复杂工业系统中班组人因失误分析

在复杂工业系统中 ,人因可靠性分析 (HRA)是预防和减少人因失误的有效方法。人在复杂工业系统中的生产活动 ,往往是由组织中班组成员集体完成的 ,完整的HRA必须充分考虑班组人误的产生。班组人误的产生有其自身的规律 ,如何合理地定义人员行为形成因子 (PSFs)是班组人因失误分析的难点 ,也是班组人因失误分析的重要手段 ,被广泛应用在核电厂 ,航空和造船工业领域的事故分析中。笔者详细分析和探讨了班组人因失误的定义、产生过程及相关的人的行为形成因子 ,以期能使大规模工业系统中的人因失误分析更加合理和完善。     

航空维修差错分析及其管理

航空维修差错是诱发或直接导致飞行事故最重要的原因之一 ,对维修差错进行分类和分析有助于航空安全。笔者在分析航空维修环境变化的基础上 ,基于Reason模型构建了维修差错分类与诱因分析的框架 ,并结合机务维修的实际情况 ,对框架所包括的不安全行为、不安全行为的先兆、不安全的管理及组织因素进行了初步编码。文章还简要论述了维修差错的管理技术 ,指出借助框架编制详细的差错分类与分析编码系统是发展的方向。     

TraK装置测定废水中的BOD_5

在对废水中的BOD5进行常规分析时,采用化学稀释法操作繁琐,对稀释倍数估计易发生错误。而利用TraK装置测试样品时,无须进行稀释和化学分析。用该装置对标准样品BOD5的测定结果表明:准确度相对误差为-3.3%～4.3%,精密度的相对误差为-3.5%～5.6%。该仪器测试性能可靠,数据准确度、精密度合格。与化学法对照分析表明,相对误差都在容许范围内,即在可接受范围内。     

江苏省空气质量预报准确度及改进方法分析

介绍了江苏省重污染天气监测预报预警系统以及大气重污染预警会商流程,将2015年13个地级市的模式预报、人工预报结果分别与实际观测值进行比较。结果表明:人工预报更准确,PM_(2.5)日均值、臭氧日最大8 h平均值、AQI 3个指标人工预报和实况的相关性分别比模式预报高出12.8%、0.3%、11.4%,平均标准误差(MNE)分别低20.7%、3.1%、23.1%。依据国家空气质量预报技术指南评分办法,对各市2015年全年空气质量级别为"良"时进行评分。通过开展07∶00预报更新,使2015年上半年空气质量预报级别得分平均提高了0.9分,全年级别得分平均提高了2.6分;通过改进模式预报参数,使PM_(2.5)日均预报值、臭氧日最大8 h平均预报值、AQI预报值和实际观测值的相关性比上年同期分别提高26.0%、5.0%、33.9%,MNE分别降低3.6%、31.3%、7.6%。     

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.     

The difficulties of systematic reviews

The need for robust evidence to support conservation actions has driven the adoption of systematic approaches to research synthesis in ecology. However, applying systematic review to complex or open questions remains challenging, and this task is becoming more difficult as the quantity of scientific literature increases. We drew on the science of linguistics for guidance as to why the process of identifying and sorting information during systematic review remains so labor intensive, and to provide potential solutions. Several linguistic properties of peer‐reviewed corpora—including nonrandom selection of review topics, small‐world properties of semantic networks, and spatiotemporal variation in word meaning—greatly increase the effort needed to complete the systematic review process. Conversely, the resolution of these semantic complexities is a common motivation for narrative reviews, but this process is rarely enacted with the rigor applied during linguistic analysis. Therefore, linguistics provides a unifying framework for understanding some key challenges of systematic review and highlights 2 useful directions for future research. First, in cases where semantic complexity generates barriers to synthesis, ecologists should consider drawing on existing methods—such as natural language processing or the construction of research thesauri and ontologies—that provide tools for mapping and resolving that complexity. These tools could help individual researchers classify research material in a more robust manner and provide valuable guidance for future researchers on that topic. Second, a linguistic perspective highlights that scientific writing is a rich resource worthy of detailed study, an observation that can sometimes be lost during the search for data during systematic review or meta‐analysis. For example, mapping semantic networks can reveal redundancy and complementarity among scientific concepts, leading to new insights and research questions. Consequently, wider adoption of linguistic approaches may facilitate improved rigor and richness in research synthesis.     

基于随机森林的突发事件分级模型研究

突发事件的分级是快速响应和有效应对的基础，为了解决目前突发事件分级宽泛、主观性强和动态适应性弱等问题，将多分类器集成引入突发事件的分级过程中，借助随机森林组合分类器，针对突发事件特征，构建突发事件分级的随机森林模型，形成突发事件分级过程，进而对事前的应急预案制定、事中的应急资源配置和应急决策提供有力支撑；最后，以2014-2016年洪涝灾害突发事件为例检验构建的模型和过程。研究结果表明:与支持向量机方法相比，通过检验随机森林组合分类器分类结果准确率达到97.56%，在突发事件分级的应用上是可行的，进而可为突发事件的快速响应和应急决策提供信息支撑和参考依据。     

我国城镇化进程中碳排放影响因素的实证研究

利用1980—2013年间的城镇人口与碳排放数据,选取城镇化进程中影响碳排放的城镇化水平、城镇建设用地面积、第三产业增加值、人均可支配收入、城镇人均绿化面积等因素,实证分析了城镇化对我国碳排放的影响程度,并利用格兰杰夫因果关系与误差修正模型分析了二者的因果关系与时间效应。最后,从降低工业碳排放、加快低碳城镇化试点建设、推进低碳社区发展,促进新能源发展等方面提出了相关建议。     

多层阻尼复合板常温贮存5年性能研究

目的分析多层阻尼复合板常温贮存5年的性能变化。方法对多层阻尼复合板进行常温下贮存5年的减振性能研究,通过贮存前后的正弦扫描试验和随机振动试验,获得贮存前后多层阻尼复合板的减振性能和模态变化,进行对比分析。结果阻尼复合板常温贮存5年后,径向模态有较大的下降,法向模态变化较少,组件上的加速度响应基本无变化。结论该多层阻尼复合板常温贮存5年后仍然满足要求。     

Phenomenological compensation of thermally caused position and orientation errors of rotary axes

Thermal errors of machine tools are one of the major sources of inaccuracy. Therefore, the reduction of temperature induced deviations or the compensation of the resulting tool center point (TCP) errors have been of strong interest to the manufacturing industry for a couple of years. Up to now, the observation of the environment, the main spindle, the linear axes and the machine bed were in the focus of research, but with the rising demand for 5-axis machine tools and the increasing requirements regarding their accuracy, the analysis of the thermal behavior of rotary axes becomes more and more important. This paper gives an overview of corresponding thermal measurements of machine tools. The thermal behavior of rotary and swiveling axes is analyzed in detail. A simulation model and an approach for a phenomenological compensation of the TCP error are introduced and verified by measurements.