Soil classification method and experimental research onCPTU based on the hierarchical clustering algorithm

Dividing the soil layer and identifying soil types are the basis for the application of CPTU. The conventional artificial stratification method is not satisfactory, but the soil behavior classification method cannot achieve the stratification effect despite its high reliability. By using the hierarchical clustering algorithm, the flow chart of CPTU soil classification based on hierarchical clustering algorithm is obtained. Through the selection of variables, CPTU test data are proposed. The test was carried out on Line 4 of the Ningbo Rail Transit with a self-developed static standardization of data, the generation of distance matrix and the determination of the number of classes. Combining the Robertson and Campanella classification maps, the soil layer classification and naming rules are based on cone penetration-drilling machine. The results of soil layer division and naming are compared with the borehole histogram. The results show that the division of 8 main layers by stratified graphs with the initial clustering parameters of cone resistance, qt, friction ratio, Rf and pore water pressure, u2, is almost identical with the drilling column. The stratified graph with qt- Rf as the initial clustering parameter can identify two thin layers which cannot be identified by qt curve alone, which reflects the role of Rf; the stratified graph with qt-u2 as the initial clustering parameter is too detailed for sandy soil classification and too rough for clay classification, indicating that u2 is insensitive to clay change and is not sensitive to sandy soil change. The stratified graph with qt- Rf-u2 as the initial clustering parameter not only retains the main characteristics of qt, but also incorporates the effects of Rf and u2 on soil stratification appropriately, and the stratification effect is the best. The undrained shear strength curve of cohesive soil in the borehole section generally conforms to the variation law of soil properties and soil depth, and reflects the accuracy of clustering stratification map from the side.