基于尾涡强度的无人机与民机纵向安全间隔评估研究

为了解决无人机频频入侵机场净空,与民航客机发生危险接近的问题,以碰撞风险为量化指标,对无人机与民机需要保持的纵向安全间隔进行评估研究。分析民机尾涡流场对无人机运行的影响,利用Crow近场涡强度消散理论,得到实际尾迹影响区改进Reich碰撞模板,据此建立CNS/GPS性能环境下的纵向间隔评估模型,通过Matlab进行间隔值求解。研究结果表明:模型可以较为准确地反映民机起飞初始爬升阶段无人机尾随运行时导航性能和尾涡迹对所需最小间隔值的影响,并得到给定安全目标水平的计算结果。     

人误因素树构建技术研究

运用人误因素辨识多视图法进行因素辨识,建立了详细的因素辨识表;把人的行为分为5个阶段,即系统状态监测阶段,目标分析阶段,方案确定阶段和行为执行阶段.分别分析各个阶段可能的人误原因及模式;以组织视图为例,根据因素辨识和人误原因及模式分析结果,阐述人误因素树的构建过程,最终得到了1个完整的人误因素树.     

上海市能耗与GDP大气污染的协整关系研究

采用计量经济学中的协整理论考察上海市能源消费量与经济增长、废气排放量、二氧化硫排放量之间的关系。结果显示,上海市能源消费只与经济增长、废气排放量之间存在长期协整关系,并建立了相应的长期均衡方程及误差修正模型。另外,对1978～2003年的能源消费与经济增长之间进行Granger因果关系检验,提出实现上海市经济-能源-环境和谐发展的措施。     

基于CREAM和贝叶斯网络的空管人误概率预测方法

针对研究管制人因可靠性时存在的模糊性和片面性问题,采用认知可靠性与失误分析方法（CREAM）中的扩展预测法,计算10项管制通用任务的人误概率;在此基础上,以管制行为形成因子作为根节点构建贝叶斯网络,建立其与情景控制模式的不确定关系模型,对管制员在多任务中的人误概率进行预测。研究结果表明:在由相同评判者给出行为形成因子影响效应的前提下,由CREAM扩展预测法和构建贝叶斯网络的方法预测得到的多数任务的人误概率差异较大,从方法的客观性、合理性和适用性角度分析,贝叶斯网络在研究该问题时更具优势。     

基于改进的SPAR-H化工实验室人因可靠性分析

近年来化工实验室事故屡禁不止,其中人的不安全行为是导致事故发生的主要原因.为评估实验人员可靠性,进一步管控化工实验室人的不安全行为,基于标准化工厂人因可靠性分析(SPAR-H)方法,结合化工实验室人因失误的特点,确定了更加适用于化工实验室的人因可靠性分析方法.首先依据"S-O-P"认知模型对人因失误类型进行划分;然后基...     

Critical Steps for Continuing Advancement of Satellite Rainfall Applications for Surface Hydrology in the Nile River Basin1

Gebremichael, Mekonnen, Emmanouil N. Anagnostou, and Menberu M. Bitew, 2010. Critical Steps for Continuing Advancement of Satellite Rainfall Applications for Surface Hydrology in the Nile River Basin. Journal of the American Water Resources Association (JAWRA) 46(2):361-366. DOI: 10.1111/j.1752-1688.2010.00428.x. Abstract: Given the increasingly higher resolution and data accessibility, satellite precipitation products could be useful for hydrological application in the Nile River Basin, which is characterized by lack of reasonably dense hydrological in situ sensors and lack of access to the existing dataset. However, in the absence of both extreme caution and research results for the Nile basin, the satellite rainfall (SR) products may not be used, or may even be used erroneously. We identify two steps that are critical to enhance the value of SR products for hydrological applications in the Nile basin. The first step is to establish representative validation sites in the Nile basin. The validation site will help to quantify the errors in the different kinds of SR products, which will be used to select the best products for the Nile basin, include the errors in decision making, and design strategies to minimize the errors. Using rainfall measurements collected from the unprecedented high-density rain gauge network over a small region within the Nile basin, we indicate that SR estimates could be subject to significant errors, and quantification of estimation errors by way of establishing validation sites is critically important in order to use the SR products. The second step is to identify the degree of hydrologic model complexity required to obtain more accurate hydrologic simulation results for the Nile basin when using SR products as input. The level of model complexity may depend on basin size and SR algorithm, and further research is needed to spell out this dependence for the Nile basin.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

Risk assessment tools incorporating human error probabilities in the Japanese small-sized establishment

Although it has been estimated that as many as 80% of all occupational accidents have human errors as a cause, no risk assessment tools incorporating human-related elements have been developed for small companies. Human error probability (HEP) and human error analysis (HEA) have been used for large-scale, safety-critical industries for last three decades, but these tools are not suitable for smaller, more general industries that comprise the majority of accident settings.Here, we describe and verify a risk assessment tool that includes human-related elements for small companies. The tool expands on traditional risk assessment methods, such as matrix, risk graph and numerical scoring method, by adding human-related elements. The tool is easy-to-use in occupational environments, and includes assessments of human behavior and potentially outdated machinery at work place.     

Impact of training programs on decision-making and situation awareness of trainee watch officers

This paper examines the impact of training programs on the ability of trainee watch officers to make decisions in collision avoidance situations.It draws on previous studies which have shown that experts are able to manage complex situations in an acceptable way. However, observations of students on simulators have revealed that many of them are unable to manage such situations or even to recall their main features. It is therefore necessary to identify new training tools that will give trainees the capacity to assess a situation quickly and accurately, and to perform satisfactory actions. These would be in addition to formal regulations.Exercises were designed to evaluate the impact of such tools on the decision-making process of trainees. The impact of the type of navigation experienced by trainees during their on-the-job training was also evaluated.Results showed that decision-making exercises did tend to improve the trainees’ capacity to analyse a complex situation; however, they did not have a clear impact on the manoeuvre performed. On the contrary, there was an obvious difference between the trainees who experienced complex avoidance situations during their on-the-job training period and those who did not.At a time where ship-owners are looking to reduce the length of the “on-the-job” training period, these results point to its vital importance.     

人-机系统事故预防理论研究

分析人-机系统事故发生原因,剖析经典以人失误为主因的事故致因模型存在的不足,在该模型基础上增加"刺激"形成的原因,构建了改进事故致因模型。对两模型进行比较研究,指出人机工程学与防止事故的关系,提出了人机工程学防止事故的方法,并给出人机界面合理性主观评价检查表。研究及论证表明:预防人-机系统事故的本质在于有效防止人失误的发生,除安全管理措施以外,最重要的是人机工程学问题,笔者提出的基于人机工程学的人-机系统事故预防理论,对人-机系统事故的预防起到积极的指导作用。