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粘性土改性细砂的强度特性
引用本文:杨瑞雪,郄玥颖,崔自治,乔彦龙,马俊斌. 粘性土改性细砂的强度特性[J]. 科学技术与工程, 2018, 18(3)
作者姓名:杨瑞雪  郄玥颖  崔自治  乔彦龙  马俊斌
作者单位:1.宁夏大学土木与水利工程学院,1.宁夏大学土木与水利工程学院,1.宁夏大学土木与水利工程学院,1.宁夏大学土木与水利工程学院,1.宁夏大学土木与水利工程学院
基金项目:教育部“长江学者和创新团队发展计划” (IRT1067);国家大学生创新训练项目(201610749025)
摘    要:粉细砂在宁夏北部分布广泛,埋藏浅,土层深厚,存在不同程度的液化倾向。围绕粘性土改善砂土抗液化性能,以银川地区粉细砂为对象,干密度,含水率和粘性土掺量为因素,设计正交试验方案,试验研究了粘性土改性细砂的强度特性,分析了各因素的作用规律,及其显著性,建立了粘聚力与干密度、粘性土含量及含水率间的多元非线性回归模型,结合土的颗粒组成和矿物组成分析了作用机理。干密度的增大能显著提高改性细砂的强度指标,粘性土可非常显著的提高细砂的粘聚力,从而显著改善细砂土的抗液化性能,且对强度不会产生明显的不利影响,建立的粘聚力关系模型显著性高,相关性较好。

关 键 词:细砂  粘性土  强度指标  回归模型
收稿时间:2017-05-11
修稿时间:2017-09-04

Strength characteristics of fine sand modified by cohesive soil
YANG Rui-xue,QIE Yue-ying,QIAO Yan-long and MA Jun-bin. Strength characteristics of fine sand modified by cohesive soil[J]. Science Technology and Engineering, 2018, 18(3)
Authors:YANG Rui-xue  QIE Yue-ying  QIAO Yan-long  MA Jun-bin
Affiliation:College of Civil and Hydraulic Engineering, Ningxia University,,,,
Abstract:The fine sand is widely distributed in the northern part of Ningxia, shallow buried, large thickness, and there are different degrees of liquefaction tendency. Around to improve the anti-liquefaction property of sand by cohesive soil, orthogonal test was designed to study the strength characteristics of fine sand modified by cohesive soil with dry density, water content and cohesive soil content. The effect and significance of factors were analyzed. The multivariate nonlinear regression model between cohesion and dry density, cohesive soil content and water content was established. The mechanism was analyzed with the particle composition and mineral composition. The increase of dry density can significantly improve the strength index of modified fine sand. The cohesive soil can improve the cohesion of fine sand remarkably, so it can improve the anti-liquefaction performance of fine sand, meanwhile will has no obvious negative effects on the strength of fine sand. The cohesion model is with high correlation and good correlation.
Keywords:fine sand   cohesive soil   strength index   regression model
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