1 to 10 of 23 Results
Mar 11, 2024 - Institute for Theoretical Physics IV
Speck, Thomas; Papanikolaou, Nikos, 2024, "Supplementary material for `Dynamic renormalization of scalar active field theories`", https://doi.org/10.18419/darus-4073, DaRUS, V1
The following folders have Jupyter notebook files that are used to obtain the results we present in Section I.1, I.2, III.B, III.C, IV.A and IV.B and Appendix C and D and Figures 9, 10, 11, 13. To calculate the graphical corrections we extensively use the Python package ``restflo... |
Jan 16, 2024 - Institute for Modelling and Simulation of Biomechanical Systems
Nadler, Tobias; Wolfen, Simon; Häufle, Daniel F. B.; Schmitt, Syn, 2024, "Technical specifications and details of the muscle-driven biorobotic arm ATARO", https://doi.org/10.18419/darus-3813, DaRUS, V1
ATARO is a bio-inspired arm robot with two degrees of freedom. Five artificial muscle-spring units (MSUs) are used for actuation. The MSUs, each consisting of a pneumatic artificial muscle (PAM) and a spring in series, mimic the characteristics of the human muscle-tendon complex.... |
Jan 11, 2024 - Projects without PN Affiliation
Magiera, Jim M., 2024, "Replication Data for: Constraint-aware neural networks for Riemann problems", https://doi.org/10.18419/darus-3869, DaRUS, V1
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... |
Dec 15, 2023 - PN 2-3B
Santana Chacon, Pablo Filipe; Hammer, Maria; Wochner, Isabell; Walter, Johannes R.; Schmitt, Syn, 2023, "Replication Data for: A physiologically enhanced muscle spindle model: using a Hill-type model for extrafusal fibers as template for intrafusal fibers", https://doi.org/10.18419/darus-3796, DaRUS, V1
This code/data allows you reproduce the results of the paper: "A physiologically enhanced muscle spindle model: using a Hill-type model for extrafusal fibers as template for intrafusal fibers" by P. F. S. Chacon, M. Hammer, I. Wochner, J. R. Walter and S. Schmitt. Always cite the... |
Pollinger, Theresa, 2023, "Replication Data for: Leveraging the compute power of two HPC systems for higher-dimensional grid-based simulations with the widely-distributed sparse grid combination technique", https://doi.org/10.18419/darus-3393, DaRUS, V1
We ran different fractions of the combination technique scenario described in the publication, also widely-distributed between the two machines SuperMUC-NG (file suffix `_ng`) and Hawk (file suffix `_hawk`). The dataset contains input files to generate the scenarios on the respec... |
Apr 20, 2023 - Publications
Pollinger, Theresa, 2022, "Replication Data for: A mass-conserving sparse grid combination technique with biorthogonal hierarchical basis functions for kinetic simulations", https://doi.org/10.18419/darus-2790, DaRUS, V2
Replication data for advection, Landau damping, and two-stream instability experiments with mass-conserving basis functions (vs hat functions) in the combination technique. The simulations are based on the DisCoTec and SeLaLib codes. If you want to re-generate the numerical data,... |
Dec 16, 2022 - demoa
Wochner, Isabell; Schmitt, Syn, 2022, "MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks", https://doi.org/10.18419/darus-3268, DaRUS, V1
This code allows you reproduce the optimal control and model predictive control results of the paper: "Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks" by Isabell Wochner, Pierre Schumacher, Georg Martius, Dieter Büchler, Syn Schmitt an... |
Oct 28, 2022 - ThermoML
Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Self-diffusion coefficients of simulated aqueous glycerol mixtures", https://doi.org/10.18419/darus-3115, DaRUS, V1
In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experi... |
Oct 28, 2022 - ThermoML
Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Densities of simulated aqueous methanol mixtures", https://doi.org/10.18419/darus-3112, DaRUS, V1
In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experi... |
Oct 28, 2022 - ThermoML
Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Self-diffusion coefficients of simulated aqueous methanol mixtures", https://doi.org/10.18419/darus-3114, DaRUS, V1
In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experi... |
