1 to 6 of 6 Results
Apr 9, 2024 - Surrogate models for groundwater flow simulations
Pelzer, Julia, 2024, "Raw Simulation Datasets for Extending Heat Plumes", https://doi.org/10.18419/darus-4133, DaRUS, V1
These data sets serve as training and testing data for modelling the extension of temperature field emanating from one groundwater heat pump. There are simulated with Pflotran and saved in h5 format. The data set for training is called "dataset_medium_k_3e-10_1000dp". It contains... |
Apr 2, 2024 - Surrogate models for groundwater flow simulations
Pelzer, Julia, 2024, "Models and Prepared Datasets for the Second Stage", https://doi.org/10.18419/darus-3689, DaRUS, V1
Models trained with Heat Plume Prediction and datasets prepared with Heat Plume Prediction into reasonable format + normalization etc, used for training these models. Last relevant git commit: 5d6c5eae5b00e438. Based on raw data from doi:darus-3651 and doi:darus-3652. |
Apr 2, 2024 - Surrogate models for groundwater flow simulations
Pelzer, Julia, 2024, "Models and Prepared Datasets for the First Stage", https://doi.org/10.18419/darus-3690, DaRUS, V1
Models trained with Heat Plume Prediction and datasets prepared with Heat Plume Prediction into reasonable format + normalization etc, used for training these models. Last relevant git commit: 5d6c5eae5b00e438. Based on raw data from doi:10.18419/darus-3649 and doi:10.18419/darus... |
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... |
Feb 22, 2024
The AMI is a limb amputation technique which aims to maintain the mechanical and neural feedback between agonist and antagonist muscle. We aim to develop a platform for in silico analysis which can provide insight to surgeons. For that we combine detailed multi-physics multi-scal... |
Jan 11, 2024
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... |