61 to 70 of 1,579 Results
May 28, 2025 -
Replication data for: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples
Jupyter Notebook - 220.0 KB -
MD5: 2bd38fd3b633e2b99ec006f005d23344
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May 28, 2025 -
Replication data for: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples
Tabular Data - 75.0 KB - 13 Variables, 1143 Observations - UNF:6:E3SROxRmTcGbJ1ofdnmuQQ==
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May 28, 2025 -
Replication data for: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples
Jupyter Notebook - 9.4 MB -
MD5: b5c33cf21b8296e0db6be85ca86b0027
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Unknown - 2.7 MB -
MD5: dcfd845bd702ec32c9a1f535055851d4
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Python Source Code - 6.9 KB -
MD5: 8c3ffcbd807c11ce809a4a9fdf2a1311
A python script for generating scattering geometrical imperfections as described in the dissertation of Janusch Töpler. |
Python Source Code - 4.1 KB -
MD5: a0737f42ce03c8fabf670f88ed232468
A user function for scatter_geomImp.py for sampling according to different distribution functions. |
Python Source Code - 209.5 KB -
MD5: 17c376cf74962dddf8dc8ba033edd86a
Python input file for an automated geometrically and materially nonlinear numerical analysis of timber beam-columns with Abaqus/CAE. |
Plain Text - 700.2 KB -
MD5: b08c262c08ff8e9c00b76d7dd32d0e6c
Input data for Abaqus_timber_beam-column.py with scattering material parameters according to the KaReMo+. |
Plain Text - 3.6 KB -
MD5: 808e1d54ed84fbf7ba523d5ee8d45fe2
Input data for Abaqus_timber_beam-column.py with measured geometrical imperfections, see DIBt - ZP 52-5-13.194 (https://doi.org/10.18419/DARUS-3304). |
Plain Text - 91.4 KB -
MD5: 0914e56d536a0350287eef41fac0c834
Input data for Abaqus_timber_beam-column.py with scattering geometrical imperfections. |