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141.
为了准确确定岩体力学参数,通过综合分析多种地质强度指标(GSI)量化方法,提出了一种改进的GSI值量化和修正方法。首先,利用测线法估算结构面平均间距(d)和岩体块度指数(RBI)的改进型岩体块度率(RBR),根据岩体三维结构面网络,获得岩体体积节理数(Jv)和岩体结构等级(SR),然后采用上述参数和结构表面条件(SCR)及结构表面特性参数(Jc)进行了GSI值的定量化处理。为了克服GSI体系的缺点,考虑结构面产状和地下水对岩体力学性质的影响,提出了GSI值的修正方法和公式。以某铅锌矿体的矿岩体为例,根据改进的GSI值量化和修正方法及Hoek-Brown强度准则来确定矿岩体力学参数,通过与原位变形试验的对比分析,验证了该方法的精确性和可行性。该方法为从室内岩石力学试验合理地获取节理岩体力学参数提供了理论及实现的依据。 相似文献
142.
在全球气候持续变暖背景下,北极地区冻土退化、冰川退缩、海冰减少等导致了一系列的生态环境问题,同时也使得资源勘探开发与国际新航道开通成为可能,北极地区的重要性日益凸显.依据2009—2019年6月期间有关北极研究的408篇ESI高影响论文,对发文量、主要作者、研究机构、国家、研究方向等字段进行分析,从自然科学角度,宏观而... 相似文献
143.
矢量数据在多尺度栅格化中的精度损失模型探讨 总被引:14,自引:2,他引:14
在进行空间分析时,由于栅格数据便于空间分析,因而通常将矢量数据转化成栅格数据进行空间分析。在转化过程中,采用不同尺度的栅格大小会造成怎样的精度损失?精度损失、栅格大小和平均斑块大小之间的关系是否可以用模型来表达?本文正是针对这样的问题,以重庆市1∶10万的土地利用矢量数据为例,探讨了在不同尺度栅格大小(从30m×30m到1000m×1000m)的情况下,各种土地利用类型在转化过程中的精度损失情况,对精度损失与栅格大小和平均斑块大小之间的关系进行了定量分析。研究表明,精度损失与地类的平均斑块大小和栅格尺度之间的关系可以用模型来表达。该模型为:Y=5.366-0.179X-0.978ln(S)+0.0348Xln(S)。模型中Y为精度损失,S为地类的平均斑块大小,X表示栅格的大小。该模型的复相关系数为0.93。 相似文献
144.
岩体结构统计均质区的划分 总被引:8,自引:0,他引:8
本文介绍由Miller提出的基本概率统计理论的关联表分析,结合施密特投影图研究岩体统计均质区的划分方法。对该法进行了适当的修改,编写了相应的计算机程序。并对三峡永久船闸地区的岩体结构,进行了岩体结构统计均质区的划分,获得了良好的效果。 相似文献
145.
长沙、株洲、湘潭三市土壤中重金属元素的来源 总被引:13,自引:0,他引:13
为追踪长沙、株洲、湘潭3个城市表层土壤中Cd、As、Pb等重金属元素的来源,分析了土壤、基岩、大气干湿沉降、水、悬浮物等介质之间重金属元素的质量平衡和土壤自身重金属元素含量随时间变化的特点。结果显示,除As外,区内基岩中的重金属元素含量低于克拉克值;残积物中Cd相对基岩贫化,As、Pb、Cu、Hg等重金属元素相对基岩的富集小于3倍;大气干湿沉降重金属元素相对土壤富集了数倍至数十倍;湘江水体主要向沿江潮土提供As、Cd物源:近50年内土壤重金属元素有较高的增加速率。不同介质间重金属元素的质量变化特点支持长沙、株洲、湘潭三市土壤重金属元素富集的主要物源为大气沉降,地表水及悬浮物是沿江湖土重金属元素的主要物源,基岩对土壤提供的物源有限的结论。 相似文献
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147.
