SMC and reduce the reliance on a precise mathematical model of the control system.To improve the robustness of the system,an adaptive parameter-adjustment strategy for the DRFNN is designed,where its dynamic mapping capabilities are leveraged to improve the transient compensation control.Additionally,a quasi-continuous second-order sliding mode controller with a calculus-driven sliding mode surface is developed to improve the current monitoring accuracy and enhance the system stability.The stability of the proposed method and the convergence of the network parameters are verified using the Lyapunov theorem.A simulation model of the three-port FMS with its control system is constructed in MATLAB/Simulink.The simulation result confirms the feasibility and effectiveness of the proposed control strategy based on a comparative analysis.

Trajectory tracking guidance of interceptor via prescribed performance integral sliding mode with neural network disturbance observer

This paper investigates interception missiles’trajectory tracking guidance problem under wind field and external disturbances in the boost phase.Indeed,the velocity control in such trajectory tracking guidance systems of missiles is challenging.As our contribution,the velocity control channel is designed to deal with the intractable velocity problem and improve tracking accuracy.The global prescribed performance function,which guarantees the tracking error within the set range and the global convergence of the tracking guidance system,is first proposed based on the traditional PPF.Then,a tracking guidance strategy is derived using the integral sliding mode control techniques to make the sliding manifold and tracking errors converge to zero and avoid singularities.Meanwhile,an improved switching control law is introduced into the designed tracking guidance algorithm to deal with the chattering problem.A back propagation neural network(BPNN)extended state observer(BPNNESO)is employed in the inner loop to identify disturbances.The obtained results indicate that the proposed tracking guidance approach achieves the trajectory tracking guidance objective without and with disturbances and outperforms the existing tracking guidance schemes with the lowest tracking errors,convergence times,and overshoots.