RELAP5/MOD3.2 sensitivity calculations of loss-of-feed water (LOFW) transient at Unit 6 of Kozloduy NPP

This paper provides a comparison between the real plant data obtained by Unit 6 of Kozloduy nuclear power plant (NPP) during the loss-of-feed water (LOFW) transient and the calculation results received by RELAP5/MOD3.2 computer model of the same NPP unit.RELAP5/MOD3.2 computer model of the VVER-1000 has been developed at the Institute for Nuclear Research and Nuclear Energy-Bulgarian Academy of Sciences (INRNE-BAS) based on Unit 6 of Kozloduy NPP. This model has been used for simulation the behavior of the real VVER-1000 NPP during the LOFW transient. Several calculations have been provided to describe how the different boundary conditions reflect on the prediction of real plant parameters.This paper discusses the results of the thermal–hydraulic sensitivity calculations of loss-of-feed water transient for VVER-1000 reactor design. The report also contains a brief summary of the main NPP systems included in the RELAP5 VVER model and the LOFW transient sequences.This report was possible through the participation of leading specialists from Kozloduy NPP and with the assistance of Argonne National Laboratory (ANL) for the United States Department of Energy (US DOE), International Nuclear Safety Program (INSP).     

Algebraic approach for the diagnosis of turbine cycles in nuclear power plants

According to plant operating staff's practical needs, authors proposed a diagnosis model to identify the performance degradation of steam turbine cycles in nuclear power plants (NPPs). The essential idea of this study is how to identify the intrinsically degraded component which causes electric loss. Authors found that there were not so many turbine cycle diagnosis applications in NPPs currently because of technical, financial, or social characteristics of the plant. So a great part of the diagnosis has been dependent on operating staff's experience and knowledge. However as economic competition becomes severe, the efficiency staffs is asking for reliable and practical advisory tools. For the solution of these shortcomings, authors proposed a simple and intuitive diagnosis concept based on the superposition rule of degradation phenomena, which can be derived by simple algebra and correlation analysis. Though the superposition rule is not so significant statistically, almost all of the performance indices under normal operation are fairly compatible with this model. Authors developed a prototype model of quantitative root-cause diagnosis and validated the background theory using the simulated data. The turbine cycle advisory system using this model was applied to Gori NPP units 3&4.     

基于P89LPC933的大功率智能充电器的设计

设计了一种基于P89LPC933单片机控制的大功率智能充电器,提出了四阶段充电控制方法。结合主电路和MCU控制电路详细地阐述了其控制策略以及充电器的硬件设计和软件设计。与市场上典型的充电器做了横向比较与总结。     

神光Ⅲ强激光能源模块测量线圈研究

神光Ⅲ能源模块作为一种大功率强激光功率源，采用合适传感头准确可靠测量其脉冲电流，有利于提高能量传输的可靠性和准确性。该文分析了置于该能源模块中高压侧测量不同脉冲宽度电流的Rogowski测量线圈的数学模型、时域和领域特性，以及最佳阻尼参数配合和优选方法，并对基于MATLAB环境下SIMULINK工具所做的仿真结果和现场实验测试采集到的脉冲电流波形进行了比较。为有效抑制积分漂移，该文提出了复合积分器电路模型。该文章介绍的基于肋Rogowski线圈的测量仪器具有尺寸小、结构简单、低功耗、高准确度、安全操作等特点。     

2002～2003年国家电网公司系统变压器类设备事故统计与分析(一)

章主要对国家电网公司系统110kV及以上电压等级变压器类设备的事故进行统计分析，着重反映这些设备在运行中的质量情况及其发生的问题，以此作为质量信息反馈和编制设备技术标准、运行管理规范、检修作业指导书、技术监督规定以及反事故措施的重要依据。     

江西省电力通信数据网建设探讨

介绍了江西省电力通信数据网的建设、整体应用状况和系统特点,重点分析和阐述了江西电力通信数据网建设的必要性、关键技术、核心／汇聚／接入3层网络结构,提出了网络业务VPN构建、网络控制与故障处理机理。     

Fuel properties of Brassica juncea oil methyl esters blended with ultra-low sulfur diesel fuel

