火源位置对房间-走廊式结构下烟气危害性影响的实验研究

利用小尺寸典型建筑结构实验台选取了两种不同大小的油盘和三个典型的火源位置进行实验,同步获取浓度、温度、质量数据,对准稳态时段内的数据进行分析;以整个火源房间为控制体,以有害组分CO的积分平均浓度及生成率为研究对象,研究了不同火源位置影响下开口的气体质量流率与中性面高度之间的关系,以及火源热释放速率或中性面的高度对CO的浓度及生成率的影响.结果表明,无论火源处于近门角落还是远角,CO积分平均浓度及生成率的数据表明其烟气层的危险性均明显高于火源处于中心时的值.     

多重防护的复杂系统中危险源风险评价定量方法研究

通过对当前风险评价方法的研究,发现目前常用的风险评价方法都是针对特定领域危险源的评价,而对于风险管理中亟需的评价具体危险源的风险可接受水平的通用方法却很少涉及,即使有也尚处于定性或半定量研究阶段,这对于其后续步骤风险缓解措施的实施,以及安全预警信息的生成都有着极大局限性。鉴于此,提出了针对具体危险源进行风险评价的定量方法。首先结合里森模型对风险及其二重属性（可能性与严重性）的含义和归属进行明确界定,然后分别用两种不同的方法对风险的二重属性进行定量,其中在对严重性属性定量时引入了事件树的方法,最终得到量化的风险值。最后,用一个风险评价实例说明了这种风险定量评价方法的实施过程。     

烟花爆竹企业安全监控预警系统研究

烟花爆竹企业安全监控预警系统采用分散监控与集中管理的监控策略,不仅可以实现传统的视频监控和记录功能,对烟花爆竹企业生产现场及厂区的工作情况进行实时监视和录像;还可以对烟花爆竹企业安全生产参数（如温度、湿度、静电等）实时采集与处理,对烟花爆竹企业内部及周边的动态安全状况实时分析的基础上根据警情设定自动做出相应的监控预警及应急响应,如声光报警等;同时,对烟花爆竹等危险源可能发生的事故后果（包括死亡、重伤和轻伤等）进行模拟与分析,为事故的应急救援提供科学的决策支持。     

企业安全操作规程编制探讨

编制安全操作规程是企业安全管理的重要工作,针对企业编制安全操作规程时存在的问题,总结企业编制安全操作规程的经验,从内容、资料收集、编制流程等环节提出改进和完善的方向,促进提高企业安全管理水平。     

作业场所职业危害统计指标筛选研究

建立科学、实用的作业场所职业危害统计指标对准确收集职业危害数据,为监管决策提供依据具有重要意义。本研究通过变异系数法、相关系数法、聚类分析、主成分分析法等数理统计学方法对5类65项待筛选统计指标进行筛选,选择次数较多的统计指标,并开展应用试点研究,最终确定入选指标。入选指标符合科学、必要和可行的原则,可用于评价各地作业场所职业危害状况。     

地震应急避险问题研究

"5·12"汶川地震造成的巨大人员伤亡,是对我国地震应急避险工作的严厉拷问,迫使我们重新审视现行的体制.从地震灾区收集了应急避险的第一手数据资料,采用数理统计的方法得出调研结论,在此基础上,对我国现有的地震应急避险措施提出了改进建议,以期进一步提高公众在地震灾害中应急避险的能力.     

模糊支持向量机在滑坡危险性评价中的应用

为了将模糊支持向量机应用于滑坡灾害危险性评价工作,并进行验证,进行了研究区滑坡现状的调查,评价指标的选取,隶属函数的确定和基于FSVM的滑坡灾害危险性评价.选取了高程指标、坡度指标、岩土体指标、地表湿度指标及植被覆盖指标等5个指标作为滑坡灾害危险性评价指标,最后以莆田市为例,结合Rs和GIS技术,进行了滑坡危险性评价的研究.评价结果与实地验证和莆田市国土局提供的地质灾害现状图基本吻合.     

Modeling flood induced interdependencies among hydroelectricity generating infrastructures

This paper presents a new kind of integrated modeling method for simulating the vulnerability of a critical infrastructure for a hazard and the subsequent interdependencies among the interconnected infrastructures. The developed method has been applied to a case study of a network of hydroelectricity generating infrastructures, e.g., water storage concrete gravity dam, penstock, power plant and transformer substation. The modeling approach is based on the fragility curves development with Monte Carlo simulation based structural–hydraulic modeling, flood frequency analysis, stochastic Petri net (SPN) modeling, and Markov Chain analysis. A certain flood level probability can be predicted from flood frequency analysis, and the most probable damage condition for this hazard can be simulated from the developed fragility curves of the dam. Consequently, the resulting interactions among the adjacent infrastructures can be quantified with SPN analysis; corresponding Markov Chain analysis simulates the long term probability matrix of infrastructure failures. The obtained results are quite convincing to prove the novel contribution of this research to the field of infrastructure interdependency analysis which might serve as a decision making tool for flood related emergency response and management.     

Application of domino effect quantitative risk assessment to an extended industrial area

Escalation of primary accidental scenarios triggering a “domino effect” have caused extremely severe accidental events in the chemical and process industry. The identification of possible escalation events is required in the safety assessment of sites where relevant quantities of hazardous substances are stored or handled. In the European Union, “Seveso-II” Directive requires the assessment of on-site and off-site possible escalation scenarios in sites falling under the obligations of the Directive. In the present study, a methodology developed for the quantitative assessment of risk due to domino effect was applied to the analysis of an extended industrial area. Recently developed equipment damage probability models were applied for the identification of the final scenarios and for escalation probability assessment. The domino package of the Aripar-GIS software was used for risk recomposition. The results evidence that quantitative risk assessment of escalation hazard is of fundamental importance in order to identify critical equipment and to address prevention and protection actions.