The impact of the COVID-19 pandemic on the safety management in Italian Seveso industries

The paper discusses the impact of the COVID-19 pandemic on the Italian chemical and process industries, where Directive 2012/18/EU Seveso III, for the control of Major Accident Hazard (MAH), is enforced. The Safety Management System (SMS) for the control of MAH, which has been mandatory for 20 years in Italian Seveso Establishments, has been highly stressed by the external pressure, related in some way to the COVID-19 pandemic. Fairly, most companies, in particular in oil and gas sectors, have demonstrated an adequate capability to reconcile operation continuity and health requirements. This experience is providing the establishment operators and the regulators with valuable suggestions for the improvements of the SMS-MAH. Within this framework, an innovative organisational resilience model is proposed, aiming at the development of a higher capability to face future new crisis. The current SMS-MAH already includes some basic pillars to enhance resilience, which were valuable during the pandemic crisis, but a full and rationale development is still needed. Starting from the first pandemic phase experience, this paper presents a novel tool to assess the degree of “resilience” of a SMS-MAH. It is based on a questionnaire, featuring 25 questions grouped into eight items, according to the typical SMS-MAH structure. A two level AHP model has been developed in order to define the weights to be assigned to each point. The AHP panel included industrial practitioners, regulators, authorities and researchers. The results are based on the COVID-19 experience and consequently the developed model is tailored to face health emergencies, but the approach may be easily transferred to other external crises.     

突发事件下人群应急信息传播策略推演方法研究*

为提升突发事件预警信息传播能力,拓宽预警信息传播渠道,增强预警信息传播多元化特征,提出群体内个体传播影响力评估方法及应急信息传播模式制定方法,并基于网络分析与多智能体建模,研究群体应急信息传播策略制定方法与有效性分析手段,重点阐述方法实施路径与应用方向。研究结果可用于制定基于社会网络的应急信息传播策略,并通过多智能建模对应急信息传播情景进行有效性推演。     

体育馆应急医疗功能转换的可行性评估*

为高效实现体育馆建筑的应急医疗功能转换,建立城市应急医疗体系,在探讨相关案例和体育馆建筑特点的基础上,提出在规划选址、室外空间、主体建筑、基础设施、应急响应能力5个方面建立体育馆应急医疗功能转换的可行性评估指标体系,并采用层次分析法确定各级指标的权重。以某市体育中心为例验证评估指标的合理性。结果表明:该评估指标体系能够合理反映城市体育馆应急医疗功能的差异,具有实用性和可操作性。     

Land-traffic crash leading to passenger vehicle submersion,drowning and other fatal injuries: A 44-year study based on records from the Finnish Crash Data Institute

Background: Land motor traffic crash (LMTC) -related drownings are an overlooked and preventable cause of injury death. The aim of this study was to analyze the profile of water-related LMTCs involving passenger cars and leading to drowning and fatal injuries in Finland, 1972 through 2015. Materials and methods: The database of the Finnish Crash Data Institute (FCDI) that gathers detailed information on fatal traffic accidents provided records on all LMTCs leading to drowning during the study period and, from 2002 to 2015, on all water-related LMTCs, regardless of the cause of death. For each crash, we considered variables on circumstances, vehicle, and fatality profiles. Results: During the study period, the FCDI investigated 225 water-related LMTCs resulting in 285 fatalities. The majority of crashes involved passenger cars (124), and the cause of death was mostly drowning (167). Only 61 (36.5%) fatalities suffered some–generally mild–injuries. The crashes frequently occurred during fall or summer (63.7%), in a river or ditch (60.5%), and resulted in complete vehicle’s submersion (53.7 %). Half of the crashes occurred in adverse weather conditions and in over 40% of the cases, the driver had exceeded the speed limit. Among drivers, 77 (68.8%) tested positive for alcohol (mean BAC 1.8%). Conclusion: Multidisciplinary investigations of LMTCs have a much higher potential than do exclusive police and medico-legal investigations. The risk factors of water-related LMTCs are similar to those of other traffic crashes. However, generally the fatal event in water-related LMTC is not the crash itself, but drowning. The paucity of severe physical injuries suggests that victims’ functional capacity is usually preserved during vehicle submersion. Practical Applications: In water-related LMTCs, expansion of safety measures is warranted from general traffic-injury prevention to prevention of drowning, including development of safety features for submerged vehicles and simple self-rescue protocols to escape from a sinking vehicle.     

