Design of insulation support system of 120 keV positive ion source accelerator

In order to support the physical research on the EAST tokamak,a new positive ion source with designed beam energy of 120 keV was proposed to be developed.Accelerator structure is one of the key components of the ion source.Through the finite element analysis method,the electrostatic analyses of insulators and grid plates were carried out,the material and structure parameters of insulators were determined.The maximum electric field around each insulator is about 4 kV/mm,and the maximum electric field between grids is about 14 kV/mm,which can meet the 120 keV withstand voltage holding.The insulation system for the positive ion source accelerator with 120 keV is designed,and the connection and basic parameters of insulators and support flanges are analyzed and determined.

A Method of Identifying Electromagnetic Radiation Sources by Using Support Vector Machines

Electromagnetic Radiation Source Identification(ERSI) is a key technology that is widely used in military and radiation management and in electromagnetic interference diagnostics.The discriminative capability of machine learning methods has recently been used for facilitating ERSI.This paper presents a new approach to improve ERSI by adopting support vector machines,which are proven to be effective tools in pattern classification and regression,on the basis of the spatial distribution of electromagnetic radiation sources.Spatial information is converted from 3D cubes to 1D vectors with subscripts as inputs in order to simplify the model.The model is trained with 187 500 data sets in order to enable it to identify the types of radiation source types with an accuracy of up to 99.9%.The influence of parameters(e.g.,penalty parameter,reflection and noise from the ambient environment,and the scaling method for the input data) are discussed.The proposed method has good performance in noisy and reverberant environment.It has an identification accuracy of 82.15% when the signal-to-noise ratio is 20 dB.The proposed method has better accuracy in a noisy environment than artificial neural networks.Given that each Electromagnetic(EM) source has unique spatial characteristics,this method can be used for EM source identification and EM interference diagnostics.

Acoustic emission source identification based on harmonic wavelet packet and support vector machine

In order to solve the fatigue damage identification problem of helicopter moving components, a new approach for acoustic emission （AE） source type identification based on the harmonic wavelet packet （HWPT） feature extraction and the hierarchy support vector machine （H-SVM） classifier is proposed. After a four-level decomposition of the HWPT, the energy feature of AE signals in different frequency bands is extracted, which overcomes the shortcomings of the traditional wavelet packet including energy leakage, and inflexible frequency band selection and different frequency resolutions on different levels. The H-SVM classifier is trained with a subset of the experimental data for known AE source types and tested using the remaining set of data. The results of pressure-off experiments on the specimens of carbon fiber materials indicate that the proposed approach can effectively implement the AE source type identification, and has a better performance in terms of computational efficiency and identification accuracy than the wavelet packet （WPT） feature extraction.

Construction and realization of the knowledge base and inference engine of an IDSS model for air-conditioning cooling/heating sources selection

The knowledge representation mode and inference control strategy were analyzed according to the specialties of air-conditioning cooling/heating sources selection. The constructing idea and working procedure for knowledge base and inference engine were proposed while the realization technique of the C language was discussed. An intelligent decision support system (IDSS) model based on such knowledge representation and inference mechanism was developed by domain engineers. The model was verified to have a small kernel and powerful capability in list processing and data driving, which was successfully used in the design of a cooling/heating sources system for a large-sized office building.

New Sr Isotope Evidence to Support the Material Source of the Mengyejing Potash Deposit in the Simao Basin from Ancient Marine Halite or Residual Sea

Objective The Mengyejing potash deposit in the Simao Basin is the only producing area of solid potash at present in China. There is still controversy about the material source and distribution of the potash in this deposit （Shen Lijian et al., 2017）, which has influenced not only the prospecting direction and efficiency but also the understanding of the control of Tethys tectonic evolution on the formation and distribution of the mineral resources. This work analyzed the Sr isotope geochemical characteristics of evaporites from core samples in the well MZK-3 in order to further clarify the material source and to explore the potash distribution in the Simao Basin.

