Dangerous good transportation by road: from risk analysis to emergency planning

Despite the relative recent move towards inherent safe materials, the relentless drive of consumerism requires increased quantities of dangerous goods to be manufactured, transported, stored and used year on year. The safety and effectiveness of road transport systems is to be considered a strategic goal in particular in those countries, like Italy, in which 80% of goods are transported by this means. In this paper, we face the risk from dangerous good transport by presenting a site-oriented framework for risk assessment and developing a theoretical approach for emergency planning and optimisation. In the first step, we collected field data on a pilot highway and developed a database useful to allow a realistic evaluation of the accident frequency on a given route, by means of multivariate statistical analysis. To this end, we considered both inherent factors (such as tunnels, bend radii, height gradient, slope etc), meteorological factors, and traffic factors (traffic frequency of tank truck, dangerous good truck etc.) suitable to modify the standard national accident frequency. By applying the results to a pilot area, referring to flammable and explosive scenarios, we performed a risk assessment sensitive to route features and population exposed. The results show that the risk associated to the transport of hazardous materials, in some highway stretches, can be at the boundary of the acceptability level of risk set down by the well known F/N curves established in the Netherlands. On this basis, in the subsequent step, we developed a theoretical approach, based on the graph theory, to plan optimal emergency actions. The effectiveness of an emergency planning can normally be evaluated in term of system quickness and reliability. As a case study, we applied the developed approach to identify optimal consistency and localisation in the pilot area of ‘prompt action vehicles’, properly equipped, quick to move and ready for every eventuality. Applying this method results in an unambiguous and consistent selection criterion that allows reduction of intervention time, in connection with technical and economic optimisation of emergency equipment.     

以人为本的现代工业安全管理

现代生产中发生的意外事故 ,80 %以上是由于人的因素造成的。笔者运用人机工程学和行为科学理论 ,对人的不安全行为和因素进行了深入的归类分析 ;阐述了人因事故预测和预防对策 ;指出工业安全管理应该从人的角度出发 ,系统地建立安全管理体系 ;最后 ,运用系统工程的观点 ,提出了构建以人为本的安全管理体系的结构 ,该体系的实行将能够使现代工业安全管理提高到一个新的水平。     

220kV开关拒动事故分析及防范

针对永安火电厂 2 2 0 k V线路接地短路之后开关拒动事故 ,从保护动作行为及开关拒动进行原因分析 ,提出防范措施 ,以避免类似事故发生。     

Joint propagation of variability and imprecision in assessing the risk of groundwater contamination

Estimating risks of groundwater contamination often require schemes for representing and propagating uncertainties relative to model input parameters. The most popular method is the Monte Carlo method whereby cumulative probability distributions are randomly sampled in an iterative fashion. The shortcoming of the approach, however, arises when probability distributions are arbitrarily selected in situations where available information is incomplete or imprecise. In such situations, alternative modes of information representation can be used, for example the nested intervals known as “possibility distributions”. In practical situations of groundwater risk assessment, it is common that certain model parameters may be represented by single probability distributions (representing variability) because there are data to justify these distributions, while others are more faithfully represented by possibility distributions (representing imprecision) due to the partial nature of available information. This paper applies two recent methods, designed for the joint-propagation of variability and imprecision, to a groundwater contamination risk assessment. Results of the joint-propagation methods are compared to those obtained using both interval analysis and the Monte Carlo method with a hypothesis of stochastic independence between model parameters. The two joint-propagation methods provide results in the form of families of cumulative distributions of the probability of exceeding a certain value of groundwater concentration. These families are delimited by an upper cumulative distribution and a lower distribution respectively called Plausibility and Belief after evidence theory. Slight differences between the results of the two joint-propagation methods are explained by the different assumptions regarding parameter dependencies. Results highlight the point that non-conservative results may be obtained if single cumulative probability distributions are arbitrarily selected for model parameters in the face of imprecise information and the Monte Carlo method is used under the assumption of stochastic independence. The proposed joint-propagation methods provide upper and lower bounds for the probability of exceeding a tolerance threshold. As this may seem impractical in a risk-management context, it is proposed to introduce “a-posteriori subjectivity” (as opposed to the “a-priori subjectivity” introduced by the arbitrary selection of single probability distributions) by defining a single indicator of evidence as a weighted average of Plausibility and Belief, with weights to be defined according to the specific context.     

建立我国工业事故风险管理制度的探讨

简要论述工业事故风险管理的要素和风险评价方法，提出建立适合我国市场经济体制的工业事故风险管理制度，制定适合各行业特点的事故风险标准值和风险分析评价方法，将风险管理与工伤保险和事故预防有机地结合起来等建议。     

铁路行车安全评价研究

在对我国铁路行车安全影响因素系统分析的基础上，根据事故指标与隐患指标相结合共同评价的思路，建立了行车安全评价指标体系，并就指标体系安全综合评价方法进行研究，提出了集常规方法与模糊方法所长的一种常规一模糊安全综合评价新方法。     

关于安全科学基本概念及相互关系的研究

安全、危险、风险、事故、隐患等是安全科学和安全管理的基本概念。对于这些概念，至今仍有不同认识。本文从国内外研究现状出发，对上述基本概念及相互关系进行了分析探讨。Ｐｒｏｆ．     

关于扭转我国安全生产严峻局面的几点建议

简要论述了建国以来数次事故高峰和当前安全生产面临的严峻局面，分析了事故高发和职业危害严重的主要原因及隐患整治、重大危险源控制、安全法制、安全生产管理体制、职工素质、舆论监督、伤亡事故统计、经济处罚等方面存在的问题，提出了控制对策和建议。     

铁路行车安全预测初探

用灰色系统和概率统计的方法，对我国铁路行业两个铁路局的行车事故件数及百万机车走行公里数进行安全预测和讨论，就开展安全预测及安全管理中的一些问题提出了见解。