Sensitive Resource and Traffic Density Risk Analysis of Marine Spill Accidents Using Automated Identification System Big Data

This study developed a new methodology for analyzing the risk level of marine spill accidents from two perspectives,namely,marine traffic density and sensitive resources.Through a case study conducted in Busan,South Korea,detailed procedures of the methodology were proposed and its scalability was confirmed.To analyze the risk from a more detailed and microscopic viewpoint,vessel routes as hazard sources were delineated on the basis of automated identification system(AIS)big data.The outliers and errors of AIS big data were removed using the density-based spatial clustering of applications with noise algorithm,and a marine traffic density map was evaluated by combining all of the gridded routes.Vulnerability of marine environment was identified on the basis of the sensitive resource map constructed by the Korea Coast Guard in a similar manner to the National Oceanic and Atmospheric Administration environmental sensitivity index approach.In this study,aquaculture sites,water intake facilities of power plants,and beach/resort areas were selected as representative indicators for each category.The vulnerability values of neighboring cells decreased according to the Euclidean distance from the resource cells.Two resulting maps were aggregated to construct a final sensitive resource and traffic density(SRTD)risk analysis map of the Busan–Ulsan sea areas.We confirmed the effectiveness of SRTD risk analysis by comparing it with the actual marine spill accident records.Results show that all of the marine spill accidents in 2018 occurred within 2 km of high-risk cells(level 6 and above).Thus,if accident management and monitoring capabilities are concentrated on high-risk cells,which account for only 6.45%of the total study area,then it is expected that it will be possible to cope with most marine spill accidents effectively.

Probabilistic Approach to Risk Analysis of Chemical Spills at Sea

Risk analysis of chemical spills at sea and their consequences for sea environment are discussed. Mutual interactions between the process of the sea accident initiating events, the process of the sea environment threats, and the process of the sea environment degradation are investigated. To describe these three particular processes, the separate semi-Markov models are built. Furthermore, these models are jointed into one general model of these processes interactions. Moreover, some comments on the method for statistical identification of the considered models are proposed.

Analysis of the Tragedy of Vila Socóin Cubatão (São Paulo, Brazil) Using the Haddon Matrix: A Comprehensive Examination of Socio-Environmental Factors and Risk Mitigation Strategies

The tragedy of Vila Socó epitomizes the socio-environmental repercussions of rapid industrialization in Cubatão. Beginning in the 1940s with the construction of the Anchieta highway, the city experienced an influx of migrants drawn by burgeoning industries, leading to unplanned urban growth and the emergence of vulnerable communities like Vila Socó. This article examines the interconnected factors—such as demographic shifts, inadequate planning, and regulatory oversight—that culminated in the devastating fire of 1984, claiming numerous lives and highlighting systemic failures. Utilizing the Haddon Matrix, this study dissects the Vila Socó incident, emphasizing the roles of human error, infrastructure integrity, and socio-economic disparities in disaster causation. By contextualizing the tragedy within Cubatão’s industrial trajectory, it underscores the urgent need for comprehensive risk assessment and proactive mitigation strategies in rapidly developing regions globally. Beyond its immediate focus, this work offers broader insights into the dynamics of industrial disasters and their socio-economic implications. As pipelines continue to play a vital role in global energy infrastructure, the lessons drawn from Vila Socó’s tragedy resonate deeply, emphasizing the imperative of robust safety protocols and accountable governance to prevent similar catastrophes in the future.

A STAMP-Game model for accident analysis in oil and gas industry

Accidents in engineered systems are usually generated by complex socio-technical factors.It is beneficial to investigate the increasing complexity and coupling of these factors from the perspective of system safety.Based on system and control theories,System-Theoretic Accident Model and Processes(STAMP)is a widely recognized approach for accident analysis.In this paper,we propose a STAMP-Game model to analyze accidents in oil and gas storage and transportation systems.Stakeholders in accident analysis by STAMP can be regarded as players of a game.Game theory can,thus,be adopted in accident analysis to depict the competition and cooperation between stakeholders.Subsequently,we established a game model to study the strategies of both supervisory and supervised entities.The obtained results demonstrate that the proposed game model allows for identifying the effectiveness deficiency of the supervisory entity,and the safety and protection altitudes of the supervised entity.The STAMP-Game model can generate quantitative parameters for supporting the behavior and strategy selections of the supervisory and supervised entities.The quantitative data obtained can be used to guide the safety improvement,to reduce the costs of safety regulation violation and accident risk.

