核电厂风险管理活动中的PRA质量要求

基于美国核管理委员会(NRC)推行的在核电厂运用的概率安全评价(PRA)技术,介绍PRA质量的含义、NRC在应用PRA过程中提出的分阶段提高PRA质量的方法以及相应的管理导则。结合国内现状,给出提高PRA质量的可接受方法。     

Probabilistic simulation of cable performance and water based protection in cable tunnel fires

Nuclear power plants contain a significant amount of fire load in form of electrical cables. The performance of the cables is interesting both from the fire development and system failure viewpoints. In this work, cable tunnel fires are studied using numerical simulations, focusing on the fire spreading along power cables and the efficiency of the water suppression in preventing the cable failures. Probabilistic simulations are performed using Monte Carlo technique and the Fire Dynamics Simulator (FDS) as the deterministic fire model. The primary fire load, i.e. the power cables are modelled using the one-dimensional pyrolysis model, for which the material parameters are estimated from the experimental data. Two different water suppression systems are studied. The simulation results indicate that using either suppression system decreased the heat release rate in the tunnel to less than 10% of the non-suppressed case. Without water suppression, the cables of the second sub-system were damaged in almost all fires, but when either of the studied water suppression systems was used, the probability of the cable failures was decreased to less than 1%. This result indicates that in current scenario, the probability of losing both sub-systems is determined directly by the suppression system unavailability.     

一种低轨卫星网络的概率风险评估方法研究

可靠性分析是卫星星座设计过程中不可或缺的一环。针对低轨卫星网络的高可靠性要求,利用概率风险评估的分析方法,结合网络风险及故障树理论,提出了卫星故障树杠铃风险模型。在此模型基础上分析＂铱＂星系统网络,利用卫星工具箱获取每颗卫星对地覆盖人口数,以此为参数计算得到对网络影响较大的节点和链路,对于今后评估卫星网络风险具有一定的启发意义。     

Natural disaster risk analysis for critical infrastructure systems: An approach based on statistical learning theory

Probabilistic risk analysis has historically been developed for situations in which measured data about the overall reliability of a system are limited and expert knowledge is the best source of information available. There continue to be a number of important problem areas characterized by a lack of hard data. However, in other important problem areas the emergence of information technology has transformed the situation from one characterized by little data to one characterized by data overabundance. Natural disaster risk assessments for events impacting large-scale, critical infrastructure systems such as electric power distribution systems, transportation systems, water supply systems, and natural gas supply systems are important examples of problems characterized by data overabundance. There are often substantial amounts of information collected and archived about the behavior of these systems over time. Yet it can be difficult to effectively utilize these large data sets for risk assessment. Using this information for estimating the probability or consequences of system failure requires a different approach and analysis paradigm than risk analysis for data-poor systems does. Statistical learning theory, a diverse set of methods designed to draw inferences from large, complex data sets, can provide a basis for risk analysis for data-rich systems. This paper provides an overview of statistical learning theory methods and discusses their potential for greater use in risk analysis.     

A feasibility assessment of the use of nanofluids to enhance the in-vessel retention capability in light-water reactors

Nanofluids, colloidal dispersions of nanoparticles, exhibit a substantially higher critical heat flux (CHF) compared to water. As such, they could be used to enhance the in-vessel retention (IVR) capability in the severe accident management strategy implemented by certain light-water reactors. It is envisioned that, at normal operating conditions, the nanofluid would be stored in dedicated storage tanks, which, upon actuation, would discharge into the reactor cavity through injection lines. The design of the injection system was explored with risk-informed analyses and computational fluid dynamics. It was determined that the system has a reasonably low failure probability, and that, once injected, the nanofluid would be delivered effectively to the reactor vessel surface within seconds. It was also shown analytically that the increase in decay power removal through the vessel using a nanofluid is about 40%, which could be exploited to provide a higher IVR safety margin or, for a given margin, to enable IVR at higher core power. Finally, the colloidal stability of a candidate alumina-based nanofluid in an IVR environment was experimentally investigated, and it was found that this nanofluid would be stable against dilution, exposure to gamma radiation, and mixing with boric acid and lithium hydroxide, but not tri-sodium phosphate.     

Key attributes of the SAPHIRE risk and reliability analysis software for risk-informed probabilistic applications

The Idaho National Laboratory is a primary developer of probabilistic risk and reliability analysis (PRRA) tools, dating back over 35 years. Evolving from mainframe-based software, the current state-of-the-practice has led to the creation of the SAPHIRE software. Currently, agencies such as the Nuclear Regulatory Commission, the National Aeronautics and Aerospace Agency, the Department of Energy, and the Department of Defense use version 7 of the SAPHIRE software for many of their risk-informed activities. In order to better understand and appreciate the power of software as part of risk-informed applications, we need to recall that our current analysis methods and solution methods have built upon pioneering work done 30–40 years ago. We contrast this work with the current capabilities in the SAPHIRE analysis package. As part of this discussion, we provide information for both the typical features and special analysis capabilities, which are available. We also present the application and results typically found with state-of-the-practice PRRA models. By providing both a high-level and detailed look at the SAPHIRE software, we give a snapshot in time for the current use of software tools in a risk-informed decision arena.     

ISDN在C＆C08交换机上的实现方法

介绍C&C08交换机ISDN硬件接口及数据设定方法。     

Analysis of a natural resources management system in the Calakmul Biosphere Reserve

An analysis of the natural resource management system was carried out for the ejido X-kanha located in the northern part of the Calakmul Biosphere Reserve in Campeche, Mexico. Through field research using participatory rural appraisal (PRA), the activities carried out by different user groups were identified. Gender roles as well as age roles were analyzed. Results show that each family depends upon the diversification of productive activities in order to meet economic needs. Diversification of activities is carried out in both space and time, making use of different ecosystems during varied seasons throughout the year. Women's activities correspond to housekeeping and house administration; they take care of home gardens and are responsible for water collection and wood gathering. Men carry out the activities of working in the milpa, cattle raising, honey production, chicle collection, and wood felling.A series of PRA activities carried out with the people of X-Kanha led to the identification of limitations to more optimal uses of natural resources. The characterization of limitations and associated alternatives is used to provide a guideline to aid the efforts of NGOs and other organizations interested in the conservation of natural resources, and for the well-being of the local population.     

A framework to integrate software behavior into dynamic probabilistic risk assessment

Software plays an increasingly important role in modern safety-critical systems. Although, research has been done to integrate software into the classical probabilistic risk assessment (PRA) framework, current PRA practice overwhelmingly neglects the contribution of software to system risk. Dynamic probabilistic risk assessment (DPRA) is considered to be the next generation of PRA techniques. DPRA is a set of methods and techniques in which simulation models that represent the behavior of the elements of a system are exercised in order to identify risks and vulnerabilities of the system. The fact remains, however, that modeling software for use in the DPRA framework is also quite complex and very little has been done to address the question directly and comprehensively. This paper develops a methodology to integrate software contributions in the DPRA environment. The framework includes a software representation, and an approach to incorporate the software representation into the DPRA environment SimPRA. The software representation is based on multi-level objects and the paper also proposes a framework to simulate the multi-level objects in the simulation-based DPRA environment. This is a new methodology to address the state explosion problem in the DPRA environment. This study is the first systematic effort to integrate software risk contributions into DPRA environments.