饱和砂卵石介质渗透系数线性预报模型研究

Linear Prediction Model of Permeability Coefficient of the Saturated Sandy Gravel Medium

以黄河中游段河床自然堆积砂砾石堆积体为研究对象,通过室内不同粒径特征混合体的系统渗流试验,探讨了砂卵石的粒径组成特征对渗透系数的影响,建立了以有效粒、限制粒径、不均匀系数和曲率系数为自变量的渗透系数线性预报模型。结果表明,砂卵石的渗透系数可用多元线性回归模型进行预测。回归模型及自变量对预测量的影响均显著,模型预测值与实测值平均相对误差为12.39%。

Taking the sand gravel piled up naturally in the river bed in the middle reaches of the Yellow River as the subject, indoor experiments on the systematic seepage flow of diversified grain sizes mixture were carried out to study the effects of the grain size characteristics of sandy gravel on permeability coefficient, and linear prediction model of permeability coefficient was established with the effective grain size, restriction grain size, coefficient of uniformity and coefficient of curvature as independent variables. The results indicated that the permeability coefficient of sandy gravel could be predicted by the diverse linear regression model. Regression model and independent variables had great influence on the prediction, and the average error between the model prediction and actually measured data was 12.39%.