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Cone penetration test dataset Premstaller Geotechnik

The dataset contains 1339 cone penetration tests (CPT, CPTu, SCPT, SCPTu) executed within Austria and Germany by the company Premstaller Geotechnik ZT GmbH. As a first processing step, core drillings, located within a maximum distance of approximately 50 m to the insitu tests, were assigned to these...

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Autores principales: Oberhollenzer, Simon, Premstaller, Michael, Marte, Roman, Tschuchnigg, Franz, Erharter, Georg H., Marcher, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744689/
https://www.ncbi.nlm.nih.gov/pubmed/33354601
http://dx.doi.org/10.1016/j.dib.2020.106618
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author Oberhollenzer, Simon
Premstaller, Michael
Marte, Roman
Tschuchnigg, Franz
Erharter, Georg H.
Marcher, Thomas
author_facet Oberhollenzer, Simon
Premstaller, Michael
Marte, Roman
Tschuchnigg, Franz
Erharter, Georg H.
Marcher, Thomas
author_sort Oberhollenzer, Simon
collection PubMed
description The dataset contains 1339 cone penetration tests (CPT, CPTu, SCPT, SCPTu) executed within Austria and Germany by the company Premstaller Geotechnik ZT GmbH. As a first processing step, core drillings, located within a maximum distance of approximately 50 m to the insitu tests, were assigned to these cone penetration tests, which allow an interpretation of the insitu measurements based on its grain size distribution. In a second step, the software Geologismiki 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 (q(c), f(s), R(f), u(2), V(s)), normalized measures (i.e. Q(t), B(q), U(2)) and soil classifications.
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spelling pubmed-77446892020-12-21 Cone penetration test dataset Premstaller Geotechnik Oberhollenzer, Simon Premstaller, Michael Marte, Roman Tschuchnigg, Franz Erharter, Georg H. Marcher, Thomas Data Brief Data Article The dataset contains 1339 cone penetration tests (CPT, CPTu, SCPT, SCPTu) executed within Austria and Germany by the company Premstaller Geotechnik ZT GmbH. As a first processing step, core drillings, located within a maximum distance of approximately 50 m to the insitu tests, were assigned to these cone penetration tests, which allow an interpretation of the insitu measurements based on its grain size distribution. In a second step, the software Geologismiki 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 (q(c), f(s), R(f), u(2), V(s)), normalized measures (i.e. Q(t), B(q), U(2)) and soil classifications. Elsevier 2020-12-07 /pmc/articles/PMC7744689/ /pubmed/33354601 http://dx.doi.org/10.1016/j.dib.2020.106618 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Oberhollenzer, Simon
Premstaller, Michael
Marte, Roman
Tschuchnigg, Franz
Erharter, Georg H.
Marcher, Thomas
Cone penetration test dataset Premstaller Geotechnik
title Cone penetration test dataset Premstaller Geotechnik
title_full Cone penetration test dataset Premstaller Geotechnik
title_fullStr Cone penetration test dataset Premstaller Geotechnik
title_full_unstemmed Cone penetration test dataset Premstaller Geotechnik
title_short Cone penetration test dataset Premstaller Geotechnik
title_sort cone penetration test dataset premstaller geotechnik
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744689/
https://www.ncbi.nlm.nih.gov/pubmed/33354601
http://dx.doi.org/10.1016/j.dib.2020.106618
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