Statistical Safety Analysis of Maintenance Management Process of Excavator Units

Within this paper, the process of statistical safety analysis has been presented, which involves the following steps： formulation of basic principles of statistical safety analysis, initial events analysis, accident sceneries progress analysis, risk calculation, and risk calculation results analysis. On this basis, it has been concluded that the bucket wheel excavator SRs 1200×24/4×0（400 kW）＋VR safety criteria is the mechanism for the hoist of rotor＇s arrow failure modes, because in that case whole bucket wheel excavator failure would necessarily happen （excavator falling down on counterweight）. Therefore, excavator units statistical safety analysis is accomplished preventively to obtain its effective maintenance management.

Maritime Oil Spill Risk Assessment for Hanhikivi Nuclear Power Plant

Fennovoima is planning to build a new nuclear power plant unit-Hanhikivi 1, on a greenfield site in Northern Finland. A nearby maritime oil spill accident is one of the external events analysed in the probabilistic risk assessment of the plant. In the worst case, the oil could cause a loss of the ultimate heat sink by blocking the sea water intake screens. By considering the maritime traffic, oil transport and oil spill accident data in the Baltic Sea area, the annual probabilities of nearby, significant oil spills are evaluated. Event tree analysis is used to evaluate the probability that significant amount of oil enters the plant intake tunnel. The spill behaviour is considered, including oil spreading, dissolution, dispersion and movement due to wind and currents. In addition, oil combat measures including the use ofoil booms and skimmers are evaluated.

基于数据驱动贝叶斯网络的化工事故风险分析

为减少化工厂风险分析中的主观干预,基于关联规则和贝叶斯网络构建1种数据驱动风险分析模型。该模型涵盖3个任务项,分别为数据集项、关联规则驱动项和贝叶斯网络风险评估项。首先,收集事故报告和事故因素构建事故数据库;其次,将事故数据导入Apriori算法,并根据关联规则的因素相关性确定贝叶斯网络和条件概率表结构;然后,基于事故因素出现频率计算先验概率和条件概率,并采用Fussel-Vesely计算事故因素的敏感度;最后,收集94起危险化学品中毒窒息事故实例,运用数据驱动风险分析模型评估事故因素的影响大小。研究结果可为减少和避免化工事故提供一定参考,有助于提高相关企业的整体安全水平。

危险货物运输驾驶人风险倾向分类及识别模型研究

为合理评估危险货物运输驾驶人驾驶过程中的风险倾向,建立危险货物运输驾驶人风险倾向聚类及辨识体系,以动态监控系统中记录的驾驶人实时违规预警数据为基础,选取可能引发交通冲突的安全关键事件为特征参数,利用探索性因子分析方法实现指标降维,提取驾驶人风险倾向主因子,并通过K means算法聚类不同风险倾向的驾驶人,最后基于聚类结果监督训练随机森林模型,辨识未知驾驶人的风险倾向。结果表明,利用选取的8类安全关键事件特征参数,可以将驾驶人风险倾向划分为攻击驾驶倾向、鲁莽驾驶倾向、驾驶分神倾向和驾驶疲劳倾向,且可以识别风险较低的驾驶人,基于随机森林模型的驾驶人风险倾向识别准确率为88.68%,可以较好地实现危险货物运输驾驶人风险倾向辨识。研究结果为危险货物运输驾驶人风险倾向分类及识别提供了方法依据。

基于DNV SAFETI Route模型的危险货物道路运输风险模拟

DNV SAFETI Route运输路线模型是专业的运输活动风险评估模型,根据所有可能发生事故的地点分布潜在事故的总频率,计算出沿线的总体风险水平。选择事故场景为大孔泄漏,对发生泄漏情景引发的火灾、爆炸和毒性物质扩散事故后果进行预测。根据后果预测结果,进而可以得到周边防护目标所承受的个人风险和社会风险曲线。

基于SA-Apriori的道路事故风险评估研究

道路事故风险评估是提高道路安全水平的有效方式。为实现在道路网络特征视角下的道路事故风险评估,融合线段分析与频繁集算法,提出SA-Apriori的特征提取算法,进而构建SA-Apriori道路事故风险评估模型,以重庆市大渡口区作为分析对象,建立以道路网络特征变量为指标的道路事故风险等级划分体系,评估其道路事故风险水平,结合商业点位分布情况对该评估方法的有效性进行验证。并针对大渡口区道路事故风险情况,提出道路事故风险的管理对策与建议。结果表明:该道路事故风险评估方法具有较高的可靠性,可为基于路网特征的道路事故风险评估提供参考。

