Department of Civil and Environmental Engineering, University of Brasilia, Campus Universitário Darcy Ribeiro, SG12, Asa Norte, 70910-900, Brasilia, Brazil
Michéle Dal Toé Casagrande
Department of Civil and Environmental Engineering, University of Brasilia, Campus Universitário Darcy Ribeiro, SG12, Asa Norte, 70910-900, Brasilia, Brazil
André Luís Brasil Cavalcante
Department of Civil and Environmental Engineering, University of Brasilia, Campus Universitário Darcy Ribeiro, SG12, Asa Norte, 70910-900, Brasilia, Brazil
Viewed
Total article views: 3,284 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
2,385
802
97
3,284
149
194
HTML: 2,385
PDF: 802
XML: 97
Total: 3,284
BibTeX: 149
EndNote: 194
Views and downloads (calculated since 18 Sep 2023)
Cumulative views and downloads
(calculated since 18 Sep 2023)
Total article views: 2,760 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
2,040
650
70
2,760
137
183
HTML: 2,040
PDF: 650
XML: 70
Total: 2,760
BibTeX: 137
EndNote: 183
Views and downloads (calculated since 23 Apr 2024)
Cumulative views and downloads
(calculated since 23 Apr 2024)
Total article views: 524 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
345
152
27
524
12
11
HTML: 345
PDF: 152
XML: 27
Total: 524
BibTeX: 12
EndNote: 11
Views and downloads (calculated since 18 Sep 2023)
Cumulative views and downloads
(calculated since 18 Sep 2023)
Viewed (geographical distribution)
Total article views: 3,284 (including HTML, PDF, and XML)
Thereof 3,260 with geography defined
and 24 with unknown origin.
Total article views: 2,760 (including HTML, PDF, and XML)
Thereof 2,743 with geography defined
and 17 with unknown origin.
Total article views: 524 (including HTML, PDF, and XML)
Thereof 517 with geography defined
and 7 with unknown origin.
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.
The paper addresses synthetic dataset challenges in nonlinear constitutive modeling of soils,...
