“T”型地铁换乘站多点火灾工况下综合火灾危险性研究

为探究大型地铁站多线路火灾场景中的综合危险性,采用火灾动力学软件FDS构建“T”型换乘站全尺寸模型,对不同火源位置、不同火源功率以及是否开启地铁排烟风机等12组工况进行数值模拟;采用性能化方法确定可用疏散时间,并通过综合火灾风险评估方法计算各工况总安全指数。结果表明:1号线站厅层和2号线站台层双点火灾为最不利火灾场景;1号线站台层和2号线站厅层双点火灾为相对安全火灾场景;火源功率的增大会增加地铁火灾危险性,但不同火源位置工况中的安全指数变化趋势相似;排烟模式开启前,1号线站厅层火灾会导致较大的火灾危险性;排烟模式开启后,地铁总安全指数显著上升且安全指数变化趋势改变,此时2号线站台层火灾会导致较大的火灾危险性。     

基于疲劳累积破坏机制的储罐结构动力可靠度分析

针对随机风载荷作用下储罐结构动力可靠性问题,以300 m3的中小型立式低温储罐为研究对象,利用AR模型进行数值模拟得到风载荷的脉动风速时程与脉动功率谱密度函数。采用ANSYS建立储罐三维有限元模型,并对储罐进行动力学分析,计算出储罐结构的随机响应,进而求出随机风载荷作用下储罐结构动力可靠性所需全部数字特征,最后利用疲劳累积损伤机制计算得到储罐的动力可靠度。结果表明:假设结构强度不随时间退化,前5 a动力可靠度基本保持不变,随着使用年限的延长,动力可靠度下降速度明显增大。研究方法可为储罐的动力可靠性及寿命预测提供一定的理论依据。     

基于社会技术系统的复工企业疫情防控风险路径研究*

为对复工企业疫情防控中的风险致因因素进行分析,探寻复工企业疫情防控的风险路径,基于社会技术系统理论,建立宏观工效学模型,通过查阅并分析国家、地方政府、企业文件以及相关文献,从人员、技术、组织管理、内部环境及外部环境5个子系统出发,识别出16个复工企业疫情失控致因因素;运用社会网络分析（SNA）构建复工企业疫情防控关系网络,对各因素节点中心度进行计算,分析各节点在网络中的位置及影响程度;采用贝叶斯网络（BN）进行参数学习和推理学习,找出复工企业疫情失控的最大致因链。结果表明:复工企业疫情失控关系网络中,存在政府监督管理不力→防疫物资筹备不足→日常监管不到位,政府监督管理不力→ 防疫宣传、培训缺失→员工防疫知识欠缺,政府监督管理不力→防疫宣传、培训缺失→日常监管不到位3条最长风险路径。研究结果可帮助复工企业针对最长风险路径中的因素进行管理,从而有效地为复工企业防疫提供理论支持。     

基于等级全息建模的输油泵机组风险根源辨识*

为“挖掘”输油泵机组风险根源,降低设备预知性维护难度,结合输油泵多准则风险评价,提出1种基于等级全息建模的输油泵机组风险根源辨识方法,运用等级全息建模方法将输油泵系统分解为泵体结构、管理因素、环境因素、操作因素、技术因素、运行因素、设备安装7个子系统进行定性和定量分析。结果表明:相比危险与可操作性分析（HAZOP）、事故树分析（FTA）等传统风险辨识方法,等级全息建模（HHM）对轴承等关键部件以及压力等运行参数的监测更为深入,能够有效辨识输油泵机组高风险情景,提升输油泵的风险辨识效率。     

A Bayesian network-based approach for the assessment and management of ageing in major hazard establishments

Currently, there is an increasing attention towards ageing of industrial equipment, as the phenomenon has been recognised as a cause of severe accidents, recorded in the last years in many process establishments. Recent studies described ageing through a number of key-factors affecting the phenomenon by accelerating or slowing it down. The Italian Competent Authority for the prevention of chemical accidents (Seveso III Directive) adopted a short-cut method, accounting for the assessment of these factors, to evaluate the adequateness of ageing management during inspections at Seveso sites. In this paper, a Bayesian Network was developed, by using the data gathered during the first application of the short-cut method, with the aim to verify the robustness of the approach for ageing assessment and the validity of the a priori assumptions used in assessing the key-factors. The structure of the Bayesian network was established by using experts’ knowledge, whereas the Counting Learning algorithm was adopted to execute the parameter learning by means of the software Netica. The results showed that this network could effectively explore the complex logical and uncertain relationships amongst factors affecting equipment ageing. Results of the present study were exploited to improve the short-cut method.     

