The use of a cluster analysis in a Ménard pressuremeter survey Available to Purchase

Cluster analysis is a statistical method used for grouping data that have similar mathematical characteristics in subsets with common or homogeneous values. This method can be used in various fields of data for which no division is known a priori and can be useful for identification of soil horizons for site characterisation. Cluster analyses for in situ applications are composed of the following six steps: selection of variables; standardisation of the data; development of a resemblance distance matrix; choice of a clustering technique; determination of the number of clusters; and interpretation of cluster results. Various types of in situ test data can be treated in this way, such as cone penetration testing data. A Ménard pressuremeter data analysis by cluster is presented here, which uses as the statistical variables: p_LM; E; E/E_M; E_M/p*_LM. The results relate to the relevance of these variables in identification of soil horizons, and to the best possible combination of data to characterise the various geological layers of the site of the northern tunnel of Grenoble.