岩石颗粒破碎的尺寸效应

固体颗粒破碎强度的尺寸效应是一种普遍存在的现象,冰块、岩石颗粒、陶瓷和混凝土块等的破碎强度都表现出随颗粒直径增加而减小的现象,分形模型为解释固体颗粒破碎强度的尺寸效应提供了可行的方法。本文采用Steacy和Sammis分形模型模拟了岩石颗粒压碎特征,分析岩石颗粒破碎后的颗粒分布规律,给出颗粒破碎分维的确定方法,建立颗粒压碎强度与粒径的理论关系,颗粒破碎强度与颗粒粒径的关系用分维D表示为fdD-3。已有的颗粒破碎分布的数据表明,岩石颗粒破碎的分维大约为2.50～2.60,颗粒破碎强度符合用分维表示的尺寸效应。     

一种基于小波域的分形遥感影像压缩方法

解决大数据量遥感影像传输和存储问题的方案之一,是对遥感影像进行高保真快速压缩。通过对遥感影像进行小波变换产生子带频域之间的相似性,再利用分形方法对具有相似性的相邻高频子带进行编码,由高一级的子影像构造低一级的子影像,然后采用分形迭代解码和小坡变换的逆变换重建影像。实验结果表明,该方法在一定程度上能够提高压缩比,在压缩时间上比传统的分形方法有明显的缩短,并且压缩后影像信息的损失量较少,影像恢复的质量较好。     

广东省公路交通网络分形空间特征研究

基于分形理论,以GIS技术为支撑,利用回转半径法测算了广东省全域及其所辖21个地级市公路交通网络半径维数D_L、分枝维数D_b和对应相关系数R²。依据广东省公路交通网络的特点,将其辖区分为四个子区域:珠三角、东部沿海、西部沿海和粤北地区,分析其半径维数和分枝维数的空间分布特征。研究表明,珠三角地区为广东省公路交通网络密度最大、结构最复杂、功能最完善、连通性最优的区域;以珠三角为中心,广东省公路交通网络分形半径维数和分枝维数随距离增大而衰减,沿海衰减程度微弱,粤北衰减程度较大。结果显示,半径维数和分枝维数结合能够更为合理系统地分析交通网络分形特征的时空差异特性。     

海南岭壳铜(银-金)矿床地质特征及找矿方向

岭壳铜(银-金)矿床赋存于白垩纪岭壳村组流纹质角砾凝灰熔岩和早白垩世花岗闪长岩中.目前已发现11条铜(银-金)矿(化)体,矿体的产出严格受断裂破碎带控制,与成矿关系密切的围岩蚀变呈现出自东(20线)向西的钾化→绢云母化→强高岭石化、绿泥石化蚀变分带,矿化相应呈现从铜(金)向铜(银)的过渡.根据其对称性的蚀变分带,应加强20线以东的地质找矿;根据成矿元素分形和统计研究发现,Au,Ag矿化具有专属性,即在流纹质凝灰熔岩中寻找Cu,Ag矿,而在花岗闪长岩中以寻找Cu,Au矿为主.     

分形理论在云南个旧锡矿遥感信息定量化分析中的应用

应用分形理论和方法对个旧锡矿遥感信息进行了定量化研究.结果显示,在格子边长为1.4～4.5 km的标度范围内,其遥感蚀变和断裂构造进入的总格子数的对数与格子边长的对数均具有很好的线性相关性,表明在研究标度范围内,各子区遥感线性与蚀变信息具有良好的统计自相似性和分形特征.在此基础上,以19号区和26号区为例,分析并进一步探讨了遥感信息分形特征的成矿意义.     

两次区域性暴雨过程副高三维结构对比分析

为探讨夏季不同大气环流背景下区域性暴雨过程副高结构特征及其对降水的贡献,利用2005年6-7月降水量和NCEP／NCAR逐日再分析等资料,采用特征指数分析和物理量诊断方法,对比分析了2005年夏季两次区域性暴雨的副高三维结构特征。结果发现,夏季不同的大气环流背景下,两次区域性暴雨过程副高结构性质分别表现为热力性高压脊和动力性高压脊特征,从而导致两次暴雨过程的水汽供应条件和产生强烈上升运动的大尺度背景场存在差异。     

