Social Sciences and Digital Humanities Archive

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ANNOUNCEMENT 12-04-2023 – We are currently running update tests on the test platform. The website might become inaccessible at times.

Welcome to the test instance of SODHA, the federal Belgian data archive for social sciences and the digital humanities. Here you can make as many tests as you like.

The SODHA platform is accessible here: https://www.sodha.be

If you have any question, you can contact us at sodha@arch.be.

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591 to 600 of 656 Results

pc_input.py Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow Plain Text - 370 B - MD5: 61e61daa130e8a1cc148554ad6ce64cf
pc.py Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow Plain Text - 330 B - MD5: 890f3e6dfc2368c1253cb89f561e9ad5
pc_setup.py Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow Plain Text - 794 B - MD5: a8ad57e1ee33b4b3829f521edcb5f6cd
plot_functions.py Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow Plain Text - 14.0 KB - MD5: 2c2374184e88708796ac63b854c4531c
pointmodel.py Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow Plain Text - 9.5 KB - MD5: 361483cb9e8f0ec1d80940f1ba785870
Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow Feb 20, 2020 Strand, Andreas, 2020, "Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow", https://doi.org/10.18710/OWKABR, Social Sciences and Digital Humanities Archive – SODHA [test instance], V1 Code and data for performing uncertainty quantification and sensitivity analysis of a multiphase flow model. The software computes the uncertainty in model predictions in the presence of uncertain input variables. The analysis also determines which variables the predictions are s...
00_ReadMe.txt Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow Plain Text - 658 B - MD5: 79e7caf7442849b2265360d7eb39c83d
mc_functions.py Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow Plain Text - 7.3 KB - MD5: 6751ae5a7540b238c0e2024ac12485a2
mc_input.py Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow Plain Text - 355 B - MD5: 0fb6848b735ad7ab9209c192abd0fef9
mc.py Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow Plain Text - 353 B - MD5: e995d5f332792b25518c6ef4de7bf525

pc_input.py

Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow

Plain Text - 370 B -

pc.py

Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow

Plain Text - 330 B -

pc_setup.py

Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow

Plain Text - 794 B -

plot_functions.py

Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow

Plain Text - 14.0 KB -

pointmodel.py

Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow

Plain Text - 9.5 KB -

Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow

Feb 20, 2020

Strand, Andreas, 2020, "Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow", https://doi.org/10.18710/OWKABR, Social Sciences and Digital Humanities Archive – SODHA [test instance], V1

Code and data for performing uncertainty quantification and sensitivity analysis of a multiphase flow model. The software computes the uncertainty in model predictions in the presence of uncertain input variables. The analysis also determines which variables the predictions are s...

00_ReadMe.txt

Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow

Plain Text - 658 B -

mc_functions.py

Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow

Plain Text - 7.3 KB -

mc_input.py

Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow

Plain Text - 355 B -

mc.py

Feb 20, 2020 - Replication Data for: Uncertainty propagation through a point model for steady-state two-phase pipe flow

Plain Text - 353 B -

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