管制员人为差错影响因素及指标权重分析

根据SHELL模型,将影响管制员人为差错的因素从内部因素和外部因素进行分析,内部因素包括管制员生理因素、心理因素、管制员业务技能三个部分;外部因素包括管制员与管制员班组之间、管制员与管制设备之间、管制员与管制程序等软件之间。通过分析和专家咨询,建立了影响管制员人为差错的影响因素指标体系,在模糊层次分析法的基础之上引入0.1-0.9标度法的三角模糊数,通过对各影响因素进行对比分析,得出了影响管制员人为差错的三级指标的重要度排序,排在前八位的因素依次为酒精及药物影响、形势意识、班组人员性格搭配、班组人员能力搭配、疲劳、人机界面、外界压力、情绪状态。为管制员培训和管理层进行安全检查提供了基础理论依据。     

基于信息处理和事故链原理的结构化飞行员差错模型

为了对民航飞行员人为差错进行系统分析,研究民航业中常见人为差错的分析方法,指出其局限性。基于信息处理过程和事故链原理,从微观的认知过程和宏观的HFACS框架2个层面构建一种新的飞行员人为差错分析模型,并对模型中的情景分析、差错模式与分类、认知机理、差错恢复、差错成因、反馈机制和防御机制等几大核心模块进行阐述,重点介绍认知机理在差错形成中产生的关键影响因素,提出结构化差错分析方法的思路与步骤。该模型为民航飞行员人为差错的产生机理、差错分类和差错成因的分析提供一种新思路,但模型的进一步应用还有待于通过案例分析来验证。     

空管威胁、差错与意外状态的贝叶斯模型分析研究

为准确理解民航空中交通管理中各类人为差错数据的可靠性和相关性,为安全决策提供量化依据,对空管威胁、差错和意外状态数据进行贝叶斯模型分析。该方法在先验概率基础上,通过研究空中意外状态发生条件下威胁与差错各自发生的后验概率,获得上述3类安全信息的相关性大小排序。针对收集到的625起数据样本进行了研究,结果表明:与空中意外状态的发生相关性最大的3类差错依次为:管制员对机组的通讯差错、信息差错以及管制员对管制员的通讯差错;与空中意外状态的发生相关性最大的3类威胁依次为:程序威胁、相邻单位威胁和空中交通威胁。空管运行单位的安全管控应重点关注管制员/机组间的通讯差错,并针对各种可能出现的威胁预先制定应对程序。     

Unveiling the liaison between human capital,trade openness,and environmental sustainability for BRICS economies: Robust panel-data estimation

Global warming and greenhouse gas emissions pose severe threats to environmental sustainability. A sustainable environment is a prerequisite for long-term socioeconomic growth and human survival. Green technology is brought about by a country's economic and financial openness, and education provides knowledge to the public and labor, contributing to environmental sustainability. Thus, this research aims to unveil the liaison between human capital, trade openness, and environmental quality for Russia, Brazil, India, China, and South Africa (BRICS) countries from 1998 to 2018. Several econometric methods, including the Driscoll–Kraay standard errors and the Dumitrescu–Hurlin causality approaches, reveal long-run and causal relationships among the modelled indicators. The Driscoll–Kraay standard error results show that human capital is negatively related to carbon dioxide emissions (CO₂ emissions). Imposing high tariffs and excise duties, changing tax structures, discouraging the inflow of polluted commodities, and encouraging green trade can help BRICS combat high environmental pollution. The results show that a one-point increase in human capital in models 1 and 2 can reduce CO₂ emissions by 1.5279 and 0.1538 points, respectively. In contrast, a 1% growth in trade can lead to a rise in CO₂ emissions of 0.3731% and 0.2384%, respectively. Similarly, financial development and energy consumption result in high CO₂ emissions in the long run. Moreover, a feedback effect of the human capital index on CO₂ emissions is discovered. As a result of the findings, the government and responsible authorities should provide financial support and encourage investments in the region's energy-resourceful and sustainable green projects.     

ANP-Fuzzy方法在MPL学生威胁与差错管理能力评估中的应用

为考核CCAR141飞行学校多人制机组驾驶员执照(Multi-crew Pilot License,MPL)训练效果,对其核心单元——威胁与差错管理(Threat and Error Management,TEM)能力进行评估.在分析ANP原理和模糊综合评价方法的基础上,结合ICAO的PANS-TRG文件,建立了面向MPL培训的TEM能力评估指标体系和能够精确界定定性指标的Fuzzy多层次评价结构.采用ANP-Fuzzy方法对CCARI41飞行学校C的MPL学生TEM能力进行评估.结果表明,威胁管理比差错管理、非预期状态管理对MPL学生TEM能力的影响大,同时,该方法能够有效区分学生自身不同方面及不同学生间的管理能力差异.此外,借助Super Decisions软件也可用于其他训练单元的效果评估.     

