21 to 30 of 102 Results
Oct 26, 2022 - Projects without PN Affiliation
Davis, Kyle; Schulte, Miriam, 2022, "Replication Data for: Geothermal-ML - predicting thermal plume from groundwater heat pumps", https://doi.org/10.18419/darus-3184, DaRUS, V1
This dataset provides all python3 code necessary to train convolutional neural networks built with pyTorch, as well as the data to train the networks. A README file is provided with instructions for accessing the training data, viewing the alread computed models, and all software... |
Mar 29, 2022 - PN 6
Holzmüller, David, 2022, "Replication Data for: Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework", https://doi.org/10.18419/darus-1779, DaRUS, V1, UNF:6:aIyuHfDcWPT9LJvtkCge9w== [fileUNF]
This dataset contains supplementary code for the paper Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework. The code is also provided on GitHub. Here, we additionally provide the runtime measurement data generated by the code, which... |
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... |
Mar 7, 2024 - Usability and Sustainability of Simulation Software
Kschidock, Helena, 2024, "Replication Data for: Development of a framework for point-particle tracking", https://doi.org/10.18419/darus-3760, DaRUS, V1
This dataset contains a custom build for Altair's simulation software ultraFluidX and the input files used in the Master Thesis 'Development of an Euler-Lagrangian framework for point-particle tracking to enable efficient multiscale simulations of complex flows', submitted by Hel... |
Jul 1, 2023 - Usability and Sustainability of Simulation Software
Schrader, Timo Pierre; Schneider, David; Uekermann, Benjamin, 2023, "Replication Data for: Data-Parallel Radial-Basis Function Interpolation in preCICE", https://doi.org/10.18419/darus-3574, DaRUS, V1
This dataset contains setup and result files for the performance measurements presented in Schneider et al. "Data-Parallel Radial-Basis Function Interpolation in preCICE". Furthermore, it contains the used snapshot of preCICE, ASTE, and Gingko. See the README for information on h... |
Feb 26, 2024 - Modelling, Simulation and Optimization for Agonist-Antagonist Myoneural Interface Surgeries
Homs Pons, Carme; Lautenschlager, Robin, 2024, "Replication Data for: Coupled Simulations and Parameter Inversion for Neural System and Electrophysiological Muscle Models", https://doi.org/10.18419/darus-4031, DaRUS, V1
This dataset allows to reproduce the results from the paper "Coupled Simulations and Parameter Inversion for Neural System and Electrophysiological Muscle Models" submitted to GAMM Mitteilungen in September 2023. Find more information about the structure of the dataset and the st... |
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 presen... |
Tkachev, Gleb, 2021, "Replication Data for: "S4: Self-Supervised learning of Spatiotemporal Similarity"", https://doi.org/10.18419/darus-2174, DaRUS, V1
We train a self-supervised siamese model that enables querying for similar behavior on spatiotemporal volumes. Here we provide the code and data needed to reproduce the representative figures of the paper. See the notes and the included readme file for details. |
Reiser, Philipp; Aguilar, Javier Enrique; Guthke, Anneli; Bürkner, Paul-Christian, 2024, "Replication Code for: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference", https://doi.org/10.18419/darus-4093, DaRUS, V1
This code allows to replicate key experiments from our paper: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference. For further details, please refer to the README.md. |
Keim, Leon; Class, Holger, 2024, "Replication Code for: Rayleigh invariance allows the estimation of effective CO2 fluxes due to convective dissolution into water-filled fractures", https://doi.org/10.18419/darus-4089, DaRUS, V1
This dataset consists of software code associated with the publication titled "Rayleigh Invariance Enables Estimation of Effective CO2 Fluxes Resulting from Convective Dissolution in Water-Filled Fractures." It includes a Dockerimage that contains the precompiled code for immedia... |
