基于文本挖掘的水电工程施工物体打击事故致因分析

为探明水电工程施工过程中物体打击事故的致因及作用关系,提出针对性的事故预防措施,从源头遏制事故发生。遴选水电工程施工物体打击事故调查报告,运用文本挖掘从人、机、环、管4个方面提取14项事故致因。融合关联规则、决策试验和评价实验室(DEMATEL)方法,厘清致因因素间的关联关系,构建重要度分析模型,确定事故近端致因因素。结果表明：水电工程物体打击事故各致因间联系紧密,其中,安全监督检查不到位、违章作业、安全防护措施不完备、安全意识淡薄等致因因素对事故发生具有直接影响作用。现场清理不彻底、安全技术交底不到位、安全教育培训不到位等是诱发事故的深层影响因素,且安全意识淡薄的中心度排名第一,对事故致因系统的影响较大,在实际施工中应着重考虑上述致因因素。     

危险源概念的重新界定及与隐患关系研究

为使危险源的定义和分类更有可操作性,并明确其与隐患的关系,首先在总结现有危险源定义及分类的基础上,将危险源的概念重新界定,然后对其进行深入分类研究,最后明确危险源与隐患的关系。研究结果表明,应将危险源定义为所有的、直接的或间接的可能导致事故发生的根源或状态;其次,将危险源进一步划分为根源危险源和状态危险源,根源危险源是可能直接或间接导致事故发生的客观存在,包括有形或无形的实体,包括人、物、组织、系统4大类;状态危险源是可能直接或间接导致事故发生的根源危险源的不安全状态,包括正处于和非正处于的不安全状态;第三,隐患是正处于不安全状态的根源危险源。     

Random parameter models for accident prediction on two-lane undivided highways in India

Introduction

Generalized linear modeling (GLM), with the assumption of Poisson or negative binomial error structure, has been widely employed in road accident modeling. A number of explanatory variables related to traffic, road geometry, and environment that contribute to accident occurrence have been identified and accident prediction models have been proposed. The accident prediction models reported in literature largely employ the fixed parameter modeling approach, where the magnitude of influence of an explanatory variable is considered to be fixed for any observation in the population. Similar models have been proposed for Indian highways too, which include additional variables representing traffic composition. The mixed traffic on Indian highways comes with a lot of variability within, ranging from difference in vehicle types to variability in driver behavior. This could result in variability in the effect of explanatory variables on accidents across locations. Random parameter models, which can capture some of such variability, are expected to be more appropriate for the Indian situation.

Method

The present study is an attempt to employ random parameter modeling for accident prediction on two-lane undivided rural highways in India. Three years of accident history, from nearly 200 km of highway segments, is used to calibrate and validate the models.

Results

The results of the analysis suggest that the model coefficients for traffic volume, proportion of cars, motorized two-wheelers and trucks in traffic, and driveway density and horizontal and vertical curvatures are randomly distributed across locations.

Conclusions

The paper is concluded with a discussion on modeling results and the limitations of the present study.     

City hazardous gas monitoring network

In our today's societies, many dangerous chemicals are produced and transported. Due to the vast use of chemicals, more chemical accidents are taking place with huge losses. In this study a city hazardous gas monitoring network was designed to detect the dispersion of toxic and combustible gases in the primary stages. The network could cover hazardous chemical facilities, important hazardous chemical routes, warehouses and special locations which may be the targets of terrorist attacks. The network is consisted of several local networks and a central control panel complex. Each local network has a local control panel in the center and many detectors and sounders around it at distances less than 3000 m that communicate with the local control panels wirelessly. In each location there are two types of gas detectors, toxic and combustible, and a sounder which are equipped with a wireless, radio frequency modem allowing the units to communicate readings and other information on a real-time basis with a remotely located local control panel. High sensitive Photo Ionization Detectors, PIDs, are used to provide fast and low-level on-site screening for chemicals contamination. Combustible gas detectors are the second choice to sense the combustible gas and verify the readings of PIDs in this regard. The central panel consists of several connected control panels work uniquely helping a computer set and the appropriate software and communicate with local control panels via telephone lines. All of the network components are shown on the monitor of central panel with special symbols by geographical information system program. The system is fully addressable so that the high level detection of a detector produces a blinking color double-circle around its symbol in GIS plan. In case of high level gas detection, a team of experts who are fully equipped with different portable detectors depart to the site to test the field to identify the chemicals. All readings of detectors are saved in a data bank and then analyzed to find any chemicals spills and leakages. The network was simulated by a special program so that the components of local networks and the central panel are shown in separate windows. By clicking on one detector on environmental window the formerly designed responses will be activated in central panel window.     