Brassica juncea is a drought-tolerant member of the Brassicaceae plant family with high oil content and a short growing season that is tolerant of low quality soils. It was investigated as a feedstock for production of biodiesel along with evaluation of subsequent fuel properties, both neat and in blends with petroleum diesel fuel. These results were compared against relevant fuel standards such as ASTM D6751, EN 14214, ASTM D975, EN 590, and ASTM D7467. Crude B. juncea oil was extracted from unconditioned seeds utilizing a continuous tubular radial expeller. The oil was then chemically refined via degumming, neutralization and bleaching to render it amenable to direct homogeneous sodium methoxide-catalyzed transesterification. The principal fatty acid detected in B. juncea oil was erucic acid (44.1%). The resulting biodiesel yielded fuel properties compliant with the biodiesel standards with the exception of oxidative stability and kinematic viscosity in the case of EN 14214. Addition of tert-butylhydroquinone and blending with soybean oil-derived biodiesel ameliorated these deficiencies. The fuel properties of B5 and B20 blends of B. juncea oil methyl esters (BJME) in ultra-low sulfur (<15 ppm S) diesel (ULSD) fuel were within the ranges specified in the petrodiesel standards ASTM D975, EN 590 and ASTM D7467 with the exception of derived cetane number in the case of EN 590. This deficiency was attributed to the inherently low cetane number of the certification-grade ULSD, as it did not contain performance-enhancing additives. In summary, this study reports new fuel property data for BJME along with properties of B5 and B20 blends in ULSD. Such results will be useful for the development of B. juncea as an alternative source of biodiesel fuel.     

一种实用车载逆变器的设计

介绍了一种以SG3525A为主控芯片的车载逆变器的设计,该逆变电源工作效率高、实用、可靠.     

Learning Behaviors of Stochastic Gradient Radial Basis Function Network Algorithms for Odor Sensing Systems

Learning behaviors of a radial basis function network (RBFN) using a singular value decomposition (SVD) and stochastic gradient (SG) algorithm, together named RBF‐SVD‐SG, for odor sensing systems are analyzed, and a fast training method is proposed. RBF input data is from a conducting polymer sensor array. It is revealed in this paper that the SG algorithm for the fine‐tuning of centers and widths still shows ill‐behaving learning results when a sufficiently small convergence coefficient is not used. Since the tuning of centers in RBFN plays a dominant role in the performance of RBFN odor sensing systems, our analysis is focused on the center‐gradient variance of the RBFN‐SVD‐SG algorithm. We found analytically that the steady‐state weight fluctuation and large values of a convergence coefficient can lead to an increase in variance of the center‐gradient estimate. Based on this analysis, we propose to use the least mean square algorithm instead of SVD in adjusting the weight for stable steady‐state weight behavior. Experimental results of the proposed algorithm have shown faster learning speed and better classification performance.     

A comprehensive layered approach for implementing internet of things-enabled smart grid: A survey

The current power grid confronts severe challenges in satisfying customers' demands. Fast transition to the much more flexible power grid enriched with renewable energies, micro-grid, and distributed energy resources has been considered as a straightforward solution to the customers’ high demand. Using smart equipment and renewable energies, electric power generation and storage through the power grid domains will be facilitated, which enables bi-directional energy and information flows. The power grid with such enhanced features is called Smart Grid (SG). Controlling and managing the diverse sets of variables in the SG requires precise measuring, monitoring, communicating, and analytic systems which increase the complexity of the grid. This complexity is the main barrier to the realization of the SG up to now. The emergence of the Internet of Things (IoT) simplifies monitoring, communications, and data processing among smart things to connect to anything in the world. This motivates the SG stakeholders and researchers to proceed with the best way to exploit the IoT technologies in the SG. In this survey paper, we summarize various efforts in this regard to highlight the advantages of the IoT-enabled SG and its probable gaps. To this end, a comprehensive layered approach has been proposed in this paper to classify various applications of the IoT technologies in the SG. Investigating IoT opportunities in each architecture layer facilitates the role of each technology and its relationship with other technologies. Also, open issues and future measures for the realization of IoT-enabled SG have been discussed in the paper.