基于Logistic回归的燃气管网风险因素重要度分析方法研究

为确定燃气管网风险评估的关键风险因素,以A省各地市燃气管网为研究对象,基于燃气专家经验确定燃气管线风险等级,提出基于Logistic回归的燃气管网风险因素重要度分析方法。采用样本增强及随机抽样的方式,选取400个均衡样本作为管网评估数据输入,通过因子分析方法对其进行降维,得到3个公共因子并作为一级指标反向构建燃气管网风险评估指标体系;利用有序多分类Logistic回归方法,根据回归系数绝对值大小对风险因素进行重要度排序。研究结果表明：外界环境对燃气管网风险的贡献程度相对较高,管道自身因素和巡检养护次之。研究结果可为城市燃气风险防控提供理论依据和方法参考。     

Privatisation and outsourcing in wartime: the humanitarian challenges

The tendency today to privatise many activities hitherto considered the exclusive preserve of the state has given rise to sharp debate. The specific nature of humanitarian emergencies elucidates in particularly stark contrast some of the main challenges connected to the privatisation and outsourcing of essential public services, such as the provision of drinking water and health care. Privatising the realms of defence and security, which are at the very core of state prerogative, raises several legal and humanitarian concerns. This article focuses on the roles and responsibilities of the various parties involved in armed conflicts, especially those of private companies engaged in security, intelligence and interrogation work, and in the provision of water supply and health services. It highlights the need for humanitarian and development actors to grasp better the potential risks and opportunities related to privatisation and outsourcing with a view to supplying effective protection and assistance to communities affected by war.     

基于CA的城市形态扩展多解模拟——以北京市东部平原区情景分析为例

构建了一个基于人工神经网络的约束型城市扩展CA模型。利用该模型,预测了北京市东部平原区在3种情景规划之下的未来50年的城市形态,为不同的城市发展模式之间的比较分析奠定基础。然后以2024年的北京东部平原区模拟城市形态为基准,从自然生态功效、社会服务功效、经济利益功效3个方面对3种规划模式进行了情景分析,从而系统的比较了3种规划模式的复合生态功效,为城市规划决策提供有力的支持。     

Application of dynamic risk analysis in offshore drilling processes

Process safety is the common global language used to communicate the strategies of hazard identification, risk assessment and safety management. Process safety is identified as an integral part of process development and focuses on preventing and mitigating major process accidents such as fires, explosions, and toxic releases in process industries. Accident probability estimation is the most vital step to all quantitative risk assessment methods. Drilling process for oil is a hazardous operation and hence safety is one of the major concerns and is often measured in terms of risk. Dynamic risk assessment method is meant to reassess risk in terms of updating initial failure probabilities of events and safety barriers, as new information are made available during a specific operation. In this study, a Bayesian network model is developed to represent a well kick scenario. The concept of dynamic environment is incorporated by feeding the real-time failure probability values (observed at different time intervals) of safety barriers to the Bayesian network in order to obtain the corresponding time-dependent variations in kick consequences. This study reveals the importance of real-time monitoring of safety barrier performances and quantitatively shows the effect of deterioration of barrier performance on kick consequence probabilities. The Macondo blowout incident is used to demonstrate how early warnings in barrier probability variations could have been observed and adequately managed to prevent escalation to severe consequences.     

隧道救援站通风网络优化设计及人员疏散研究*

为确定铁路隧道救援站最佳通风结构,对烟道布置提出合理建议,采用计算流体力学（CFD）的方法,对铁路隧道救援站通风网络进行优化设计。同时,采用模拟计算的方法对救援站人员疏散进行模拟分析,确定救援横通道布置及防护门开度设置的合理性。研究结果表明:在同等通风参数工况设置下,采用多节点排烟竖井结构后各救援横通道流量分配更均匀,救援站压力平衡性更好,通风效率可提升15%;通过疏散模拟证实,在长560 m的紧急救援站范围内设置10条疏散横通道,横通道设1.7 m宽的逃生门能够满足疏散要求。     

