事故致因理论综述

结合中国应急管理现状,揭示了目前企业应急管理中存在的问题,从理论指导研究的视角切入,主张以基础性理论为指导改变应急管理观念,改变应急管理现状。回顾了事故致因理论的历史演进历程,总结了该理论在国内理论研究的拓展,以及在生产领域应用的实际情况。     

道路交通环境中驾驶疲劳的生成模型研究

为预防由驾驶疲劳引起的交通事故,有必要研究在道路、交通和环境的综合影响下驾驶疲劳的生成机理。基于生理、心理学中的经典理论,借鉴国内外相关的研究成果,采用理论推理的方法对驾驶疲劳生成过程中驾驶员唤醒水平的变化规律及其影响因素进行分析。在此基础上建立了驾驶疲劳的生成模型,并将模型应用于工程实际。通过驾驶员唤醒水平的变化,指出驾驶疲劳的生成时刻,及其对驾驶时间的规定和道路、景观设计的影响。该模型以唤醒水平为核心,描述驾驶疲劳生成过程中驾驶员唤醒水平的变化规律,强调道路交通环境对驾驶员唤醒水平的影响。     

烟花爆竹烟火药剂危险性评价方法

为预防涉及烟花爆竹用烟火药剂的事故,应当在大规模制造、使用、储存之前,初步评估其危险性。在大量文献调研和专家建议基础上,选取机械感度(撞击和摩擦)和热感度作为烟火药安全性的最主要的指标。基于危险度的定义,用摩擦感度、撞击感度和热感度表征可能性,用最大放热量原则计算的放热量表征严重度,提出一种简便的,对烟花爆竹用烟火药剂的危险性进行评价的方法。运用此种方法得到的几种药剂的危险性等级比较符合实际情况。     

柔性时间约束突发事件交通疏散规划研究

柔性时间约束突发事件是对疏散时间强制程度较小的突发事件。为有效处理城市中这类突发事件下的人员疏散问题,在分析柔性时间约束突发事件特点的基础上,提出完整的突发事件交通疏散规划框架。根据我国现阶段国情,以总的疏散时间最少为决策目标,同时面向私人汽车和公共汽车2种方式,综合考虑成本费用、车辆保有量、道路容量等资源约束条件,建立求解突发事件交通疏散方案的整数线性规划(ILP)模型,并给出有效的求解算法。最后通过算例,演示应用模型及算法求解交通疏散规划方案的详细过程。结果表明,应用研究成果求解得到疏散交通工具选择及其路线安排方案,可以实现在一定资源约束下总的疏散时间最少。     

事故致因模型体系及建模一般方法与发展趋势

为完善事故致因建模的基础理论体系,从微观、中观与宏观3个层面归纳国内外现有的50余种事故致因模型,并以“点-线-面-体”为主线论述事故致因模型的立体网状结构体系。基于此,从方法学的视角论述事故致因建模的理论基础,并提炼相似比较法、概率统计法等5种一般建模方法。最后分析新形势下事故致因模型及其建模方法的发展趋势。研究结果系统的梳理与归纳了现有事故致因模型及其结构体系,完善了事故致因建模的方法论,可为事故致因建模的研究与实践提供基础理论指导。     

Supply chain and logistics competencies in humanitarian aid

The continuing incidence of disasters and their associated challenges has increased the demand for humanitarian logisticians. However, there is a dearth of research on their essential competencies. This paper proposes, therefore, a humanitarian logistics competency framework (HlCF) to assist with the professional development of humanitarian logisticians. In creating the HlCF, nine competency domains containing 29 specific competencies across four levels (entry to senior management) were identified. This study makes two key contributions to the literature: (i) it extends the discussion of competency frameworks in humanitarian logistics; and (ii) it presents a framework designed to support the human resource plans and practices of aid agencies. The HlCF allows not only individual humanitarian logisticians to develop the competencies necessary for career success, but also humanitarian organisations to map their own competency frameworks to a common standard. This will, in turn, facilitate workforce mobility and support the overall concept of a certified humanitarian logistics professional.     

A concise review of ecological risk assessment for urban ecosystem application associated with rapid urbanization processes

ABSTRACT

Urban ecological risk (UER) caused by rapid urbanization means potential threat to urban ecosystem structure, pattern and services. The scales of ecological risk assessment (ERA) have been expanded from individual organisms to watersheds and regions. The types of stressor range from chemical to physical, biological and natural events. However, the application of ERA in urban ecosystems is relatively new. Here, we summarize the progress of urban ERA and propose an explicit framework to illumine future ERA based on UER identification, analysis, characterization, modeling, projection and early warning and management. The summary includes six urban ERA-relevant methods: weight-of-evidence (WoE), procedure for ecological tiered assessment of risks (PETAR), relative risk model (RRM), multimedia, multi-pathway, multi-receptor risk assessment (3MRA), landscape analysis and ecological models. Furthermore, we review critical cases of urban ERA in landscape ecology, soil, air, water and solid waste. Based on the Internet of Things (IoT) and cloud computing, an urban ERA management platform integrates various urban ERA methodologies that can be developed to provide better implementation strategies of UER for urban ecosystem managers and stakeholders. We develop a conceptual model of urban ERA based on the urban characteristics in China. The future applications of urban ERA include uncertainty analysis using Monte Carlo techniques on the basis of geospatial techniques and comprehensive urban ERA using nonlinear models or process models.     

Scaling up of biomass simulation for Eucalyptus plantations based on landsenses ecology

ABSTRACT

Sustainable forest management on a regional scale requires accurate biomass estimation. At present, technologically comprehensive forecasting estimates are generated using process-based ecological models. However, isolation of the ecological factors that cause uncertainty in model behavior is difficult. To solve this problem, this study aimed to construct a meliorization model evaluation framework to explain uncertainty in model behavior with respect to both the mechanisms and algorithms involved in ecological forecasting based on the principle of landsenses ecology. We introduce a complicated ecological driving mechanism to the process-based ecological model using analytical software and algorithms. Subsequently, as a case study, we apply the meliorization model evaluation framework to detect Eucalyptus biomass forest patches at a regional scale (196,158 ha) using the 3PG2 (Physiological Principles in Predicting Growth) model. Our results show that this technique improves the accuracy of ecological simulation for ecological forecasting and prevents new uncertainties from being produced by adding a new driving mechanism to the original model structure. This result was supported by our Eucalyptus biomass simulation using the 3PG2 model, in which ecological factors caused 21.83% and 9.05% uncertainty in model behavior temporal and spatial forecasting, respectively. In conclusion, the systematic meliorization model evaluation framework reported here provides a new method that could be applied to research requiring comprehensive ecological forecasting. Sustainable forest management on regional scales contributes to accurate forest biomass simulation through the principle of landsenses ecology, in which mix-marching data and a meliorization model are combined.