基于CREAM和贝叶斯网络的航空维修人为差错概率预测

航空维修差错不仅严重威胁着飞行安全,同时也会增加航空公司的维修成本。针对航空维修人员发生差错成因的复杂性以及历史事故数据缺乏的情况下,将人因可靠性与失误分析方法（CREAM）和贝叶斯网络（BN）相结合,提出一种改进的维修差错分析模型。根据维修任务构建相应的贝叶斯网络模型,为各子节点设置条件概率表（CPT）;基于维修基地的实际维修环境,对行为形成因子（PSFs）进行评估,得到共同绩效条件（CPCs）的水平;利用各CPC因子下各个行为功能失效模式的权重因子,对各认知活动进行失效概率的修正;将修正概率作为贝叶斯网络根节点的输入,利用推理机制,得到差错发生概率。通过案例分析和计算,验证了所述方法的可行性和有效性。     

Application of CREAM human reliability model to cargo loading process of LPG tankers

The storage and handling processes of liquefied petroleum gas (LPG) constitutes a complex operational environment in the maritime mode of transportation. The LPG cargo is carried by specially designed ships called LPG tankers. The LPG cargo loading and discharging operations have always potential hazards. Thus, the crew on-board LPG tankers should be fully aware of operational risks during the cargo handling process, which includes various critical tasks such as drying, inerting, gassing-up, cooling, and reliquefaction. During these stages, human reliability (operation without failure) plays a crucial role in sustainable transportation of cargo. Human reliability analysis (HRA), related to various parameters such as the human factor, technology, and ergonomics, is always a critical consideration as regards maritime safety and environment. The main focus of the research is to systematically predict human error potentials for designated tasks and to determine the required safety control levels on-board LPG ships. The paper adopted CREAM (Cognitive reliability and error analysis method) basic and extended versions in order to assess human reliability along with the cargo loading process on-board LPG tanker ships. Specifically, the model is demonstrated with an operational case study. Consequently, the research provides should contribute to maritime safety at sea and prevention of human injury and loss of life on-board LPG ship.     

Accuracy assessment of a small-area method for estimating the spatial distribution of the degree of tree damage

Tree damage, gauged by the amount of defoliation, is one of the basic criteria used to determine treatments for protected and economic forests. Monitoring should include an assessment of the degree of tree damage in different spatial scales. Therefore, in addition to the commonly applied large-area methods, small-area methods should be used. The aim of the paper is to present the results of the accuracy assessment of a small-area method, proposed by Podlaski (2005) [Podlaski, R. (2005). Inventory of the degree of tree defoliation in small areas. Forest Ecology and Management, 215, 361–377], for monitoring the degree of tree damage. The degree of tree damage was shown in sub-blocks P₃ of the system of information on natural environment (SINUS). To estimate the spatial distribution of the degree of tree defoliation, survey sampling, based on simple random sampling with replacement (SRSWR), was used. The degree of damage to fir (Abies alba Mill.) and beech (Fagus sylvatica L.) was analysed in the Święty Krzyż forest section in the Świętokrzyski National Park. The maximum total estimation errors for the proportion of trees with a degree zero of damage, and with second and third degrees of damage together (for α = 0.05) were at most 30.8% for fir and 24.3% for beech trees. For standard, small-area evaluations, these are satisfactory values. In the Święty Krzyż forest section, the number of P₃ sub-blocks with 0.00–5.00% of undamaged trees and with 80.01–100.00% of moderately- or severely-damaged trees was significantly greater for fir than for beech. These results indicate that the fir population was unhealthier than the beech group in the study area. P₃ sub-blocks of the SINUS system, in which the proportion of the healthiest trees was highest, were situated at the forest margin, bordering on meadows and arable fields (in the case of fir) and forming dense patches consisting of several sub-blocks, or occurring singly in the whole study area (in the case of beech). The results show the significant differentiation of forest tree health in small areas.     

HpGe γ谱仪本底变化对环境样品放射性测量结果的影响

在环境样品测量过程中,本底涨落对天然核素测量结果的影响应根据其在谱仪中计数率的高低具体分析.用γ谱仪测量介质中天然放射性核素的活度浓度时,必然要进行本底谱的扣除,由此会带来一定的误差.对一台N型HpGe γ谱仪在8年间的23个本底谱进行了研究,并分析了本底涨落对测量结果的影响.研究发现,被测介质中天然放射性核素的活度浓度越低,本底涨落越大,由扣除本底引入的误差就越大.     

大气扩散模型计算结果析疑

扩散模型是大气污染物浓度预测最重要的工具。然而不同模型的预测结果差距很大,应该理性看待和应用其结果,本研究旨在通过实例说明这些问题。同时指出,同一类型的环评预测应该使用同一种模型,其结果才具有可比性。而最重要的还是要通过降低排放量来减少污染影响,不必过于计较模型观测结果。