%0 Generic
%A Varkey, Divya
%A Hicks, Michael A.
%A van den Eijnden, Abraham P.
%D 2025
%T Scripts underlying the publication: Predicting subsurface classification in 2D from cone penetration test data
%U 
%R 10.4121/e36a2326-5492-420e-9fe5-05299c10d28c.v1
%K cone penetration tests
%K site characterisation
%K stratigraphic uncertainty
%X <p><span style="color: rgb(31, 31, 31);">This dataset contains the script underlying the manuscript titled '</span>Predicting subsurface classification in 2D from cone penetration test data<span style="color: rgb(31, 31, 31);">'. The script can be used for predicting the most likely 1D classification of the subsurface at CPT locations. The uncertainties in the CPT measurements and transformation to soil units are accounted for by integrating the Robertson chart with the Bayesian approach. The classification is carried out in two steps: (a) for a given number of layers, identifying the most probable soil layer thicknesses, and (b) identifying the most likely number of layers which, together with the most probable thicknesses, maximises the likelihood of observing the CPT measurements. The script can be used with any CPT data in .gef format.</span></p>
%I 4TU.ResearchData