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作 者:贺拿[1,2,3] 陈宁生[1] 朱云华[1,2] 杨建元 杨成林[1]
机构地区:[1]中国科学院水利部成都山地灾害与环境研究所山地灾害与地表过程重点实验室,成都610041 [2]中国科学院大学,北京100049 [3]河南理工大学土木工程学院,河南焦作454000 [4]浙江华东建设工程有限公司,杭州310030
出 处:《岩土力学》2014年第9期2543-2548,共6页Rock and Soil Mechanics
基 金:十二五国家科技支撑计划课题(No.2011BAK12B02);国家自然科学基金青年科学基金项目(No.41201555);国家自然科学基金资助(No.41302284);国家自然科学基金资助(No.51209195);中国科学院水利部成都山地灾害与环境研究所青年基金
摘 要:以取自泥石流易发区的182个砾石土土样为基础,进行室内颗分试验,通过分形理论计算各土样的分维值,经计算发现,泥石流源区砾石土以一重分形为主,一重分形的土样占样本总数的88.46%,一重分形土样的分维值介于2.250~2.798之间;以此数据为基础配置土样,通过自制、可控的常水头试验装置进行渗透试验。试验结果表明,渗透系数k与分维值D之间有极显著的相关性,且在干密度为1.8 g/cm3时相关性最好。通过多元回归分析发现,不同密度条件下,k与D之间均有较好的幂函数关系;相同的分维值条件下土样的渗透系数随密度的增大呈减小的趋势,分维值在2.450~2.600之间时,样本的干密度d?与渗透系数k之间的幂函数关系较为明显。试验结果可以为泥石流启动的临界雨量研究提供理论基础,提高已有预报模型的普适性及精度。On the basis of 182 gravelly soil samples taken from debris flow source area, the particle size distribution are obtained through laboratory test, fractal dimensions of samples are calculated by fractal theory. Analysis of calculated results show that the gravelly soil samples are mainly one dimension fractal;and it account for 88.46%of the total samples, the value of one dimension fractal is between 2.250-2.798. Based on the calculated fractal dimension, soil samples are configured;and self-made constant head device with controllable waterhead are used to conduct penetration experiment. The experimental results indicate that the correlation between permeability coefficient and fractal dimension is significant. When dry density equals 1.8 g/cm3, the correlation of permeability coefficient and fractal dimension is best; and the relationship between permeability coefficient and fractal dimension shows obvious power function using multiple regression analysis under different density conditions. Moreover, under same fractal dimension (condition), the permeability coefficient decreases with the increase of density;the power function relation between fractal dimension and permeability coefficient is obvious when fractal dimension ranges from 2.450 to 2.600. This study results can provide theory basis for future critical rainfall research; meanwhile, these can improve the universality and accuracy of the existing forecasting models.
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