基于APRIORI-TAN的交通事故伤害分析与预测*

为探究道路交通事故因素和事故伤害的相关性,以2 467起涉及人员伤亡的交通事故为数据集,运用Apriori算法分别挖掘事故伤害关联规则,并结合社会网络分析的可视化和核心-边缘分析构建受伤事故和死亡事故的关联规则网络。结果表明:事故伤害程度与事故时间、道路条件和交通环境等因素关系紧密,尤其死亡事故与碰撞固定物、人行横道事故、高速公路、高速道路、非市区、酒驾和超速存在高相关性。基于树型贝叶斯网络（TAN）构建事故伤害程度的预测模型,预测结果准确率可达87.56%。     

基于半定量的FRAM道路危险品运输事故分析方法研究*

为弥补事故分析法在道路危险品运输事故致因研究方面的缺失,解决传统事故分析方法分析结果不全面、防控措施不具体且针对性较差的问题,引入半定量功能共振事故模型（FRAM）,通过定量化功能上下游耦合变异性,阐述事故发生机理同时,找到系统关键功能和关键链路,制定防控措施重点监控。结果表明:基于半定量的FRAM道路危险品运输事故分析方法能够更快、更准确地找出事故发生的关键功能和关键链路,制定针对性防控措施,有效提高道路危险品运输系统安全性。研究结果可为道路事故分析提供参考。     

基于“纵深防御”原则的危化企业事故预防系统建立

危险化学品生产是当前的高危行业和安全管理的重点领域。面对事故频发的严峻形势,如何开展好危险化学品生产企业的安全管理,建立事故预防系统防止事故的发生非常关键。“纵深防御”原则作为核电厂实现核安全的一项基本原则,为核电厂长期稳定安全的发展奠定了坚实的基础,对危化企业提升事故预防能力,建立事故预防系统有较强的借鉴意义。借鉴“纵深防御”原则,文章分析危化企业应用“纵深防御”原则预防和减少事故发生的必要性,结合生产特点建立了事故纵深防御系统,对企业提高安全管理水平,预防事故的发生有重要的意义。     

基于ARIMA和XGBoost组合模型的交通事故预测

近年来交通事故及其损失严重影响社会经济的发展和人民生活的提高,交通事故预测可以为交通事故预防提供数据支持。基于自回归滑动平均(ARIMA)模型和极端梯度提升(XGBoost)模型,构建时间序列组合预测模型,对交通事故相关指标进行趋势预测。根据交通事故的特点,选定"事故起数""受伤人数""死亡人数"及"损失"4个指标。首先,根据自相关、偏自相关图确定ARIMA模型参数,根据AIC(赤池信息准则)值确定最终模型;然后,对4个指标的ARIMA模型预测结果的残差构建残差序列,对其进行XGBoost建模,得出修正后的残差预测值;最后,根据残差预测值和ARIMA模型预测值得出组合模型最终的预测值。实例结果表明,4项指标的混合预测模型的预测精度均优于单一的ARIMA模型和Holt-winters模型,其中以"受伤人数"和"死亡人数"的模型改善效果最为显著,"受伤人数"指标的平均绝对百分比误差降低了5.431 7个百分点,"死亡人数"指标的平均绝对百分比误差降低了3.625 9个百分点。     

突发公共卫生事件下多阶段应急救援物资配置研究*

为提高突发公共卫生事件背景下应急救援物资分配效率,减少人员伤亡与经济损失,以应急物资需求未满足所导致的损失最小及物资分配总距离最短为目标,研究重大公共卫生事件爆发后不同阶段下应急物资分配问题。构建优化模型,并通过某城市中13个物资需求点的应急物资分配案例验证模型的科学性与合理性。结果表明:本文方法能有效解决动态需求下应急物资分配问题,为解决突发公共卫生事件下应急物资配置提供参考和借鉴。     

基于事理图谱的电力安全事故预控方法*

为解释全国电力安全事故的演化规律并为预控事故的发生,提出电力安全事故事理图谱的构建与推演方法。以国家能源局发布的全国电力安全生产情况为数据源,使用规则模板提取事件槽对;利用Word2vec训练词向量,通过事件槽相似度计算泛化事件槽,并以热力图矩阵记录泛化权重;采用Neo4j构建事故事理图谱,以泛化权重和事件链的方向预测事故走向。结果表明:方法能够较好地揭示事故演化的关键节点、预演电力安全事故发展路径,为事故的预控提供1种有效的知识服务方案。