腈纶生产叉车作业区的作业条件危险性分析

运用作业条件危险性分析法对腈纶生产叉车作业区域危险性进行分析,根据分析结果,采取相应安全对策,降低作业区域危险程度,并进一步给出建议,以确保叉车作业安全。     

采油厂化验室危险因素及对策

针对采油厂化验室的特点,对其存在的危险有害因素,从火灾爆炸、中毒、腐蚀、触电、机械伤害、人员、储存场所等方面进行了较为系统的分析,并提出了相应的对策措施。     

关注危险化学品企业绿色物流的储运安全

阐述了危险化学品物流安全储运的特点及事故危害,分析了危险化学品企业物流中的安全隐患及经济发展对危险化学品企业物流的安全储运提出的新要求,指出要用安全科学为物流科学保驾护航,以及危险化学品企业绿色物流安全储运的技术措施。     

某石化厂工作场所噪声危害现状调查分析

目的了解某石化厂噪声危害关键控制点,为企业噪声防护提供依据,减少职业病发生。方法采用现场职业卫生学调查、工作场所噪声检测、作业人员等效连续A声级检测、噪声作业分级相结合的方法进行分析。结果该企业工作场所噪声强度为51.4～100.0dB(A);主要接噪岗位每周40h的等效声级为73.2～90.8dB(A),合格率为54.5%;噪声作业分级为0级、I级,分别占59.1%和40.9%。噪声关键控制点为各种泵类、风机、压缩机、冷却器等设备。结论该企业噪声危害比较严重,需要进一步采取隔声降噪措施。     

某芳烃抽提装置职业病危害控制效果评价

对某芳烃抽提装置建设项目中存在的主要职业病危害因素进行了分析,评价其职业病危害控制效果,提出建议措施。     

中国技术灾害的时序变化与区域差异

近年来,由于生产的全球化、工业水平的迅速提高、技术系统的复杂化和规模化,以及社会结构急剧变化,我国技术灾害的发生频次增多,强度加剧,经济损失趋于上升.技术灾害继自然灾害之后,已逐渐发展为威胁我国人民生命安全和生存环境的主要灾种.基于技术灾害数据库,从致灾因子多度、风险频数、相对损失强度和综合风险指数等4个方面对中国技术灾害的时序变化和区域差异进行了分析与探讨,以期加深对中国技术灾害的系统认识,并为中国技术灾害的风险管理提供依据.     

重大危险源事故风险预警技术研究

重大危险源事故风险预警技术是事故控制技术中的一大研究重点。本文通过对比分析安全生产领域常用事故预警模型的优缺点,总结了事故预警模型的发展趋势,提出了基于模糊综合评判技术和动态模糊神经网络技术的重大危险源事故风险预警模型,详细陈述其构建过程,最后对液化石油气蒸气云爆炸事故应用该模型,得到了较好的预测效果,实现了风险程度的定量化预警。该预警模型具有快速的自学习能力和容错能力,能够同时处理多种风险因素、自动生成模糊规则并满足预警系统的实时性要求,可应用于重大危险源在线监控预警系统,为企业端和政府端监管者提供有效的重大危险源事故风险定量化预警信息,为遏制重大灾难事故的发生、减少死亡人、数受伤人数和直接经济损失提供先进的理论和技术支撑。     

Inferring extinction of mammals from sighting records, threats, and biological traits

For species with five or more sightings, quantitative techniques exist to test whether a species is extinct on the basis of distribution of sightings. However, 70% of purportedly extinct mammals are known from fewer than five sightings, and such models do not include some important indicators of the likelihood of extinction such as threats, biological traits, search effort, and demography. Previously, we developed a quantitative method that we based on species' traits in which we used Cox proportional hazards regression to calculate the probability of rediscovery of species regarded as extinct. Here, we used two versions of the Cox regression model to determine the probability of extinction in purportedly extinct mammals and compared the results of these two models with those of stationary Poisson, nonparametric, and Weibull sighting-distribution models. For mammals with five or more sightings, the stationary Poisson model categorized all but two critically endangered (flagged as possibly extinct) species in our data set as extinct, and results with this model were consistent with current categories of the International Union for the Conservation of Nature. The scores of probability of rediscovery for individual species in one version of our Cox regression model were correlated with scores assigned by the stationary Poisson model. Thus, we used this Cox regression model to determine the probability of extinction of mammals with sparse records. On the basis of the Cox regression model, the most likely mammals to be rediscovered were the Montane monkey-faced bat (Pteralopex pulchra), Armenian myotis (Myotis hajastanicus), Alcorn's pocket gopher (Pappogeomys alcorni), and Wimmer's shrew (Crocidura wimmeri). The Cox model categorized two species that have recently disappeared as extinct: the baiji (Lipotes vexillifer) and the Christmas Island pipistrelle (Pipistrellus murrayi). Our new method can be used to test whether species with few records or recent last-sighting dates are likely to be extinct.     

Analysis of underlying causes of investigated loss of containment incidents in Dutch Seveso plants using the Storybuilder method

In the Netherlands there are around 400 “Seveso” sites that fall under the Dutch Major Hazards Decree (BRZO) 1999. Between 2006 and 2010 the Dutch Labour Inspectorate's Directorate for Major Hazard Control completed investigations of 118 loss of containment incidents involving hazardous substances from this group. On the basis of investigation reports the incidents were entered in a tailor-made tool called Storybuilder developed for the Dutch Ministry of Social Affairs and Employment for identifying the dominant patterns of technical safety barrier failures, barrier task failures and underlying management causes associated with the resulting loss of control events. The model is a bow-tie structure with six lines of defence, three on either side of the central loss of containment event. In the first line of defence, failures in the safety barriers leading to loss of control events were primarily equipment condition failures, pre start-up and safeguarding failures and process deviations such as pressure and flow failures. These deviations, which should have been recovered while still within the safe envelope of operation, were missed primarily because of inadequate indication signals that the deviations have occurred. Through failures of subsequent lines of defence they are developing into serious incidents. Overall, task failures are principally failures to provide adequate technical safety barriers and failures to operate provided barriers appropriately. Underlying management delivery failures were mainly found in equipment specifications and provisions, procedures and competence. The competence delivery system is especially important for identifying equipment condition, equipment isolation for maintenance, pre-start-up status and process deviations. Human errors associated with operating barriers were identified in fifty per cent of cases, were mostly mistakes and feature primarily in failure to prevent deviations and subsequently recover them. Loss of control associated with loss of containment was primarily due to the containment being bypassed (72% of incidents) and less to material strength failures (28%). Transfer pipework, connections in process plant and relief valves are the most frequent release points and the dominant release material is extremely flammable. It is concluded that the analysis of a large number of incidents in Storybuilder can support the quantification of underlying causes and provide evidence of where the weak points exist in major hazard control in the prevention of major accidents.