手机定位人口数据在应急救援中的应用

随着智能手机的普及,基于手机定位的人口数据在突发性灾害应急救援领域发挥着日益重要的作用.以近几年地震灾区为主要研究对象,选择灾区中有代表性的旅游景区、县城及乡镇,获取这些区域手机定位的人口数据,同时采用传统方法估算区域内人口数量,并进行差异性对比.研究结果表明:差异性最大的是旅游景区、其次是县城和乡镇;在人口年度变化上...     

江苏省及南京市工业危险废物现状研究与分析

通过对全国、江苏省以及南京市工业危险废物的产生量和排放量进行调查、总结和对比分析,指出江苏省作为一个工业大省、强省,每年工业危险废物的产生量接近全国的10%,且呈逐年下降趋势.而排放量所占比例大于10%,且出现了先降低、再增加、又降低到零的现象,最高时达到16.67%.造成这一现象的原因可能跟工业危险废物的管理有关.同时指出了目前江苏省乃至南京市目前存在的问题以及相应的对策措施.     

氯气泄漏扩散半径估算与应急处置

氯气泄漏是常见的化学事故之一.通过对氯气的理化性质、危险特性和泄漏原因分析,估算氯气泄漏的扩散半径,同时以扩散半径作参考,提出氯气泄漏的应急处置措施,为氯气泄漏事故应急处理提供技术支持.     

智能手机应用程序使用与操作的驾驶分心风险影响研究

为研究智能手机应用程序操作方式与使用行为对驾驶分心影响的问题,探讨智能手机程序操作方式对驾驶分心影响的优劣关系,基于结构方程模型提出4个因果关系假设,构建涵盖程序使用、驾驶分心、驾驶绩效等潜变量的智能手机使用行为影响的结构方程模型。通过收集线下问卷的方式进行调查,搭建模拟场景,设计6项实验方案,通过驾驶模拟实验方式收集相关数据,建立相对偏差矩阵。研究结果表明：手机通话功能的使用(路径系数0.472)对驾驶分心影响显著,手机导航功能使用(路径系数0.256)、手机音乐功能使用(路径系数0.249)对驾驶分心影响不显著。语音交互方式均优于手动操作方式,其中语音交互启动导航方式(F₃=0.019)的影响最小。研究结果可对道路驾驶情况下智能手机应用使用与操作方式的研究起推动作用。     

安全风险分级防控在油气开发领域的探索与应用

为推动油气开发领域安全风险分级防控有效落地,提高风险预控能力,本文基于风险防控现状评估结果,探索性地研究安全风险分级防控思路,构建了油气开发领域安全风险分级防控体系推进模型,提出了逆向与正向危害因素识别方法,明确了风险评价关键隐性过程原则,构建了风险-后果-能资分级防控决断模型。选取典型试点单位进行实践,结果证明,油气开发领域安全风险分级防控体系推进模型是科学合理的,其他领域也可借鉴该模型开展安全风险分级防控工作。     

移动通信技术发展对安全生产影响研究*

为了深入揭示安全生产水平同移动通信技术发展的内在联系,提出安全生产信息技术能力的概念及其监控管理连接、救援响应监测、定位导航追踪3方面子能力的定义,进而通过构建3方面子能力同移动通信主要性能指标之间的关系模型（SPITCMC）,并对其进行深入分析和研究。研究结果表明:SPITCMC模型可以准确诠释过去移动通信技术发展对安全生产水平产生的影响,同时可用于预判未来移动通信技术发展对安全生产可能产生的影响程度,从而为后续相关工作的开展提供参考和借鉴。     

环境中的微塑料:赋存、检测及其危害

近年来,由个人护理品及废旧塑料直接或间接产生的微塑料不断地在各种环境介质中被检出,且微塑料会对生态系统产生各种危害,因此对微塑料的研究受到越来越广泛的关注。阐述了微塑料在水体、沉积物、沙滩和生物体中的赋存情况,介绍了微塑料的采集与分离方法,以及定性与定量分析方法。指出微塑料对环境及生物体产生的危害,提出现阶段研究存在的主要问题,并对今后的研究方向进行了展望。     

双重预防机制在家具制造业的应用与实践

为了减少安全事故的发生,进一步加强和规范企业生产现场的安全管理,探索双重预防机制在企业安全管理中的应用,结合家具制造企业安全生产现状,运用风险分级管控与隐患排查的相关理论,详细论述了企业构建双重预防体系的要点及方法,并提出了双重预防体系的监督与考核机制。实践结果证明,双重预防机制是一个统一的有机结合体,只有将风险分级管控体系和隐患排查治理体系有机结合,才能将导致事故发生的根源性因素进行有效识别和管控,双重预防机制建设也是一个动态管理的过程,需要及时进行监督、考核和调整。     

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.     

Inherent thermal runaway hazard evaluation method of chemical process based on fire and explosion index

Thermal runaway hazard assessment provides the basis for comparing the hazard levels of different chemical processes. To make an overall evaluation, hazard of materials and reactions should be considered. However, most existing methods didn't take the both into account simultaneously, which may lead the assessment to a deviation from the actual hazard. Therefore, an integrated approach called Inherent Thermal-runaway Hazard Index (ITHI) was developed in this paper. Similar to Dow Fire and Explosion Index(F&EI) function, thermal runaway hazard of chemical process in ITHI was the product of material factor (MF) and risk index (RI) of reaction. MF was an indicator of material thermal hazards, which can be determined by initial reaction temperature and maximum power density. RI, which was the product of probability and severity, indicated the risk of thermal runaway during the reaction stage. Time to maximum rate under adiabatic conditions and criticality classes of scenario were used to indicate the runaway probability of the chemical process. Adiabatic temperature rise and heat of the desired reaction and secondary reaction were used to determine the severity of runaway reaction. Finally, predefined hazard classification criteria was used to classify and interpret the results obtained by this method. Moreover, the method was validated by case studies.