基于改进Apriori算法的道路运输事故致因分析

为深入研究我国道路运输事故的致因因素,探究各因素之间的相关联系,提出一种改进的关联规则算法,并将其运用于道路运输事故数据分析。首先,将预处理后的数据进行分类,建立多维层体系框架;其次,对影响事故属性的因素进行灰色关联分析,生成新的候选项集;最后,运用考虑定向约束的Apriori算法挖掘关联规则。基于广西壮族自治区2019—2022年道路运输事故数据并对其进行详细分析,结果表明:道路运输事故中夜间时段发生事故的原因大多为疲劳驾驶,由于驾驶员行车速度不当造成追尾事故的发生。与运用传统的Apriori算法相比,该方法生成的无效规则减少了69.15%,准确率提高了49.14%,在保证准确性提升的前提下大大提高算法的效率。

基于STPA-BN的船舶航行人为风险因素分析与评估

人为因素是引发船舶事故的最主要因素之一,为了研究船舶人为风险因素的因果关系,从中国海事局发布的船舶事故报告出发,引入系统理论过程分析-贝叶斯网络(STPA-BN)模型对船舶航行人为风险因素进行分析和评估。采用系统理论过程分析(STPA)方法识别出船舶航行中存在的不安全控制行为,结合事故报告内容提取出12种人为风险因素,利用风险因素的内在因果关系和结构学习功能构建贝叶斯网络拓扑结构;将事故报告量化,并对网络进行参数学习,对模型进行验证。在此基础上,利用贝叶斯网络(BN)的推理功能得到船舶航行中7种突出的人为风险因素和3条事故核心致因链,为保障船舶安全航行与船员培训提供数据支持。

基于HFACS的道路运输事故致因分析与分类系统研究

为了深入研究道路运输事故的致因因素,挖掘出关键致因规则,在人因分析和分类系统(HFACS)的基础上,构建道路运输事故致因分析与分类系统(RTAACS),并根据该系统框架对收集到的事故进行分析。首先将RTAACS框架分为监管部门、道路运输企业、驾驶人3个层级,将事故致因因素纳入该系统框架进行频率统计,通过R语言改进卡方检验、让步比分析得出致因因素之间的关联规则,最后根据ANP网络层次分析法计算各项致因因素的权重,并确定关键致因规则。结果表明:工作流程与不充分的企业监督、工具技术与习惯性违规、资源管理与工具技术、资源管理与习惯性违规、未纠正的已知错误与习惯性违规为道路运输事故的关键致因规则。研究构建的系统框架以及提出的分析方法为道路运输业的安全预防提供一定的借鉴意义。

基于N-K模型的石化储罐事故风险耦合度分析

为预防石化储罐事故,通过收集212份石化储罐事故报告,将事故风险因素归纳为人为、设备、环境、管理4个类别,利用N-K模型分析事故风险因素之间的耦合作用,并运用N-K模型计算各种耦合模式下的风险耦合度,得出了石化储罐事故风险因素的耦合关系及耦合作用规律。结果表明,随着参与耦合的因素增多,风险耦合值总体呈现上升趋势;人为因素与其它因素耦合更容易导致事故;石化储罐区事故各风险因素之间的耦合作用程度相比其它行业更高。研究结果可为石化企业储罐事故管控提供依据和参考。

危险化学品道路运输事故复杂性机理研究综述

为探寻危险化学品道路运输事故复杂性机理的研究现状,基于事故风险特征提出了一种新的文献分类方法。该方法分别从复杂性与复杂系统特征、事故致因理论、事故风险演化过程、事故风险耦合后果4个方面对既有的文献进行综合评述。分析认为,近年来危险化学品道路运输事故相关理论和方法的研究发展迅速,其中事故致因理论研究最为成熟,事故风险演化和事故风险耦合研究正逐步成为关注的重点;既有研究大多集中在系统的宏观层面,微观层面研究较少,且风险和能量如何在不同层面进行传递和转化尚未形成完整的理论,也未揭示系统内部风险因子相互作用及演化发展的过程和规律;基于新的分类方法发现,大多数研究采用单目标求解或多目标优化模型,未能充分考虑运输过程动态风险特征和时变效应,基于事故后果和环境污染风险的事故不确定性分析可能是未来的研究热点。

新兴能源基础设施安全风险分析与防控体系

“双碳”背景下,随着终端电气化水平和氢能利用占比的逐步提高,新兴能源基础设施呈现爆发性增长趋势,与此同时,安全事故频发,安全问题不断凸显,制约了产业的健康发展。对以储能站、充电站、加氢站、综合能源站等为代表的新兴能源基础设施的主要安全风险要素进行了全面梳理,剖析了当前全环节、全链条安全风险认知、防控、监管方面存在的问题和挑战,并进一步总结了新兴能源基础设施安全风险及防控的共性现状和总体形势。在此基础上,从安全防控技术创新、多利益相关方监管、公共安全保障体系建设等维度提出了安全防控体系性框架和应对措施,为我国新兴能源基础设施的安全防控与保障提供支撑和参考。