Primary Sources of Job Burnout Among University Teachers in China and Its Impact

This qualitative study employs interview and observation to locate possible factors that bring forth burnout among university teaching faculty in China and sort out possible im pact.By working out possible supporting measures to reduce and alleviate the burnout level,this research hopefully would benefit not only the university teaching staff in the sense of informing them of possible ways to combat burnout,but also the adm inistrators of higher education because they would be more aware of the key to improving productivity and reducing turnover rate in college.

服务于新型能源体系建设的气象服务保障体系构建思考

[目的]新型能源体系是以清洁低碳为核心目标的能源体系,国家新型能源体系构建是实现“双碳”目标的重要举措。天气气候因素及气象灾害等对电网稳定、安全运行影响巨大,需要针对国家新型能源体系建设新需求,构建高质量气象服务保障体系。[方法]文章通过文献调研、政策调研和专家咨询等方法,在对国家新型能源体系相关政策措施进行分析的基础上,对照国内能源气象服务业务现状、研判未来发展方向,提出新型能源体系建设的气象服务保障体系发展思路,并研提相关建议。[结果]研究表明,中国气象局各级业务单位在风光发电、水电、核电,及输电通道、能源消纳等方面均较好开展了能源气象服务。国家新型能源体系建设对气象服务保障提出了面向清洁能源基地建设整体优化气象服务保障布局,强化发电功率预报以及气候预测等服务精准度,针对新能源基础设施建设、发电、储能、输电、消纳等各场景开展气象服务保障等新要求。[结论]对标国家新型能源体系建设要求,文章从优化能源气象业务服务布局,提升服务保障能力,强化技术人才、合作机制保障支撑等方面,对更好发挥气象部门在国家新型能源体系建设中的服务保障作用提出了对策建议。

New Individual Identification Method of Radiation Source Signal Based on Entropy Feature and SVM

In this paper,according to the defect of methods which have low identification rate in low SNR,a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firstly,based on the theory of multi-resolution wavelet analysis,the wavelet power spectrum of noncooperative signal can be gotten. Secondly,according to the information entropy theory,the wavelet power spectrum entropy is defined in this paper. Therefore,the database of signal's wavelet power spectrum entropy can be built in different SNR and signal parameters. Finally,the sorting and identification model based on SVM is built for the individual identification of radiation source signal. The simulation result indicates that this method has a high individual's identification rate in low SNR,when the SNR is greater than 4 dB,the identification rate can reach 100%. Under unstable SNR conditions,when the range of SNR is between 0 dB and 24 dB,the average identification rate is more than 92. 67%. Therefore,this method has a great application value in the complex electromagnetic environment.

Neutron-gamma discrimination method based on blind source separation and machine learning

The discrimination of neutrons from gamma rays in a mixed radiation field is crucial in neutron detection tasks.Several approaches have been proposed to enhance the performance and accuracy of neutron-gamma discrimination.However,their performances are often associated with certain factors,such as experimental requirements and resulting mixed signals.The main purpose of this study is to achieve fast and accurate neutron-gamma discrimination without a priori information on the signal to be analyzed,as well as the experimental setup.Here,a novel method is proposed based on two concepts.The first method exploits the power of nonnegative tensor factorization(NTF)as a blind source separation method to extract the original components from the mixture signals recorded at the output of the stilbene scintillator detector.The second one is based on the principles of support vector machine(SVM)to identify and discriminate these components.In addition to these two main methods,we adopted the Mexican-hat function as a continuous wavelet transform to characterize the components extracted using the NTF model.The resulting scalograms are processed as colored images,which are segmented into two distinct classes using the Otsu thresholding method to extract the features of interest of the neutrons and gamma-ray components from the background noise.We subsequently used principal component analysis to select the most significant of these features wich are used in the training and testing datasets for SVM.Bias-variance analysis is used to optimize the SVM model by finding the optimal level of model complexity with the highest possible generalization performance.In this framework,the obtained results have verified a suitable bias–variance trade-off value.We achieved an operational SVM prediction model for neutron-gamma classification with a high true-positive rate.The accuracy and performance of the SVM based on the NTF was evaluated and validated by comparing it to the charge comparison method via figure of merit.The results indicate that the proposed approach has a superior discrimination quality(figure of merit of 2.20).

