文章摘要
侯晓坤,李同录,谢萧,晁建红,赵权利,张常亮.甘肃Q3原状黄土的微观结构对其土-水特征曲线的影响[J].水利学报,2016,47(10):1307-1314
甘肃Q3原状黄土的微观结构对其土-水特征曲线的影响
Effect of undisturbed Q3 loess's microstructure on its SWCC
投稿时间:2015-11-30  
DOI:10.13243/j.cnki.slxb.20151290
中文关键词: 黄土  土-水特征曲线  微观结构  孔隙分布曲线
英文关键词: loess  SWCC  microstructure  pore size distribution
基金项目:国家重点基础研究发展计划(973计划)项目(2014CB744701);国家自然科学基金项目(41372329,41502286)
作者单位
侯晓坤 长安大学 地质工程与测绘学院, 陕西 西安 710054 
李同录 长安大学 地质工程与测绘学院, 陕西 西安 710054
中国地质调查局西安地质调查中心 国土资源部黄土地质灾害重点试验室, 陕西 西安 710054 
谢萧 长安大学 地质工程与测绘学院, 陕西 西安 710054 
晁建红 长安大学 地质工程与测绘学院, 陕西 西安 710054 
赵权利 长安大学 地质工程与测绘学院, 陕西 西安 710054 
张常亮 长安大学 地质工程与测绘学院, 陕西 西安 710054 
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中文摘要:
      为了探究原状黄土土-水特征曲线与土样微观结构之间的关系,对甘肃黑方台不同埋深Q3原状黄土进行了基本物理指标的测试,张力计法测得其土-水特征曲线,并利用Fredlund&Xing模型对土-水特征曲线进行了拟合。采用光学显微镜和Photoshop合成技术获得了不同埋深土样的微观结构,统计得到孔隙累积级配曲线和分布曲线。结果表明不同埋深Q3黄土,颗粒组成相同;其土水特征曲线,在饱和区,相同基质吸力下土样埋深(干密度)越大,体积含水率越小;而在过渡区,体积含水率则越大;在残余区,土水特征曲线几乎重合,这种差异主要是由土样的孔隙分布特征所控制。最后根据土样的分布曲线建立了黄土土水特征的本构关系,其预测值同实测值基本吻合。
英文摘要:
      In order to explore the relationship between the soil water characteristic curves (SWCC) of un-disturbed loess with its microstructure,basic mechanical parameters of undisturbed Q3 loess at the same lo-cation but different buried depth were measured firstly and then the corresponding SWCCs by the TEN ten-sionmeter. The measured SWCC was modeled by the Fredlund & Xing model. Afterwards the microstruc-tures of undisturbed Q3 loess at different buried depths were obtained by the optical microstructure and the Photoshop Synthesis Technology. The pore size distribution characteristic was quantitatively analyzed to ob-tain the pore size cumulative distribution and pore size distribution curves. The results show that the soil particles of the intact Q3 loess at different buried depth are the same; for the SWCCs, in the saturated zone, the bigger the buried depth is, the lower the volumetric water content is at the same suction value, while the relationship in the transitional zone is contrary to the saturated zone; at the residual zone, the SWCCs of intact Q3 loess converges together. This discrepancy is mainly controlled by the different pore size distributions. Then a model based on the pore size distribution curves was established to predict the SWCC and the predicting values are close to the measured ones.
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