Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 8
Articles | Volume 17, issue 8
https://doi.org/10.5194/gmd-17-3175-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-3175-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 8
Model experiment description paper
 | 
23 Apr 2024
Model experiment description paper |  | 23 Apr 2024

NorSand4AI: a comprehensive triaxial test simulation database for NorSand constitutive model materials

Luan Carlos de Sena Monteiro Ozelim, Michéle Dal Toé Casagrande, and André Luís Brasil Cavalcante

Viewed

Total article views: 1,422 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
981 377 64 1,422 59 52
  • HTML: 981
  • PDF: 377
  • XML: 64
  • Total: 1,422
  • BibTeX: 59
  • EndNote: 52
Views and downloads (calculated since 18 Sep 2023)
Cumulative views and downloads (calculated since 18 Sep 2023)

Viewed (geographical distribution)

Total article views: 1,422 (including HTML, PDF, and XML) Thereof 1,422 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 08 May 2025
Download
Short summary
The paper addresses synthetic dataset challenges in nonlinear constitutive modeling of soils, providing two datasets: one with 2000 soil types, 40 test conditions each (160 000 triaxial tests), and a second with 2048 soil types, 42 test conditions each (172 032 triaxial tests). Each dataset is a 4000×10 matrix applicable for multivariate forecasting and geotechnical simulations. In addition, a new Python code is introduced, empowering researchers to leverage Python packages for NorSand analyses.
Read more
Share