黄土湿陷系数与物性指标的相关性分析

Correlation Analysis of Loess Collapsibility Coefficient and Physical Property Index

为了探究湿陷系数与物性指标间的内在关系,在西安市南郊神禾塬采取270组土样进行室内试验,分析湿陷系数与12个物性指标的相关性,选取与湿陷系数具有高度相关关系的7个物性指标作为自变量,以平方根变换后的正态变量为因变量,采用逐步回归分析方法建立以天然密度、压缩系数、孔隙率、饱和度为自变量的最优回归模型,用同一场地的另外29组实测数据验证该预测模型的准确性。结果表明:该回归模型具有统计学意义,4个自变量对因变量的影响也均有统计学意义;湿陷系数实测值与预测值的决定系数等于0.930,二者得到的湿陷等级一致,说明该回归模型的预测精度较高。研究结果对于快速准确地预测黄土的湿陷系数具有一定的参考价值。

To explore the inherent relationship between collapsibility coefficient and physical property indexes,270 groups of soil samples were taken from Shenhe Plateau in the southern suburb of Xi'an for indoor tests.The correlation between the collapsibility coefficient and 12 physical property indexes was analyzed.Seven physical property indexes highly correlated with the collapsibility coefficient were selected as independent variables,the normal variables after square root transformation were used as dependent variables,and an optimal regression model with natural density,coefficient of compressibility,porosity,and saturation as independent variables was established by stepwise regression analysis method.Another 29 groups of measured data from the same site were used to verify the accuracy of the prediction model.The results show that the regression model is statistically significant,and the effects of the four independent variables on the dependent variables are also statistically significant;The determination coefficient between the measured value and the predicted value of the collapsibility coefficient is equal to 0.930,and the collapsibility grades obtained by the two ways are consistent,indicating that the prediction accuracy of the regression model is high.The study results have certain reference value and practical engineering significance for quick and accurate prediction of the collapsibility coefficient of loess.