Cone penetration test dataset Premstaller Geotechnik
Simon Oberhollenzer1, Michael Premstaller2, Roman Marte1, Franz Tschuchnigg1, Georg H. Erharter3, Thomas Marcher3
1. Institute of Soil Mechanics, Foundation Engineering and Computational Geotechnics, Graz University of Technology
2. Premstaller Geotechnik ZT GmbH, Austria
3. Institute of Rock Mechanics and Tunnelling, Graz University of Technology
The dataset contains 1339 cone penetration tests (CPT, CPTu, SCPT, SCPTu) executed within Austria and Germany by the company Premstaller Geotechnik ZT GmbH. Core drillings, located within a maximum distance of approximately 50 m to the insitu tests, are assigned to these cone penetration tests, which allow an interpretation based on its grain size distribution. In a second step, the software Geologismiki (Ref: CPeT-IT User’s manual v.1.4) was used to calculate various normalized measures, which can e.g. be used as input parameters for soil behaviour type charts. The present data can be utilized by researches for example to develop new approaches related to soil classification based on cone penetration test. Furthermore, it provides a framework for combining insitu measurements (qc, fs, Rf, u2, Vs), normalized measures (i.e. Qt, Bq, U2) and standard soil classifications based on grain size distribution.
Value of data
The dataset includes 1339 CPT, CPTu, SCPT and SCPTu executed in a wide range of grain size distributions within Austria and Germany. All cone penetration tests have been performed by Premstaller Geotechnik ZT GmbH. Furthermore, the soil classification of core drillings was assigned to 490 insitu tests, which allow an interpretation (of the insitu measuments) based on the grain size distribution.
The data can be used by researches to develop e.g. new approaches related to soil classification or the identification of soil layers based on CPT results.
The data provide a framework for combining insitu measurements (qc, fs, Rf, u2, Vs), normalized measures (i.e. Qt, Bq, U2) and standard soil classifications (of core drillings) to achieve an improved characterization of soils.
The dataset addresses the problem that there is a lack of publicly available datasets that can be used for benchmark tests in geotechnics (e.g. for machine learning applications). This dataset could be used as basis of supervised machine learning techniques for CPT data processing.
Please use the following reference in your work / publications if you use the database: Oberhollenzer S., Premstaller M., Marte R., Tschuchnigg F., Erharter G.H., Marcher T. (2020): CPT dataset Premstaller Geotechnik. Data in Brief.