Effects of nitrogen and carbon dioxide on hydrogen explosion behaviors near suppression limit

By varying inert gas content, equivalence ratio and initial pressure, this study is aimed at investigating flame propagation behaviors and explosion pressure characteristics near suppression limit. For carbon dioxide, the weakest flame floating phenomenon is observed at Φ = 1.5 and the buoyant instability is enhanced when the equivalent ratio deviates to the rich and lean sides. For nitrogen, the buoyant instability decreases with increasing equivalent ratio. Both maximum explosion pressure and maximum pressure rise rate increase firstly and then decrease with the increase of equivalence ratio, and they decrease significantly with increasing content of carbon dioxide and nitrogen. For carbon dioxide, the critical suppression ratio of Φ = 0.6, 0.8, 1.0, 1.5 and 2.0 is 7.50, 7.18, 5.74, 3.83, and 2.87. For nitrogen, the critical suppression ratio of Φ = 0.6, 0.8, 1.0, 1.5 and 2.0 is 15.83, 11.87, 9.50, 6.33 and 4.75. Compared to nitrogen, the carbon dioxide is more effective on suppressing hydrogen explosion pressure. The adiabatic flame temperature, thermal diffusivity and mole fraction of active radicals continue to decrease with increasing content of carbon dioxide and nitrogen, which contributes to the decrease of laminar burning velocity.     

Recent application of Computational Fluid Dynamics (CFD) in process safety and loss prevention: A review

In recent years, significant progress has been made to ensure that process industries are among the safest workplaces in the world. However, with the increasing complexity of existing technologies and new problems brought about by emerging technologies, a strong need still exists to study the fundamentals of process safety and predict possible scenarios. This is attained by conducting the corresponding consequence modeling and risk assessments. As a result of the continuous advancement of Computational Fluid Dynamics (CFD) tools and exponentially increased computation capabilities along with better understandings of the underlying physics, CFD simulations have been applied widely in the areas of process safety and loss prevention to gain new insights, improve existing models, and assess new hazardous scenarios. In this review, 126 papers from 2010 to 2020 have been included in order to systematically categorize and summarize recent applications of CFD for fires, explosions, dispersions of flammable and toxic materials from accidental releases, incident investigations and reconstructions, and other areas of process safety. The advantages of CFD modeling are discussed and the future of CFD applications in this research area is outlined.     

煤矿水害风险量化评价方法

为提高煤矿防治水管理水平,预防和消除矿井水害,在层次分析法的基础上建立中性值作为参照对象对矿井水害风险进行实时评判的方法。根据《煤矿防治水细则》建立以矿井水文地质类型、矿井涌水量标准分数、突水预兆、采掘面位置、探水结果为准则层的层次结构模型,并对各评价指标赋权。依据制定的水害风险评价指标的评分细则和监测监控数据并结合其权重得到水害评价总得分。通过总得分与中性参照分数比较得出预测结果:水害评价总得分大于中性参照分数,证明水害的威胁小,分数越高越安全;反之则水害的威胁较大,分数越低越危险,这时需要加强防治水的力度,令评价分数管控大于中性参照分数。这种方法依赖于井下监测监控数据进行量化评价,能实时、客观、全面且准确地反映煤矿水害的风险情况。     

基于模糊推理的FRAM事故定量分析方法研究

为有效克服FRAM事故分析中无法进行定量分析的缺陷,提出结合模糊推理技术的Fuzzy FRAM模型。此改进模型基于FRAM识别系统运行状态;依据功能输出要素的时间/精度属性利用Matlab构建2阶模糊推理系统量化功能输出质量;根据通用性能条件(CPC)及功能输入耦合端口构建功能评价体系,针对评价体系中存在的不确定性信息融合及建模问题,采用模糊证据推理技术,通过模糊信度结构建立、数据处理、信息融合测度后获得功能的风险指数;以既有铁路危险品运输事故为例,验证方法的可行性。结果表明:Fuzzy FRAM模型的评估结果较为精确,是FRAM分析方法的有效补充。     

安全信息认知对心理安全感的作用机理研究

为揭示安全信息认知对员工心理安全感的影响,把握信息时代背景下心理安全感的研究趋势。基于安全信息认知的背景与特征,构建心理安全感的安全信息认知流程模型。通过描述安全信息对心理安全感的影响机理,从需要、动机、意识、期望剖析心理安全感的安全信息认知动力,归纳心理安全感的安全信息认知偏好,并从风险管控、安全氛围、安全管理落地、安全防护措施设计、员工安全生产积极性方面论述心理安全感在企业的应用对策。研究表明,员工安全信息认知对其心理安全感具有重要影响,是引起心理安全感波动的关键因素,也为心理安全感在企业的应用提供指导。