211 to 220 of 376 Results
Jun 20, 2023 - Usability and Sustainability of Simulation Software
Willeke, Leonard; Schneider, David; Uekermann, Benjamin, 2023, "Reproduction data for: A preCICE-FMI Runner to Couple FMUs to PDE-Based Simulations", https://doi.org/10.18419/DARUS-3549, DaRUS, V1
Input files and results for two simulation examples using the preCICE-FMI runner as described in "A preCICE-FMI Runner to Couple FMUs to PDE-Based Simulations". First, the simulation of a partitioned mass-spring oscillator system is considered. All model equations are based on ODEs. The coupled simulation can be executed with a FMU models, a Python... |
Jun 12, 2023PN 3
We aim to use first-principles calculations at finite temperatures in combination with machine learning (ML) techniques to derive an accurate picture of hydrogen embrittlement in Ni-based superalloys. The ML-based interatomic potential will allow for the determination of the temperature dependent antiphase boundary energy (APB energy) for γ' precip... |
Jun 7, 2023 - Usability and Sustainability of Simulation Software
Willeke, Leonard, 2023, "Replication Data for: A preCICE-FMI Runner to couple controller models to PDEs", https://doi.org/10.18419/DARUS-3408, DaRUS, V1
A preCICE-FMI Runner was developed during the Master's Thesis "A preCICE-FMI Runner to couple controller models to PDEs". It couples models using the FMI standard with other simulation programs via the coupling library preCICE. This data set contains the code and casefiles presented in the thesis, as well as instructions to replicate the results. F... |
Jun 6, 2023 - Projects without PN Affiliation
Herkert, Robin, 2023, "Replication Code for: Randomized Symplectic Model Order Reduction for Hamiltonian Systems", https://doi.org/10.18419/DARUS-3519, DaRUS, V1
This dataset includes the code to reproduce the results from the paper titled "Randomized Symplectic Model Order Reduction for Hamiltonian Systems". In this paper randomized symplectic basis generation techniques are introduced. The numerical experiments where error decay rates and runtimes from the randomized methods and the classical, non-randomi... |
Jun 5, 2023 - Usability and Sustainability of Simulation Software
Schrader, Timo Pierre, 2023, "Replication Data for: Efficient Application of Accelerator Cards for the Coupling Library preCICE", https://doi.org/10.18419/DARUS-3404, DaRUS, V1
This dataset contains all testcase setup files and result files for the measurements presented in the Master's thesis with the title "Efficient Application of Accelerator Cards for the Coupling Library preCICE" (Author: Timo Pierre Schrader). Furthermore, it contains the version of preCICE used throughout this thesis. The thesis revolves around GPU... |
May 26, 2023 - Materials Design
Gubaev, Konstantin; Zaverkin, Viktor; Srinivasan, Prashanth; Duff, Andrew; Kästner, Johannes; Grabowski, Blazej, 2023, "Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems", https://doi.org/10.18419/DARUS-3516, DaRUS, V1
Data for the publication "Performance of two complementary machine-learned potentials in modelling chemically complex systems", npj. Comp. Mat. This data set contains the datasets of structures in cfg and npz formats INCAR file which was used for VASP calculations python script for reading npz format These are essentially the 2-, 3-, and 4-componen... |
May 25, 2023 - Data and Code for: Meta-Uncertainty in Bayesian Model Comparison
Schmitt, Marvin, 2023, "Replication Code for: Meta-Uncertainty in Bayesian Model Comparison", https://doi.org/10.18419/DARUS-3514, DaRUS, V1, UNF:6:zUDr3KGdcaDCy+jFtcz8lA== [fileUNF]
This dataverse contains the code for the paper Meta-Uncertainty in Bayesian Model Comparison: https://doi.org/10.48550/arXiv.2210.07278 Note that the R code is structured as a package, thus requiring a local installation with subsequent loading via library(MetaUncertaintyPaper). The experiments from the accompanying paper (see below) are implemente... |
