%0 Generic %1 magiera2024replication %A Magiera, Jim M. %D 2024 %K %R 10.18419/darus-3869 %T Replication Data for: Constraint-aware neural networks for Riemann problems %X Data sets of the article "Constraint-aware neural networks for Riemann problems", consisting of training and test data sets for Riemann solutions of the cubic flux model, an isothermal two-phase model, and the Euler equations for an ideal gas. You can find detailed information in the README.md.

@misc{magiera2024replication, abstract = {Data sets of the article "Constraint-aware neural networks for Riemann problems", consisting of training and test data sets for Riemann solutions of the cubic flux model, an isothermal two-phase model, and the Euler equations for an ideal gas. You can find detailed information in the README.md. }, added-at = {2024-01-15T12:35:53.000+0100}, affiliation = {Magiera, Jim M./Universität Stuttgart}, author = {Magiera, Jim M.}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2343eceaf3167b093b7537d3963c49274/unibiblio}, doi = {10.18419/darus-3869}, howpublished = {Dataset}, interhash = {13972096182f175c582d60c0c4b0abe6}, intrahash = {343eceaf3167b093b7537d3963c49274}, keywords = {}, note = {Related to: Jim Magiera, Deep Ray, Jan S. Hesthaven, Christian Rohde, Constraint-aware neural networks for Riemann problems, Journal of Computational Physics, Volume 409, 2020, 109345. doi: 10.1016/j.jcp.2020.109345}, orcid-numbers = {Magiera, Jim M./0000-0001-9807-0784}, timestamp = {2024-01-15T11:35:53.000+0100}, title = {Replication Data for: Constraint-aware neural networks for Riemann problems}, year = 2024 }