长大区间隧道抽出式串联通风机排烟能力实验研究*

为实现有效通风以降低隧道火灾带来的损失和伤亡,依托青岛市地铁8号线大洋站至青岛北站区间隧道,建立线性比尺为1∶15的隧道通风排烟模型实验系统,针对通风机串联单抽,围绕3种通风机频率匹配组合,测定单机的变频频率值、电功消耗、排烟道与行车道的断面平均风速以及右侧行车道静压。研究结果表明:在相同功率消耗下,不同频率匹配的串联通风机排烟效果存在差异;针对此差异,利用气体挡烟墙性能及其计算欧拉数值比较发现,风井近端的通风机频率较大时,下游对污染气流的抵抗力更强,拥有更好的排烟效果。研究结果可为隧道火灾提供更有效率的防灾救灾数据支持,并从欧拉数方面为研究隧道临界风速提供新角度。     

基于缓冲区重采样的LSTM林火预测模型*

为提高林火风险预测精度,挖掘地图上隐含的空间信息、时间序列上隐含的长期趋势和循环波动,提出1种基于缓冲区重采样的长短期记忆（LSTM）林火预测模型,选取15个与林火相关的影响因素,以方差膨胀因子为评价指标对其进行多重共线性检验,方差膨胀因子大于10的因素具有共线性,并采用信息增益率验证筛选结果的合理性。考虑到火灾的空间聚集特性,采用缓冲区分析与过采样相结合方法减少样本不均衡现象的影响,最终得到176 732条样本。对12个影响因素和研究时间段的火点建立LSTM预测模型,对森林火灾发生风险进行预测。研究结果表明:基于缓冲区重采样的LSTM林火预测模型有效考虑时空上隐含的信息,预测模型准确率为87.06%,特异性为97.99%,敏感度为76.12%,阳性预测率为97.43%,阴性预测率为80.41%,ROC曲线与AUC值均优于随机森林（RF）和支持向量机（SVM）这2种基准算法。维尔克松秩和检验发现,本文提出的模型与基准算法结果具有显著性差异。研究结果可为提高林火风险预测精度提供参考。     

顶空毛细柱气相色谱法测定水中七种苯系物研究

选用Elite-FFAP色谱柱,利用顶空-毛细柱气相色谱技术对水中的苯、甲苯、乙苯、对二甲苯、间二甲苯、邻二甲苯、苯乙烯七种挥发性苯系物进行同时测定,并对样品的平衡温度、保温时间、程序升温的条件控制、水中含盐量等影响因素进行了探讨,优化了检测条件,使七种挥发性苯系物得到不错的分离。样品平衡温度控制在70℃,样品平衡时间19 min,进样口温度180℃,检测器温度230℃,10 mL水样中加入4 g NaCl的条件下,分离效果最佳。     

Mo-modified Pd/Al2O3 catalysts for benzene catalytic combustion

Mo-modified Pd/Al2O3catalysts were prepared by an impregnation method and tested for the catalytic combustion of benzene. The catalysts were characterized by N2 isothermal adsorption, X-ray diffraction（XRD）, X-ray photoelectron spectroscopy（XPS）, temperatureprogrammed desorption of NH3（NH3-TPD）, H2temperature-programmed reduction（H2-TPR）, and high-angle annular dark-field scanning transmission electron microscopy（HAADF-STEM）. The results showed that the addition of Mo effectively improved the activity and stability of the Pd/Al2O3catalyst by increasing the dispersion of Pd active components, changing the partial oxidation state of palladium and increasing the oxygen species concentration on the surface of catalyst. In the case of the Pd-Mo/Al2O3catalyst,benzene conversion of 90% was obtained at temperatures as low as 190°C, which was 45°C lower than that for similar performance with the Pd/Al2O3catalyst. Moreover, the 1.0% Pd-5% Mo/Al2O3catalyst was more active than the 2.0% Pd/Al2O3catalyst. It was concluded that Pd and Mo have a synergistic effect in benzene catalytic combustion.     

卫星遥感洞庭湖主汛期水体时空变化特征及影响因子分析

基于1989~2011年的长时间序列卫星遥感数据,利用综合水体信息提取方法提取了洞庭湖区6~9月主汛期的水体信息,通过较高分辨率卫星遥感数据验证,水体面积提取精度达到90%以上。洞庭湖年平均径流入湖量、NCEP再分析资料计算的湖体上空和流域累计月平均降水量分别与水体面积变化的关系进行分析,结果表明: 1989~2011年间洞庭湖水体面积最大值主要分布在7和8月,这两个月也是洞庭湖区域发生洪涝灾情的高风险期;洞庭湖水体面积与年平均径流入湖水量的相关系数为0.67(置信度为95%);2003年以前,洞庭湖主汛期间水体面积波动比较大,2003年三峡水库运行后,洞庭湖的面积波动有所减少;洞庭湖上空累计月平均降水量对于水体面积存在正相关性,相关系数为0.68(置信度为99%);2003年以前,洞庭湖流域累计月平均降水量和水体面积相关系数为0.50(置信度为90%),2003年三峡水库运行后,两者相关性有所减弱。     

基于神经网络分类器的城市污水处理厂水力冲击预警系统

提出了一套基于神经网络分类器的城市污水处理厂水力负荷冲击预警系统,以期对进水水量骤增现象进行提前1天的预报,使污水处理厂可根据预报结果提前采取水力冲击防护措施,从而保证各单元的平稳运行.根据进水水量的涨幅将某污水处理厂12年日进水水量监测数据分为"常规"和"冲击"两类,重点对"冲击"数据进行提前1天的预测,并采用冲击漏报率、冲击误报率和报准率对模型的预测精度进行评价;同时,基于同样的建模方法和不同的训练、验证样本建立了N(1)、N(2)和N(3)3个平行模型,以对模型的鲁棒性和建模方法的可重复性进行考察.结果显示,3个模型对2010年、2011年和2012年3年测试样本的预测效果良好,冲击漏报率和报准率两项指标数值均较为稳定,分别在0~0.167和0.981~0.995之间浮动,冲击误报率虽然在数值上的浮动较大,最低为0.143,最高为0.500,平均为0.310,但仍在工程上的可承受范围内.该结果表明,本研究基于神经网络分类器所建立的3个神经网络模型预测精度高、鲁棒性好,显示出良好的性能,有望为污水处理厂水力冲击防护工作提供有力参考.     