Effects of N source and nitrification pretreatment on growth of Arthrospira platensis in human urine

Culture ofArthrospiraplatensis （Spirulinaplatens） in human urine was investigated to get valuable biomass. NO3-N was the proper N source, in comparison with other N source, including urea, NH4-N and NO2-N. As a result, aerobic nitrification of human urine was performed, with above 93.6% nitrification percentage finally achieved with total-N （TN） load of 46.52 mg/（L.d）, in which Arthrospira platensis was successfully grown. The main compositions of the obtained biomass are close to those in Zarrouk medium. Thus, it is possible to culture Arthrospiraplatensis in nitrified human urine for food production within bioregenerative life support systems （BLSSs）.

Factors associated with financial support in old age for young and middle-aged rural residents in China

This study examined the factors associated with financial support in old age from three primary mechanisms-personal savings,family support,and social insurance-to explore the implications for the future development of China's rural social welfare system.Cross-sectional surveys of 1392 young and middle-aged rural residents were conducted in July and August2012.The results showed that while social insurance was increasingly acceptable,personal savings and family support still had fundamental value.Combining the three mechanisms,the rural old-age welfare system presented nontraditional features.China's new rural endowment insurance is discussed as a means to address the need for financial support among the rural aging population.

虚拟同步机电流受限暂态电压支撑机理与改进故障穿越控制研究

针对虚拟同步机在电网低、过电压故障下所面临的无功电压支撑不足、特性差等问题,建立考虑电流限幅特性的虚拟同步机等效电路模型,并基于拓扑同伦原理,给出不同无功电压控制在等效电路相量图上的几何表征方法。利用该方法,揭示几种常见无功电压控制下的虚拟同步机电流受限暂态电压支撑机理,并由此提出一种改进的故障穿越控制策略,有效改善电网低电压、过电压故障下的暂态电压控制能力和支撑特性,进而缓解故障期间的暂态功角稳定问题。基于PSCAD/EMTDC仿真对所提机理和故障穿越控制方法进行详细验证,最后,在3机9节点系统中对其在近、远区电网故障下的支撑特性进行仿真验证。

Effects of task orientation on subsequent source memory as revealed by functional MRI

Episodic memories are composed of various interrelated elements, including those specific to items of central interest and those pertaining to related features, such as the color, shape, size, spatial location, temporal order, and media or modalities of presentation. Memory about a core item （such as a word, object, or picture） is called item memory while memory about the context or related fea- tures of a core item is defined as source memory. What determines which sources within an episode are successfully remembered is of particular interest to researchers. Behavioral evidence suggests that the orientation of a memory task influences whether the related source of the item will be re- membered later. This study explored changes in the hippocampus and prefrontal cortex while par- ticipants completed two tasks： an item-oriented task and a source-oriented task. We used functional MRI to investigate the neural mechanisms by which task orientation influences source encoding. We found that subsequent source memory effects in the right prefrontal cortex and hippocampus were modulated by task orientation, whereas task orientation modulated item memory effects in the prefrontal cortex. These findings highlight the possibility that the hippocampus contributes to the intentional encoding of item-source associations, whereas the prefrontal cortex is biased toward processing information to which attention is directed.

