虚拟现实地理信息系统技术在城市环境污染突发事件中应用探讨

通过分析事件驱动原理,将事件驱动机制（EDI）融入虚拟现实地理信息系统（VRGIS）的建模框架,探索基于VRGIS的事件驱动时空模型及其在城市环境污染突发事件响应中的应用前景以及主要技术设计过程,旨在为资源与环境的可持续利用研究提供一个形象直观的虚拟演示平台来反映城市中环境变化的空间响应及其对策定制等问题。     

金矿尾矿库渗漏后治理措施的探寻

分析了金矿尾矿库发生渗漏的原因,重点介绍了尾矿库渗漏后的综合治理措施。通过治理措施的实施,不仅解决了尾矿库渗漏问题,而且为尾矿库的增高扩容提供了良好的条件。其成功经验可以为类似金矿企业所借鉴。     

填埋场直流电阻电路模型及分析

为研究垃圾填埋场的导电特性,建立了一种填埋场直流电阻电路模型,并对回路中的各部分电阻进行了分析.结果表明:随着供电电极直径和入土深度的增加,回路电阻减小,而随着供电电极与漏洞之间距离的增大,回路电阻缓慢增加;漏洞电阻由接触电阻和内阻组成,前者远大于后者,对一个半径为1cm的圆形漏洞来说,接触电阻可达1500Ω,而内阻只占到接触电阻的1/10;在供电电极周围浇水可明显降低回路电阻,在场内电极直径为20mm,入土深度为0.4m,电极与漏洞之间距离为20m时,浇水后的回路电阻可减小26.6%.     

Numerical study on the horizontal stretching effect of ground on high-pressure vapor jets of LNG tank leakage

The objective of this work is to investigate the horizontal stretching effect of ground on high-pressure vapor jet of LNG tank leakage near the ground. A numerical model for leakage jet was developed and several series of leakage scenarios were theoretically analyzed for different heights of the tank orifice, inner pressures and outer temperatures. The results show that the near ground plays an important role in the horizontal transportation of LNG leakage vapor. The corresponding danger distance is surprisingly lengthened because of the horizontal stretching of leakage vapor cloud by the ground nearby, especially for those cases with a lower orifice on tank. It is illustrated that there is an obvious change for the central axis track, gas concentration and velocity of the jet in the far-field during the jet is touching the ground. In addition, the dimensionless analyses on the dependence of gas concentration, velocity and gas concentration on the transportation distance indicated that there were two stages of deflection behaviors of the jet. Finally, the enlarged danger distance by the horizontal stretching for the LNG tank leakage with a low orifice indicated the more dangerous scene of those leakage close on ground. The data and revelation here about the danger area prediction can be an important guide for the emergency management during the LNG tank leakage accidents.     

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.     

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。