压力型锚杆支护边坡的动力响应与数值分析

采用振动台模型试验,输入汶川波、EL-Centro波和正弦波三种地震波,监测边坡加速度和锚杆应变,探讨地震作用下加固边坡的动力响应特征及锚杆应变的响应规律。得出:加固边坡土体对输入的地震波有垂直放大作用,水平方向放大作用不明显;在地震频率和幅值共同影响下,边坡加速度响应具有明显的差异。同一锚杆沿长度方向应变分布呈"前小后大"的模式;同列不同层锚杆在垂直方向应变响应差别较大,顶层、底层锚杆应变较边坡中部的锚杆应变响应明显。利用ABAQUS数值软件模拟振动台试验过程,得出锚固边坡动力响应特征与振动台试验结果一致。     

单因子指数法在水质评价中的应用研究

水质评价是工程设计水资源评价中非常重要的内容,现阶段我国水质评价工作主要依据《地表水环境质量标准》和《地下水质量标准》进行单因子评价,单因子评价法中,能判断水质类别,但不能反映与限值差距,同一水质类别时反映不出洁净程度。本文中引入单因子指数法,计算综合污染指数,对同水质类别进行洁净程度判别。     

A CRPS-Based Spatial Technique for the Verification of Ensemble Precipitation Forecasts

Traditional precipitation skill scores are affected by the well-known“double penalty”problem caused by the slight spatial or temporal mismatches between forecasts and observations. The fuzzy (neighborhood) method has been proposed for deterministic simulations and shown some ability to solve this problem. The increasing resolution of ensemble forecasts of precipitation means that they now have similar problems as deterministic forecasts. We developed an ensemble precipitation verification skill score, i.e., the Spatial Continuous Ranked Probability Score (SCRPS), and used it to extend spatial verification from deterministic into ensemble forecasts. The SCRPS is a spatial technique based on the Continuous Ranked Probability Score (CRPS) and the fuzzy method. A fast binomial random variation generator was used to obtain random indexes based on the climatological mean observed frequency, which were then used in the reference score to calculate the skill score of the SCRPS. The verification results obtained using daily forecast products from the ECMWF ensemble forecasts and quantitative precipitation estimation products from the OPERA datasets during June-August 2018 shows that the spatial score is not affected by the number of ensemble forecast members and that a consistent assessment can be obtained. The score can reflect the performance of ensemble forecasts in modeling precipitation and thus can be widely used.     

The Asian Subtropical Westerly Jet Stream in CRA-40, ERA5, and CFSR Reanalysis Data:Comparative Assessment

The Asian subtropical westerly jet(AWJ) exerts crucial influences on Eurasian continent weather and climate. This paper analyzes the advantages and limitations of CRA-40, which is China's first generation 40-yr(1979–2018) global atmosphere and land reanalysis product, in describing the characteristics of AWJ, compared with the ECMWF Reanalysis version 5(ERA5) and NCEP Climate Forecast System Reanalysis(CFSR). The results show a close agreement across the three reanalyses on the whole.(1) In terms of climatology, overall differences of 200-h Pa zonal wind across the three reanalyses are within ± 0.5 m s^-1(i.e., ± 2%). Large differences with maxima of ± 2 m s^-1(±5%) appear over the Iranian Plateau and south of the Tibetan Plateau in the mid–upper troposphere in winter.(2) For seasonal cycle, the position and intensity of the AWJ centers in the three reanalyses are highly consistent, with correlation coefficient over 0.98. But there are some discrepancies in the zonal shift of the western AWJ center during the transition season.(3) On the interannual timescale, intensity of all AWJ centers varies consistently among the three reanalyses, while larger differences appear in their meridional displacement, especially in the eastern AWJ center.(4)For long-term variations, the three reanalyses all present a significant northward movement of the westerly jet axis in winter, and a southward displacement over central Asia(40°–80°E) and a northward migration over East Asia(80°–110°E) in summer. Thus, this study has provided confidence that CRA-40 has comparable performance with ERA5 and CFSR in depicting the characteristics of AWJ.     