基于人工免疫原理的事故预防研究

介绍生物免疫识别模式,分析事故预防过程的实质是抑制潜在危险转化成事故的控制过程,分析比较事故预防与生物免疫识别模式在作用、生存环境、动作触发源等的共性,构建了基于免疫识别模式的事故预防系统并建立了事故预防数学模型;定义事故预防系统的识别率、失效率、误判率并给出了数学表达式,指出监测生产系统各环节状态信息是否符合系统的安全要求就是识别潜在危险的过程,是事故预防的关键,基于人工免疫原理的事故预防数学模型具有较强的健壮性、自适应性和动态防护性等特点.     

石化企业的环境污染事故应急预案分析与建议

从环境污染角度分析了"吉化爆炸"、"大连原油泄漏"和"兰化系列爆炸"三个典型石化企业安全生产事故案例,论证了环境污染控制在应急预案中的重要地位和完善的应急预案对于避免环境污染事故或最大程度减少事故损失的重要作用。在此基础上,分析了目前石化企业的环境污染应急预案中存在的普遍性问题,并以天津某石化企业的环境污染事故应急预案为例,从应急能力、应急行动、应急培训、预案演练、预案修订和环境污染预防等方面提出了完善建议,增强其针对性、可操作性和科学合理性,以期在应急救援中发挥更好的功效,避免安全生产事故次生环境污染事故。     

Risk management in operations of petrochemical plants: Can better planning prevent major accidents and save money at the same time?

This paper presents an argument that improvement in operational safety can be achieved concurrently with increased operational efficiency. This is a fundamentally different viewpoint on the investment in safety. Traditionally, the cost of providing safety barriers is offset by the expected benefits of reducing the occurrence and severity of accidents. Our approach departs from this method of accounting for safety improvements and focuses on planning as a means of managing systems' response uncertainty and consequently reducing both major accident risk and the cost of operations. The scope of the paper is limited to interventions such as maintenance and repairs and defined in the context of major accident prevention e.g. hydrocarbon leaks. However, the developed methodology is general enough to be applied across the spectrum of process industry facilities and operations.     

RAPID-N: Rapid natech risk assessment and mapping framework

Natech accidents at industrial plants are an emerging risk with possibly serious consequences. For the mitigation of natech risk, authorities need to identify natech prone areas in a systematic manner. In order to facilitate probabilistic natech risk mapping, a unified methodology was developed that is based on the estimation of on-site natural hazard parameters, determination of damage probabilities of plant units, and assessment of probability and severity of possibly triggered natech events. The methodology was implemented as an on-line, extensible risk assessment and mapping software framework called RAPID-N, which allows rapid local and regional natech risk assessment and mapping with minimal data input. RAPID-N features an innovative data estimation framework to complete missing input data, such as on-site natural hazard parameters and plant unit characteristics. The framework is also used for damage assessment and natech consequence analysis, and allows easy modification of input parameters, dynamic generation of consequence models according to data availability, and extension of models by adding new equations or substituting existing ones with alternatives. Results are presented as summary reports and interactive risk maps, which can be used for land-use and emergency planning purposes by using scenario hazards, or for rapid natech consequence assessment following actual disasters. As proof of concept, the framework provides a custom implementation of the U.S. EPA's RMP Guidance for Offsite Consequence Analysis methodology to perform natech consequence analysis and includes comprehensive data for earthquakes. It is readily extendible to other natural hazards and more comprehensive risk assessment methods.     

煤矿事故大数据驱动的风险治理模式研究综述

为明确智能化风险治理在煤矿的研究进展,综合分析数据驱动的煤矿安全风险治理模式研究发展现状,评述用于煤矿安全风险评估的不同预测手段和分析模型,首先,明确智能化风险治理的概念,并检索相关文献确定分析范围;然后,从数据驱动分析方法、煤矿安全风险评估模型和煤矿大数据预测预警平台等3方面,综述事故大数据研究现状、存在的问题及发展趋势。结果表明：煤矿安全领域已基本形成数据驱动的风险分析理论和应用框架,但仍不能满足风险评估与应急管理的需求。在预警平台应用方面,已形成统一的、通用的煤矿安全生产大数据分析平台基本框架,但在生产实际中的应用和推广还远远不够。未来应从提高数据质量和融合动静态多源数据入手,构建综合风险评估模型,研判煤炭开采风险,并加强数据驱动分析在生产实际中的应用,以推动煤矿安全风险治理模式由经验主义向数据驱动转变,实现煤矿安全风险治理信息化与智能化。