19,711 to 19,720 of 20,142 Results
Nov 24, 2021 -
Code of the tBME method
RAR Archive - 245.4 KB -
MD5: 215dd1b236398f8c6638b322e7db88f8
Data for the publication "Diagnosis of model errors with a sliding time-window Bayesian analysis" in Journal Water Resource Research. This folder includes the files and data to generate the tBME analysis plots for Case 1, Case 2, Case 3, and real data Case. |
Nov 24, 2021 - PN 1-6
Schulz, Sebastian; Bringedal, Carina; Ackermann, Sina, 2021, "Code for relative permeabilities for two-phase flow between parallel plates with slip conditions", https://doi.org/10.18419/DARUS-2241, DaRUS, V1
This MATLAB code calculates relative permeabilities of two fluids flowing between two parallel plates, depending on their viscosities, saturation and boundary conditions at the top and bottom plates. The underlying assumptions behind the derivation are shown in the pdf "overview_relativepermeabilities.pdf", where also the resulting equations are li... |
Nov 24, 2021 -
Code for relative permeabilities for two-phase flow between parallel plates with slip conditions
Objective-C Source Code - 771 B -
MD5: 4023c6b9ebbe56673b683e3e6cc127b5
Example script on how to use relativePermeabilities.m |
Nov 24, 2021 -
Code for relative permeabilities for two-phase flow between parallel plates with slip conditions
Adobe PDF - 160.5 KB -
MD5: 295831a59379d0f398f7dbe168a59b65
Underlying assumptions behind the relative permeabilities |
Nov 24, 2021 -
Code for relative permeabilities for two-phase flow between parallel plates with slip conditions
Objective-C Source Code - 4.3 KB -
MD5: f05cb34f371fe59b9208e7b5ea9f42a4
Calculation of relative permeabilities |
Nov 22, 2021PN 1
SimTech Project PN 1-6 "Upscaling of two-phase porous media flow based on fluid morphology." |
Oct 15, 2021 - PN 6
Zaverkin, Viktor; Holzmüller, David; Steinwart, Ingo; Kästner, Johannes, 2021, "Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments", https://doi.org/10.18419/DARUS-2136, DaRUS, V1
Code and documentation for the improved Gaussian Moments Neural Network (GM-NN). An updated version can be found on GitLab |
Oct 15, 2021 -
Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments
Python Source Code - 2.8 KB -
MD5: 43201d1bd5e849ffc4b7794c6ab8e87c
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Oct 15, 2021 -
Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments
Unknown - 89 B -
MD5: 8250c6756d6506ffa4b66dd979abe8eb
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