提高GPS定位精度的群调度滤波算法*

为解决现行安全生产科技领域中全球定位系统（GPS）/惯性导航系统（INS）融合系统容易产生较大时变误差的关键问题,满足GPS定位信号的精度和信号数据处理时间的要求,提出1种群调度滤波算法,通过实验仿真,分别与模糊算法、机器学习算法及卡尔曼滤波网络算法进行比较研究。结果表明:群调度滤波算法兼顾了定位精度与数据处理时间,具有较大优势,可在航空安全、船舶安全、应急监测、灾后抢险等安全科技领域广泛应用。     

基于复杂网络的燃气管线破裂灾害链风险分析*

为提高燃气管线突发事件应急处置决策水平和应急响应能力及效率,采用复杂网络理论和灾害链演化机理对燃气管线破裂灾害事件影响进行耦合分析,构建燃气管线破裂灾害链网络和风险评估模型,并计算得出燃气管线破裂灾害链风险度。为更准确地表达无传播路径的灾害事件之间的关系,将灾害网络中所有最短路径长度的最大值作为其最短路径长度,计算表明这种算法更符合灾害传播实际情况。结果表明:通过燃气管线破裂灾害链风险分析,能够为燃气管线灾害风险控制措施和方案制定提供参考,有利于提高燃气管线破裂灾害事件的应急处置能力和决策水平。     

基于改进模体方法的国家应急组织合作网络基元比较

为分析和比较应对非常规突发事件过程中,由不同类型组织个体及其不同频次合作关系构成的应急复杂组织网络的微观结构特征,研究运用表征个体差异和关系强弱的改进模体分析方法,以中国和美国国家应急组织合作网络为例,比较分析其基元同构与异构特征。结果表明:中美应急组织系统不同类型的应急主导和支持组织构成的主要合作模式具有同构性,但子图结构数量分布具有异构性;考虑个体间关系频次差异,中美应急组织网络基元合作模式具有形式同构但相对数量分布异构的特征;比较而言,美国合作网络为分布式、分权化和关系型基元构型,中国合作网络具有集中式、集权化和契约型基元特征。     

氧化还原体系低温引发丙烯酸酯乳液聚合安全风险研究

以甲基丙烯酸甲酯、丙烯酸酯乙酯、丙烯酸酯丁酯为反应单体,十二烷基苯磺酸钠为乳化剂,过硫酸铵为氧化剂,亚硫酸氢钠为还原剂,在低温下进行乳液聚合。主要研究了反应单体的热稳定性及反应过程中的相关热力学参数,最后按照规定对该聚合体系进行了安全风险研究。研究结果表明,丙烯酸酯混合单体无热分解放热风险,丙烯酸酯乳液体系的绝热温升(△Tad)为49.6℃,失控体系能达到的最高温度(MTSR)为91.9℃,该体系的最终反应工艺危险度评估为1级,聚合工艺热风险低。     

基于人工神经网络的气体泄爆最大超压预测研究

为解决传统经验公式在预测气体泄爆中最大超压出现时的较大偏差或过于保守的问题,提出使用人工神经网络预测气体泄爆最大超压。基于124组实验数据,采用BP与RBF神经网络,通过优化算法计算与迭代循环对泄爆样本中的影响因素进行降维与选择,并确定2类神经网络本身在学习与计算气体泄爆样本时的相关参数。结果表明:PCA（主成分分析法）在当前样本条件下的降维效果较差,而通过迭代对比确认气体泄爆样本中的5类特征全部保留时神经网络的训练模拟效果最好;通过对124组实验数据进行随机挑选训练集与测试集的训练模拟结果发现,神经网络对气体泄爆中最大超压的预测效果较好;通过对比Molkov提出的和经Fakandu等改进的NFPA 68经验公式以及2类神经网络的预测结果表明,神经网络相比于传统气体泄爆经验公式具有明显优势。