基于分形理论的赫巴流体在多孔介质中的渗流模型

泥浆是一种用途广泛的工程浆液,在工程施工过程中会渗流进入地层,给工程带来一定的影响。为深入研究泥浆的渗流机理,把地层模拟为多孔介质,泥浆模拟为能更全面地反映其流变性能的赫巴流体,基于分形理论,建立赫巴流体在多孔介质中的渗流模型。基于渗流模型计算结果,详细分析压力梯度、流性指数、稠度系数及孔隙率等参数对多孔介质中赫巴流体瞬时平均流速的影响,指出流速变化与压力梯度、流性指数及稠度系数的变化均呈幂指数关系,与孔隙率变化呈二项式关系,且流性指数是一个影响赫巴流体渗流速度的极敏感因素。渗流模型计算结果为相关工程中泥浆方案的设计与施工奠定了一定的理论基础。     

Piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events on the Loess Plateau,China

Establishing a universal watershed‐scale erosion and sediment yield prediction model represents a frontier field in erosion and soil/water conservation. The research presented here was conducted on the Chabagou watershed, which is located in the first sub‐region of the hill‐gully area of the Loess Plateau, China. A back‐propagation artificial neural model for watershed‐scale erosion and sediment yield was established, with the accuracy of the model, then compared with that of multiple linear regression. The sensitivity degree of various factors to erosion and sediment yield was quantitatively analysed using the default factor test. On the basis of the sensitive factors and the fractal information dimension, the piecewise prediction model for erosion and sediment yield of individual rainfall events was established and further verified. The results revealed the back‐propagation artificial neural network model to perform better than the multiple linear regression model in terms of predicting the erosion modulus, with the former able to effectively characterize dynamic changes in sediment yield under comprehensive factor conditions. The sensitivity of runoff erosion power and runoff depth to the erosion and sediment yield associated with individual rainfall events was found to be related to the complexity of surface topography. The characteristics of such a hydrological response are thus closely related to topography. When the fractal information dimension is greater than the topographic threshold, the accuracy of prediction using runoff erosion power is higher than that of using runoff depth. In contrast, when the fractal information dimension is smaller than the topographic threshold, the accuracy of prediction using runoff depth is higher than that of using runoff erosion power. The developed piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events, which introduces runoff erosion power and runoff depth using the fractal information dimension as a boundary, can be considered feasible and reliable and has a high prediction accuracy. Copyright © 2013 John Wiley & Sons, Ltd.     

Size and spatial distribution of loess slides on the Chinese Loess Plateau

ABSTRACT

The size and spatial distribution of loess slides are important for estimating the yield of eroded materials and determining the landslide risk. While previous studies have investigated landslide size distributions, the spatial distribution pattern of landslides at different spatial scales is poorly understood. The results indicate that the loess slide distribution exhibits a power-law scaling across a range of the size distribution. The mean landslide size and size distribution in the different geomorphic types are different. The double Pareto and inverse gamma functions can coincide well with the empirical probability distribution of the loess slide areas and can quantitatively reveal the rollover location, maximum probability, and scaling exponents. The frequency of loess slides increases with mean monthly precipitation. Moreover, point distance analysis showed that > 80% of landslides are located < 3 km from other loess slides. We found that the loess slides at the two study sites (Zhidan and Luochuan County) in northern Shaanxi Province, China show a significant clustered distribution. Furthermore, analysis results of the correlated fractal dimension show that the landslides exhibit a dispersed distribution at smaller spatial scales and a clustered distribution at larger spatial scales.     

分形分维理论在地质灾害发育及空间分布规律中的应用——以长安区滑坡、崩塌地质灾害为例

长安区区内地层岩性、地质构造多样,加之人类经济工程活动、降雨、地震等诱发影响,秦岭北坡及黄土台塬边缘滑坡崩塌地质灾害发育,是陕西省地质灾害较严重的县(区)之一。本文以长安区为研究区域,在对长安区自然地理及区域地质环境条件等资料充分收集的基础上,结合长安区滑坡崩塌灾害点的实际调查资料,详细分析了长安区的滑坡崩塌灾害发育特征及空间分布规律,并采用网络覆盖法,对长安区滑坡崩塌地质灾害的空间分布进行了分形分维计算。求得地质灾害的空间分布分维值为0.876 6,反应出长安区滑坡崩塌地质灾害空间分布特性的复杂性。研究结果表明,分形分维理论能合理评价地质灾害空间分布特征,对类似地区的地质灾害空间分布特征分析具有借鉴意义。