财政支持、源头创新与产业链安全

强化源头创新是化解国外掣肘中国技术链、供应链以及产业链安全发展的根本办法。选取2003—2022年中国通信装备产业分布在30个省级行政区的面板数据,通过门槛效应回归模型和调节效应回归模型展开实证研究,探索政府财政支持背景下源头创新影响产业链安全的效果和机制。研究表明,相对于应用创新,源头创新对产业链安全发展的积极作用更强,且存在显著的一期滞后效应和单一门槛效应等基本结论。另外,研究还发现产业发展引导、科技项目支撑、创新平台搭建等政府财政支持方式可在源头创新影响产业链安全发展的过程中发挥正向调节效应。基于此,提出重塑政府与市场关系、拓宽财政支持渠道、优化创新资源配置等建议,以期从政府角度为提升源头创新能力、构筑安全产业链提供更多政策支撑。

基于PSO-MSVR的太阳能耦合土壤源热泵系统优化配置

为了优化太阳能耦合土壤源热泵系统(SGSHPS)的配置,以沈阳地区办公建筑为例,基于TRNSYS平台建立了不同运行模式的SGSHPS模型,对比分析不同模式下系统运行30 a后土壤温度不平衡率和系统总能耗;以并联过渡季蓄热模式为对象,对不同的太阳能集热系统和地埋管换热器组合方式进行模拟;在保证系统稳定的前提下,以动态费用年值最低为目标,优化太阳能集热器面积和地埋管换热器钻孔数的配置方式;引入粒子群优化-多输出支持向量机回归(PSO-MSVR)算法,使用PSO算法生成MSVR模型参数并寻找最优值。结果表明:与采用传统热平衡法确定的配置方式相比,优化后运行30 a的系统能耗降低379522 kW,节能11.2%,费用年值降低61863元,土壤温度仅上升0.73 K;对于不同的太阳能集热器和地埋管换热器造价,优化后费用年值相较优化前仍有不同程度的节省,且土壤温度均未有较大偏移。

多源融合实况分析产品2022年度研发改进及应用进展

简要总结了国家气象信息中心多源融合实况分析产品在2022年的研发和改进进展,重点阐述了实况产品在高影响天气过程监测和重大服务保障中的应用情况。通过多源数据协同质量控制技术、复杂地形实况分析技术、风云卫星应用同化技术、网格实况真实性检验4方面的优化,改进降水、气温等实况产品质量。其中,气温产品在复杂地形区误差降低20%,有效剔除了虚假降水和80%融雪性降水,改善了复杂山区降水信息;大气风场误差降低2%;大气湿度误差降低3.5%。在暴雨、台风、高温、寒潮等监测服务中,系统反映了“龙舟水”期间对流系统的活动特征;准确捕捉台风“梅花”降水落区的演变、雨强大小、大风影响范围以及台风的垂直结构等特征;对于极端高温天气和寒潮中雨雪冰冻及大风的影响区域均有较好的监测效果;在山洪等突发事件中,实况产品的分钟级数据有效弥补了站点稀疏区监测资料的不足;百米分辨率实况产品有效支撑了2022年冬奥气象服务保障。

提升柔性直流系统惯量主动支撑能力的自同步解耦控制策略

针对电力电子化电力系统低惯量特性引起的频率稳定问题,从挖掘电网输电环节调控潜力的视角出发,提出了提升柔性直流系统惯量主动支撑能力的自同步解耦控制策略。定量分析了利用柔性直流系统能量裕度提升系统惯量水平的可行性,提出了计及子模块电容和电感元件能量裕度的换流站自同步控制策略,在实现无锁相环自同步的同时主动支撑受端系统惯量;在此基础上,为了解决现有控制中直流电压安全约束限制电容能量利用的问题,提出了柔性直流系统直流电压与子模块电容电压解耦控制策略及参数设计方法,通过自适应调节子模块投入数量与电容电压参考值,实现柔性直流系统内储能元件能量裕度的充分利用,并设计了其恢复策略及启动判据,有效提升了受端系统惯量水平和频率稳定性。定量评估了柔性直流系统的惯量支撑能力,并通过实时数字仿真验证了所提控制策略的有效性。