膨胀土的自由膨胀率与矿物组成关系试验研究
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摘要
以揭示膨胀土自由膨胀率的内在规律为研究目的,对膨胀土自由膨胀率的影响因素进行试验研究,结果表明:本文模型能定量分析膨胀土膨胀势与矿物组成之间的相关关系,并能很好地拟合实测数据;可以定量预测膨胀土的膨胀势,并解释膨胀土膨胀特性与矿物组成之间的内在规律。
The purpose of this study is to reveal the inherent law of free expansion rate of expansive soil. In this paper,the influence factors of free expansion rate of expansive soil is studied. The results show that the model can quantitatively analyze the coupling relationship between swelling potential and mineral composition of expansive soil,and can well fit the measured data. It can predict the expansive potential of expansive soil very accurately,and quantitatively explain the inherent law between swelling characteristics and mineral composition of expansive soil,which provides a basis for researchers to explain quantitatively the swelling reason of expansive soil.
The purpose of this study is to reveal the inherent law of free expansion rate of expansive soil. In this paper,the influence factors of free expansion rate of expansive soil is studied. The results show that the model can quantitatively analyze the coupling relationship between swelling potential and mineral composition of expansive soil,and can well fit the measured data. It can predict the expansive potential of expansive soil very accurately,and quantitatively explain the inherent law between swelling characteristics and mineral composition of expansive soil,which provides a basis for researchers to explain quantitatively the swelling reason of expansive soil.
引文
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[4]赵月平.膨胀土分类的分形插值评价方法[J].人民黄河,2015,37(6):91-94.
[5]高卫东,刘永建.熵权可拓模型在膨胀土胀缩等级判别中的应用[J].长江科学院院报,2012,29(11):91-94.
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[7]吕海波,宁世朝,赵艳林,等. SOM神经网络在膨胀土分类中的应用[J].土工基础,2006,20(4):90-93.
[8]邓丁杰.基于开源GIS的海南省公路膨胀土信息管理系统开发研究[D].长沙:长沙理工大学,2014.
[9]李萍.基于非线性主成分和聚类分析法的膨胀土分类[J].人民长江,2012,43(7):40-43.
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[11]师旭超,郭志涛.膨胀土等级判别的遗传支持向量机多分类方法[J].土木建筑与环境工程,2009,31(4):44-48+59.
[12]戴绍斌,黄俊,夏林.鄂北膨胀土的矿物组成和化学成分分析[J].岩土力学,2005,1(S1):296-299.
[13]邵梧敏,谭罗荣,张梅英,等.膨胀土的矿物组成与膨胀特性关系的试验研究[J].岩土力学,1994,1(1):11-19.
[2]汪明武,李健,徐鹏,等.膨胀土与石灰改良膨胀土胀缩性的云模型评价[J].东南大学学报(自然科学版),2014,44(2):396-400.
[3]赵国彦,李鑫,梁伟章.膨胀土分类的改进TOPSIS法及应用[J].中国地质灾害与防治学报,2017,12(3):130-136.
[4]赵月平.膨胀土分类的分形插值评价方法[J].人民黄河,2015,37(6):91-94.
[5]高卫东,刘永建.熵权可拓模型在膨胀土胀缩等级判别中的应用[J].长江科学院院报,2012,29(11):91-94.
[6]董陇军,李夕兵,宫凤强.膨胀土胀缩等级分类的未确知均值聚类方法及应用[J].中南大学学报(自然科学版),2008,39(5):1075-1080.
[7]吕海波,宁世朝,赵艳林,等. SOM神经网络在膨胀土分类中的应用[J].土工基础,2006,20(4):90-93.
[8]邓丁杰.基于开源GIS的海南省公路膨胀土信息管理系统开发研究[D].长沙:长沙理工大学,2014.
[9]李萍.基于非线性主成分和聚类分析法的膨胀土分类[J].人民长江,2012,43(7):40-43.
[10]文畅平.膨胀土判别的属性测度模型[J].公路交通科技,2008,25(5):34-39.
[11]师旭超,郭志涛.膨胀土等级判别的遗传支持向量机多分类方法[J].土木建筑与环境工程,2009,31(4):44-48+59.
[12]戴绍斌,黄俊,夏林.鄂北膨胀土的矿物组成和化学成分分析[J].岩土力学,2005,1(S1):296-299.
[13]邵梧敏,谭罗荣,张梅英,等.膨胀土的矿物组成与膨胀特性关系的试验研究[J].岩土力学,1994,1(1):11-19.