基于事故树的N-K模型施工事故风险耦合分析

为了研究水平定向钻施工事故风险,考虑事故树定性分析与N-K模型(N为系统的组件数量,K为每个组件与其他组件的交互数量)定量分析方法的缺点,从人为、设备、环境及管理4类风险因素构建一种基于事故树的N-K施工事故风险分析综合模型。通过建立事故树施工底层事件与N-K模型耦合风险因素集合映射关系,分别计算单因素、双因素以及多因素耦合风险概率,求解风险耦合值。结果表明:水平定向钻施工事故风险概率随着风险耦合因素的增加而增大;三因素耦合作用时,设备-环境-管理耦合作用值最大为0.2608,人为-设备-管理次之为0.2034;双因素耦合作用时,环境-管理耦合作用值最大为0.1554;水平定向钻施工事故共有50种引发事故的可能途径,可以按照准备阶段、导向孔钻进阶段、扩孔阶段、管道回拖阶段与规划管理阶段对整体事故风险进行分阶段预防。研究成果一方面可为风险研究提供新的综合模型,另一方面也可为水平定向钻安全施工提供重要的参考依据。

考虑安防措施的撬装氢压缩机系统安全性分析

首先对氢压缩机氢安全事故进行了汇总与分析;进而开展基于故障树的撬装氢压缩机氢燃爆事故危险源识别;然后应用事件树分析,研究考虑系统安防措施的氢安全事故后果与发生概率;最后基于FLACS软件,结合人身与建筑物伤害标准,开展考虑安防措施的射流火焰、闪火与燃爆事故的风险量化评价,并提出了安防措施的优化建议。研究表明:氢泄漏主要是由设计缺陷和操作失误所引发,而氢泄漏检测装置的失效对燃爆事故有较大影响;各类氢安全事故发生概率均小于3.3×10^(-3)/年,但氢气泄漏后氢射流火灾事故发生概率较高;对于射流火焰事故,最高温度可达2 329.8℃,最大热流密度可达399.0 kW/m^(2);对于闪火事故,最大损伤半径可达7.7 m,最高温度可达3 069.5℃;对于燃爆事故,其伤害半径最大为5.5 m,最大超压为10 bar。这些事故均会造成严重的人身伤害与集装箱结构损伤,因此压缩机安全距离应设置为7.7 m以上;而提高氢浓度传感器灵敏度、优化氢浓度传感器布局位置、增强排风系统排风量等措施可有效增强系统的安全性。

基于NBN-EM的地铁施工事故致因分析模型研究

地铁施工事故具有易发性且事故类型复杂多样,针对现有地铁施工事故分析方法多依赖于专家主观经验构建,且仅有较少方法对事故报告信息加以利用的问题,提出一种基于NBN-EM的地铁施工事故致因分析模型。首先,以搜集的2010—2021年间的223起事故报告为数据来源,采用统计学方法提取及筛选风险因素,进一步归纳建立事故致因分析的指标体系;其次,采用改进的朴素贝叶斯网络构建风险因素指标与事故类型关系的图形结构,同时分层随机抽样80%的数据为训练样本,借助EM算法和Netica软件进行数据学习,确定各节点的先验概率和条件概率参数;最后,通过贝叶斯网络推理和敏感性分析得到不同类型事故的关键致因排序,不同视角下的情景分析对风险因素组合作用下的事故发生概率和风险源识别进行了确定。研究结果表明:施工工法、施工方案内容、安全隐患排查分别为三个维度上造成事故发生的最重要因素,不同类型事故的关键风险因素具有差异性,应区别预控,模型测试验证方法的有效性,平均正确率为84.55%。

GNSS边坡监测与事故风险分析平台融合应用

在露天煤矿开采过程中,边坡的稳定性关乎矿山正常的生产运营。在矿山建设投产开始直至采完闭矿,滑坡、裂缝等影响始终贯穿矿山的整个开采周期。传统的人工光学设备边坡稳定性监测方式,无法满足全天候、全时段监测,从而延误了预警的最佳时机。随着卫星导航技术和差分解算技术的发展,GNSS边坡监测方式以其低成本、全天候实时监测的优点逐步成为矿山监测的主要方式。本文以山煤进出口集团河曲旧县露天矿为例,通过两期GNSS边坡、排土场监测案例,介绍了全球卫星导航系统原理、边坡监测系统组织架构、多源数据融合等。