DING Guoan CHAN Chuenyu GAO Zhiqiu YAO Wenqing LI Yoksheung CHENG Xinghong MENG Zhaoyang YU Haiqing WONG Kamhang WANG Shufeng MIAO Qiuju 《中国科学D辑(英文版)》2005,48(Z2)
The vertical structures and their dynamical character of PM2.5 and PM10 over Beijing urban areas are revealed using the 1 min mean continuous mass concentration data of PM2.5 and PM10 at 8, 100, and 320 m heights of the meteorological observation tower of 325 m at Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP CAS tower hereafter) on 10―26 August, 2003, as well as the daily mean mass concentration data of PM2.5 and PM10 and the continuous data of CO and NO2 at 8, 100 (low layer), 200 (middle layer), and 320 m (high layer) heights, in combination with the same period meteorological field observation data of the meteorological tower. The vertical distributions of aerosols observed on IAP CAS tower in Beijing can be roughly divided into two patterns: gradually and rapidly decreasing patterns, I.e. The vertical distribution of aerosols in calm weather or on pollution day belongs to the gradually decreasing pattern, while one on clean day or weak cold air day belongs to the rapidly decreasing pattern. The vertical distributive characters of aerosols were closely related with the dynamical/thermal structure and turbulence character of the atmosphere boundary layer. On the clean day, the low layer PM2.5 and PM10 concentrations were close to those at 8 m height, while the concentrations rapidly decreased at the high layer, and their values were only one half of those at 8 m, especially, the concentration of PM2.5 dropped even more. On the clean day, there existed stronger turbulence below 150 m, aerosols were well mixed, but blocked by the more stronger inversion layer aloft, and meanwhile, at various heights, especially in the high layer, the horizontal wind speed was larger, resulting in the rapid decrease of aerosol concentration, I.e. Resulting in the obvious vertical difference of aerosol concentrations between the low and high layers. On the pollution day, the concentrations of PM2.5 and PM10 at the low, middle, and high layers dropped successively by, on average, about 10% for each layer in comparison with those at 8 m height. On pollution days, in company with the low wind speed, there existed two shallow inversion layers in the boundary layer, but aerosols might be, to some extent, mixed below the inversion layer, therefore, on the pollution day the concentrations of PM2.5 and PM10 dropped with height slowly; and the observational results also show that the concentrations at 320 m height were obviously high under SW and SE winds, but at other heights, the concentrations were not correlated with wind directions. The computational results of footprint analysis suggest that this was due to the fact that the 320 m height was impacted by the pollutants transfer of southerly flow from the southern peripheral heavier polluted areas, such as Baoding, and Shijiazhuang of Hebei Province, Tianjin, and Shandong Province, etc., while the low layer was only affected by Beijing's local pollution source. The computational results of power spectra and periods preliminarily reveal that under the condition of calm weather, the periods of PM10 concentration at various heights of the tower were on the order of minutes, while in cases of larger wind speed, the concentrations of PM2.5 and PM10 at 320 m height not only had the short periods of minute-order, but also the longer periods of hour order. Consistent with the conclusion previously drawn by Ding et al., that air pollutants at different heights and at different sites in Beijing had the character of "in-phase" variation, was also observed for the diurnal variation and mean diurnal variation of PM2.5 and PM10 at various heights of the tower in this experiment, again confirming the "in-phase" temporal/spatial distributive character of air pollutants in the urban canopy of Beijing. The gentle double-peak character of the mean diurnal variation of PM2.5 and PM10 was closely related with the evident/similar diurnal variation of turbulent momentum fluxes, sensible heat fluxes, and turbulent kinetic energy at various heights in the urban canopy. Besides, under the condition of calm weather, the concentration of PM2.5 and PM10 declined with height slowly, it was 90% of 8 m concentration at the low layer, a little lesser than 90% at the middle layer, and 80% at the high layer, respectively. Under the condition of weak cold air weather, the concentration remarkably dropped with height, it was 70% of 8 m concentration at the low layer, and 20%―30% at the middle and high layers, especially the concentration of PM2.5 was even lower. 相似文献
148.
地震经济损失快速评估是应急救灾的重要决策依据。本文选取了震级、极震区烈度、极震区烈度和抗震设防烈度之差ΔI、人口密度、人均GDP等5个指标作为输入层节点,将地震灾害的直接经济损失作为输出层节点,通过对1996—2013年的地震灾害损失资料进行训练和仿真分析,构建了Elman神经网络地震经济损失快速估计模型。运用该模型,对近年来的7个破坏性地震的直接经济损失进行评估分析,评估结果和实际直接经济损失有较好的一致性,该方法为地震经济损失快速评估提供了一种新思路。 相似文献
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