开展新的安全监察模式探讨

安全稽查的运作突破常规的安全检查方式,本文介绍开展安全稽查工作的运做情况,通过安全稽查实时反映出施工的具体实际情况,取得了直接的、第一手资料,纠正施工人员侥幸心理,有效控制习惯性违章的行为,促使其落实好各项安全措施,减少事故隐患,杜绝事故发生.     

AN EVALUATION OF PHYSICAL STREAM HABITAT ATTRIBUTES USED TO MONITOR STREAMS1

ABSTRACT: The last few decades have seen an increased reliance on the use of stream attributes to monitor stream conditions. The use of stream attributes has been criticized because of variation in how observers evaluate them, inconsistent protocol application, lack of consistent training, and the difficulty in using them to detect change caused by management activity. In this paper, we evaluate the effect of environmental heterogeneity and observer variation on the use of physical stream attributes as monitoring tools. For most stream habitat attributes evaluated, difference among streams accounted for greater than 80 percent of the total survey variation. To minimize the effect that variation among streams has on evaluating stream conditions, it may be necessary to design survey protocols and analysis that include stratification, permanent sites, and/or analysis of covariance. Although total variation was primarily due to differences among streams, observers also differed in their evaluation of stream attributes. This study suggests that if trained observers conducting a study that is designed to account for environmental heterogeneity can objectively evaluate defined stream attributes, results should prove valuable in monitoring differences in reach scale stream conditions. The failure to address any of these factors will likely lead to the failure of stream attributes as effective monitoring tools.     

隧道渗涌水量的随机模型预测

渗涌水问题是常见的隧道病害 ,是影响隧道正常使用 ,危及行车安全的重要因素。因此 ,科学地预测隧道涌水量大小 ,是制定最优防治水方案 ,确保安全通车的关键。笔者以大瑶山隧道渗涌水量的实测数据为基础 ,应用随机过程的理论和方法 ,建立了隧道渗涌水量的平稳序列预测模型 ,并将预测值与实测结果进行了对比 ,比较吻合。     

城镇燃气爆炸极限影响因素与计算误差的分析

可燃气体的爆炸极限是消防报警和安全使用燃气的重要参数之一 ,笔者对影响城市燃气爆炸极限的因素进行了讨论 ;同时指出有关文献上公布的燃气爆炸极限是一定条件下测定的 ,当空气中含有略低于文献公布爆炸下限或略高于文献公布爆炸上限的可燃气体 ,在一定的条件下也可能产生爆炸。对燃气爆炸极限的计算方法及其计算误差进行了分析 ,指出在使用测试或计算爆炸极限时应考虑安全系数     

预防事故的重要途径——人为失误控制

从伤亡事故致因理论和我国大多数企业的安全管理现状出发，分析说明人为失误控制是预防事故的重要途径，并具体介绍了人为失误控制的两种主要技术方法。     

现代化工业企业人因失误分析与事故预防

现代化工业企业中人因失误已成为影响系统安全与可靠性的最主要因素，通过分析现代化企业的基本特征，探讨了系统监控人员行为模型、人因失误分类及原因，并提出了人因事件的预防策略。     

1990~2020年阿克苏河流域土地利用碳排放时空轨迹与影响因素

土地利用变化会导致不同类型碳源和碳汇功能变化,是碳排放的关键来源.从土地利用变化的角度开展阿克苏河流域碳排放及其影响因素研究,对于促进流域山水林田湖草沙冰一体化保护修复、助力碳达峰与碳中和目标实现具有重要意义.基于1990~2020年的4期土地利用数据与同期社会经济数据,测算土地利用碳排放总量,探究土地利用碳排放时空轨迹及其影响因素.结果表明:①1990~2020年,耕地、林地、建设用地和未利用地整体呈增加趋势,草地和水域呈减少态势.土地利用类型空间变化特征主要表现为草地、未利用地转换为耕地;②1990~2020年流域净碳总排放量呈现持续上升趋势,累计增加了14.78×10⁴ t,耕地面积增加是引起流域净碳排放量增长的关键因素;③流域土地利用碳排放量空间上呈中间高四周低的分布格局,净碳排放量显著变化区域主要分布在温宿县南部、阿克苏市、阿瓦提县及阿拉尔市;④人类活动对土地利用碳排放驱动作用最强且其影响由东部向西部逐渐增大,年均气温对土地利用碳排放影响贡献主要集中在阿克苏市东部和阿瓦提县北部,年均降雨量对温宿县北部和阿合奇县西部的抑制作用较强.     

基于机器学习算法的精细化流场模拟研究

基于决策树和随机森林两种机器学习算法,以长沙市国控站气象观测数据和WRF模式模拟得到的风场数据构建数据集,对WRF预报长沙市城区风场数据进行优化.同时,利用树模型特征选择法,筛选对近地面风场数据有重要影响的气象要素,将其作为两种机器学习算法的输入,并利用网格搜索法进行调参建模.最后,将训练结果与地面观测数据进行对比评估...     

Drivers of future streamflow changes in watersheds across the Northeastern United States

Accurate projections of streamflow, which have implications for flooding, water resources, hydropower, and ecosystems, are critical to climate change adaptation and require an understanding of streamflow sensitivity to climate drivers. The northeastern United States has experienced a dramatic increase in extreme precipitation over the past 25 years; however, the effects of these changes, as well as changes in other drivers of streamflow, remain unclear. Here, we use a random forest model forced with a regional climate model to examine historical and future streamflow dynamics of four watersheds across the Northeast. We find that streamflow in the cold season (November–May) is primarily driven by 3-day rainfall and antecedent wetness (Antecedent Precipitation Index) in three rainfall-dominant watersheds, and 30-day rainfall, antecedent wetness, and 30-day snowmelt in the fourth, more snowmelt-dominated watershed. In the warm season (June–October), streamflow is driven by antecedent wetness and rainfall in all watersheds. By the end of the century (2070–2099), cold season streamflow depends on the importance placed on snow in the machine learning model, with changes ranging from −7% (with snow) to +40% (without snow) in a single watershed. Simulated future warm season streamflow increases in two watersheds (56% and 193%) due to increased precipitation and antecedent soil wetness, but decreases in the other two watersheds (−6% and −27%) due to reduced precipitation.     

移动通信基站产品的随机振动试验分析

本文首先对随机振动试验和电动式振动台的原理进行简要分析,然后结合这些分析,对移动通信基站产品的随机振动试验的级别分类,设备选择,问题解决等进行探讨。