基于差分筛选的YOLOv2监控视频目标检测方法

监控视频的多目标跟踪是视频智能分析的热点研究内容,其中目标的检测是目标跟踪的基础,精度高、速度快的目标检测器对于后续的实时分析任务尤为重要。提出一种针对监控视频的基于差分筛选的YOLOv2目标检测算法,采用差分算法筛选无前景目标帧及设置重叠度量阈值进行跨帧检测,改善了YOLOv2作为检测方法用于监控视频多目标跟踪任务时速度过慢的不足,同时高精度的检测结果有利于下一步多目标跟踪任务的顺利完成。利用NPLR监控视频数据集对YOLOv2目标检测算法进行了测试,并将该方法与可变型部件模型DPM进行了比较。结果表明,差分YOLOv2方法在精度上高出DPM方法0.304 6,检测时间快了26倍左右,验证了该算法的有效性。     

利用主动深度学习提取极化SAR影像建筑区

针对利用传统监督分类方法从极化SAR影像中提取建筑区存在标记样本数量不足、难以挖掘有效特征等问题,提出一种主动学习与深度学习相结合的极化SAR影像建筑区提取方法。首先通过自动编码器对训练样本训练得到初始分类器;接着利用主动学习得到未标记样本中最富有信息量的样本进行人工标记;并将标记好的样本加入到训练样本中重新训练分类器。分别采用RADARSAT-2和ALOS-2极化SAR影像进行实验。结果表明传统的SVM方法和深度学习的方法加入主动学习后建筑区的提取精度都有所提高,而主动深度学习方法的提取效果优于主动SVM方法。     

GPS RTK在异形建筑物放样中的应用

针对异形建筑物传统施工放样过程操作复杂、效率低下的问题,该文提出了采用GPS RTK进行异性建筑物施工中的放样工作。以天津市文化中心商业项目为例,利用GPS RTK技术分别对建筑物的主轴线和异形次轴线进行了放样工作,并与全站仪在放样过程和数据精度两个方面进行了对比分析,实现了异型建筑物快速、高效的施工放样。实验结果表明,GPS RTK技术不仅在放样过程中操作简单,节约资金,而且放样精度满足工程要求,相对全站仪来说具有很大优势,有助于提高复杂异形建筑物的施工放样效率。     

GF-1垂直干旱指数的土壤湿度空间格局分析——以秭归县为例

针对中低分辨率的遥感图像在表征空间异质性较大地区的土壤湿度空间格局存在较大误差问题,该文探讨了基于高分辨率影像在小尺度上分析土壤湿度空间分布及变异规律的可行性。首先利用高分一号WFV数据构建垂直干旱指数来反映秭归县土壤湿度干湿状况,然后进一步分析了该县土壤湿度在水平及垂直方向上的空间格局和分异规律。实验结果表明,野外同步土壤表层水含量测试数据同垂直干旱指数两者表现出较好的相关程度。     

基于有效区域约束的GPU-CPU协同影像快拼方法

提出了一种以有效区域约束的Voronoi图为拼接线网络,利用GPU-CPU协同处理航空影像快速拼接方法。首先,基于成像有效区域生成有效区域约束的Voronoi图拼接线网络,解决了传统Voronoi图拼接线网络在低重叠度条件下拼接后影像局部区域不被覆盖的问题,然后利用GPU-CPU协同处理将正射纠正嵌入到影像拼接的过程中,并且只对每张影像的有效区域进行纠正,再通过选择配置优化和存储层次性优化进一步提高拼接效率。实验表明,对237张高分辨率航空影像进行快速正射纠正和拼接,本文算法较传统先纠正再拼接的方法效率提高近20倍,同时保证很高的拼接精度,可以满足应急测绘要求。