基于ARIMA的安全生产事故预测与实证研究

为了减少企业安全管理者在生产作业中由于不确定性导致错误决策所产生的风险,在企业历年安全生产事故数据基础上进行预测具有一定的现实意义。以某企业2008年至2011年的安全生产事故次数时序数据,采用EViews 5统计分析软件,基于ARIMA时间序列预测模型更加关注对事故发生是否平稳而相对于其他预测模型更关注于趋势研究的良好特点,建立安全生产事故ARIMA时序预测模型,并对2012年的安全生产事故发生次数进行预测,通过效果检验发现该模型预测结果基本上能够反映该企业安全生产事故发生的实际情况。通过ARIMA方法在某企业安全生产事故预测具体案例的实现,是对现有安全生产事故预测方法的补充和完善,可为企业安全管理和决策提供一定的指导。     

基于时序InSAR的覆砂石尾矿坝形变演化研究

为解决目前采用在尾矿坝坝体及滩面覆盖砂石进行防尘治理与闭库，但传统监测手段难以实现坝体整体监测的问题，采用时序InSAR技术对2014年10月至2018年7月的Sentinel-1A影像进行处理，提取了对应时间段内卡房尾矿坝的形变信息，并结合实地调查及尾矿坝建设资料，研究了卡房尾矿坝的时序形变演化规律。结果表明:SBAS InSAR监测到坝体出现第1次异常形变加速运动时间与坝体开始铺设砂石工程的施工时间节点完全吻合，体现SBAS InSAR技术在受人为工程影响的坝体形变监测方面具有极高的敏感性。坝体在施工结束后，坝体形变加剧趋势并未缓解，并且出现2次加速现象，分析认为是由于在坝体铺设约2 m厚的碎砂石极大地增加了坝体荷载，打破了坝体原有的应力平衡状态，且识别出雨季对坝体形变影响显著，表明铺设砂石会使得降雨在坝体中的停滞时间加长，进一步引发非雨季期间坝体形变加剧。研究结果不仅能还原坝体出现异常形变的时间与演化过程，而且还可以对引起异常形变的内在影响因素进行分析与论证，对指导尾矿坝灾害识别、分析与治理具有重要的指导意义。     

Tracking a half century of media reporting on gray wolves

Natural resource and wildlife managers must balance the disparate priorities of a diversity of stakeholders. To manage these priorities, a firm understanding of topics salient to the public is needed. The media often report on issues of importance to the public; therefore, these reports may be a useful measure of public interest. However, efficient methods for distinguishing diverse topics related to a wildlife management issue reported in the media and changes in the salience of those topics have been lacking. We used latent Dirichlet allocation, a Bayesian mixture model, to quantitatively assess the salience of topics surrounding the gray wolf (Canis lupus), which was reintroduced to Idaho (U.S.A.) in 1995. We analyzed articles published from 1960 to 2015 in an Idaho newspaper. We identified 6 distinct topics associated with gray wolves: policy, hunting, biological status, implementation of management, recovery, and human-wolf conflict. The salience of topics pre- and postreintroduction of wolves (1995) and pre- and postdelisting of wolves from the U.S. Endangered Species Act (2009) differed significantly, underscoring that these events were turning points in how issues were being publicly discussed and framed. Articles written by the local reporters were more likely to report on topics regarding conflict between humans and wolves, whereas articles sourced from a national outlet reported more on topics pertaining to wolf policy and biological status. In the context of managing a contentious, far-ranging, and long-lived wildlife species, our methods can help guide the location and timing of a suite of management strategies (e.g., media relation plans and stakeholder engagement) that promote human-wildlife coexistence across different landscapes.     

Optimal Reorganization of NASA Earth Science Data for Enhanced Accessibility and Usability for the Hydrology Community

A long‐standing “Digital Divide” in data representation exists between the preferred way of data access by the hydrology community and the common way of data archival by earth science data centers. Typically, in hydrology, earth surface features are expressed as discrete spatial objects (e.g., watersheds), and time‐varying data are contained in associated time series. Data in earth science archives, although stored as discrete values (of satellite swath pixels or geographical grids), represent continuous spatial fields, one file per time step. This Divide has been an obstacle, specifically, between the Consortium of Universities for the Advancement of Hydrologic Science, Inc. and NASA earth science data systems. In essence, the way data are archived is conceptually orthogonal to the desired method of access. Our recent work has shown an optimal method of bridging the Divide, by enabling operational access to long‐time series (e.g., 36 years of hourly data) of selected NASA datasets. These time series, which we have termed “data rods,” are pre‐generated or generated on‐the‐fly. This optimal solution was arrived at after extensive investigations of various approaches, including one based on “data curtains.” The on‐the‐fly generation of data rods uses “data cubes,” NASA Giovanni, and parallel processing. The optimal reorganization of NASA earth science data has significantly enhanced the access to and use of the data for the hydrology user community.