Welch谱估计的随机误差与置信度

目的分析Welch谱估计的随机误差及置信度。方法首先导出Welch谱估计量随机误差的表达式,然后采用正态标准化处理方法,将Welch谱估计分量转化为χ2变量。结果获得了Welch谱估计的置信度分析方法。结论以128自由度的Welch谱估计结果的随机误差(12.5%)作为相对置信区间,则其置信概率为68.4%,若要达到95.5%以上置信概率,则Welch谱估计的自由度不能小于512,相应的随机误差为6.25%。     

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.     

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。     

NaI（Tl）多道谱仪测量固体样品时实验数据准确性分析

通过对同一样品中的放射性核素含量进行多次等精度测量,对结果的可靠性进行分析和出现离散的数据进行数据舍弃检验。在放射性测量过程中除考虑统计误差外,同时也应考虑仪器的、人为的及偶然因素导致的系统误差,从而提高测量精度。     

基于信息加工模型的管制员差错分类与分析

在Wickens的人类信息加工模型的基础上,加入注意功能、情景意识、内部和外部操作成形因素,建立了管制员信息处理模型。按照该模型,空中交通管制人为差错可按照认知领域分为感知与警觉性差错、短时记忆差错、长时记忆差错、判断与计划差错、响应选择差错和响应执行差错;影响管制员操作的情境条件可分为外部操作成形因素和内部操作成形因素。对以往空管人为差错的分析表明,在信息加工层面分类的人为差错更宜于确定差错的心理致因。基于该理论模型的差错分类系统可以改进人为差错分析的有效性和一致性,从而提高差错管理的有效性。     

库存弹药事故人误危险性分析与评估模型研究

针对库存弹药安全的特殊性,提出库存弹药事故人为失误的定义,并从个体角度分析人误事件发生的机理。根据人为失误的不同主体,从管理决策、组织和勤务处理、操作两个方面构建了29个人误危险性的评价指标及相应的评判标准;综合考虑生理、心理、知识与技能、设备、环境、监督与管理等6类危险性抵消因子对人误危险性的影响;进而建立了库存弹药事故人误危险性的理论评估模型。研究结果表明:人为失误属于弹药仓储安全管理中的一类特殊危险源,人误评估指标体系和评估模型的构建过程应充分考虑人自身条件以及内、外部环境等因素的综合影响;同时研讨了人为失误危险性分析和评估模型存在的问题,并从发展人误数据采集技术、完善人误事故报告制度以及建立人误数据库等方面,指出下一步的研究重点。     

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.     

Optimal power flow model incorporating wind,solar, and bundled solar-thermal power in the restructured Indian power system

A new optimal power flow model for wind, solar, and solar-thermal bundled power scheduling and dispatch is proposed, incorporating the deviation incentive/penalty charges for renewable energy introduced in India. The multiobjective function is solved using the flower pollination algorithm; the scheme is successfully tested on the IEEE 30-bus and Indian utility 30-bus systems. The forecasting error constraints introduced in renewable energy scheduling and dispatch are demonstrated to be beneficial in several aspects. Solar-thermal bundling is shown to create win-win situations for thermal and solar generators. The effectiveness of the flower pollination algorithm in solving optimal power flow models is proved.     

Relationship between (210)Pb(ex) activity and sedimentary organic carbon in sediments of 3 Chinese lakes

This report demonstrates that organic matter was an important factor in lake sediment ²¹⁰Pb_ex dating. Sediment cores from lakes in central and western China with different-trophic levels were collected, and the ²¹⁰Pb_ex activity and total organic carbon (TOC) were measured. The Rock-Eval pyrolysis technique was used to deconvolute TOC into free hydrocarbons (S1), thermally less-stable macromolecular organic matter (S2a), kerogen (S2b), and residual carbon (RC). The results show significant correlations between TOC and ²¹⁰Pb_ex, particularly between S2a and ²¹⁰Pb_ex, in all the sediment cores. This indicated that the algal-derived organic component S2a may play the most important role in controlling the distribution of ²¹⁰Pb_ex. Scavenging by algal-derived organic matter may be the main mechanism. As chronology is the key to the understanding of pollution reconstruction and early diagenesis in sediments, more attention should be paid to the influence of organic matter on ²¹⁰Pb_ex.     

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.