1 to 10 of 217 Results
Neubauer, Felix, 2025, "Replication Data for: AI-assisted JSON Schema Creation and Mapping", https://doi.org/10.18419/DARUS-5157, DaRUS, V1, UNF:6:cu/nriFjeIsGtYAoB7K7fw== [fileUNF]
The steps and sources of the application example from the paper + the JSONata instructions for the LLM. Recommended: download all files and open the README.md with a markdown editor/viewer. The README.md document shows the steps performed in the application example and also corresponding screenshots and input and output documents. The screenshots a... |
Jul 4, 2025 - Few-Shot Learning by Explicit Physics Integration: An Application to Groundwater Heat Transport
Pelzer, Julia, 2024, "Datasets: 100 Heat Pumps + Synthetic Permeability Fields, Simulation - Raw, 3 + 1 Data Points", https://doi.org/10.18419/DARUS-4156, DaRUS, V2
This data set serves as training and testing data for modelling the temperature field emanating from open loop groundwater heat pumps (100, randomly placed). It is simulated with Pflotran and saved in h5 format. It contains 3 + 1 data points, each consisting of one simulation run until a quasi-steady state is reached. Each data point measures 12.8... |
Jul 4, 2025 - Few-Shot Learning by Explicit Physics Integration: An Application to Groundwater Heat Transport
Pelzer, Julia, 2025, "Datasets: 100 Heat Pumps + Real Permeability Fields, Simulation - Raw, 4 + 1 Data Points", https://doi.org/10.18419/DARUS-5065, DaRUS, V1
This data set serves as training and testing data for modelling the temperature field emanating from open loop groundwater heat pumps (100, randomly placed). It is simulated with Pflotran and saved in h5 format. It contains 4 + 1 data points, each consisting of one simulation run until a quasi-steady state is reached. Each data point measures 12.8... |
Jul 4, 2025 - Few-Shot Learning by Explicit Physics Integration: An Application to Groundwater Heat Transport
Pelzer, Julia; Verburg, Corné, 2025, "Trained Vanilla Models on Synthetic Permeability Fields, 101 Data Points", https://doi.org/10.18419/DARUS-5081, DaRUS, V1
Models are trained with [git: DDUNet] on 101 data points (dp). Both, vanilla UNet and DDU-Net, can be applied directly end-to-end. For inference follow the guidelines of Heat Plume Prediction to prepare raw data, then apply the models as described in [git: DDUNet]. Based on raw data from https://doi.org/10.18419/darus-5064. |
Jul 4, 2025 - Few-Shot Learning by Explicit Physics Integration: An Application to Groundwater Heat Transport
Pelzer, Julia, 2025, "Trained Models on Real Permeability Fields, 4+1 Data Points", https://doi.org/10.18419/DARUS-5082, DaRUS, V1
Models are trained with Heat Plume Prediction on 4 data points (dp). Steps 1 and 3 of LGCNN (Local Global Convolutional Neural Network) are separate, step 2 is a numerical solver that does not require any trained model. For inference follow the guidelines of Heat Plume Prediction and applied all 3 steps/models sequentially to your input data. Based... |
Jul 4, 2025 - Few-Shot Learning by Explicit Physics Integration: An Application to Groundwater Heat Transport
Pelzer, Julia, 2025, "Trained Models on Synthetic Permeability Fields, 3+1 Data Points", https://doi.org/10.18419/DARUS-5080, DaRUS, V1
Models are trained with Heat Plume Prediction. Steps 1 and 3 of LGCNN (Local Global Convolutional Neural Network) are separate, step 2 is a numerical solver that does not require any trained model. The vanilla UNet can be applied directly end-to-end, just does not give very good results. For inference follow the guidelines of Heat Plume Prediction... |
Jul 4, 2025 - Few-Shot Learning by Explicit Physics Integration: An Application to Groundwater Heat Transport
Pelzer, Julia, 2025, "Datasets: 100 Heat Pumps + Synthetic Permeability Fields, Simulation - Raw, 101 Data Points", https://doi.org/10.18419/DARUS-5064, DaRUS, V1
This data set serves as training and testing data for modelling the temperature field emanating from open loop groundwater heat pumps (100, randomly placed). It is simulated with Pflotran and saved in h5 format. It contains 101 data points, each consisting of one simulation run until a quasi-steady state is reached. Each data point measures 12.8 km... |
Jun 30, 2025 - Data Analytics in Engineering
Keshav, Sanath; Herb, Julius; Fritzen, Felix, 2025, "Supplemental data for "Spectral Normalization and Voigt–Reuss net: A universal approach to microstructure‐property forecasting with physical guarantees"", https://doi.org/10.18419/DARUS-5120, DaRUS, V1
This repository contains supplemental data for the article "Spectral Normalization and Voigt-Reuss net: A universal approach to microstructure‐property forecasting with physical guarantees", accepted for publication in GAMM-Mitteilungen by Sanath Keshav, Julius Herb, and Felix Fritzen [1]. The data contained in this DaRUS repository acts as an exte... |
Jun 26, 2025 - Institute of Engineering and Computational Mechanics
Leprich, David; Rosenfelder, Mario; Hermle, Mario; Chen, Jingshan; Eberhard, Peter, 2025, "Experiment Video for Model Predictive Path-Following Control of a Quadrotor", https://doi.org/10.18419/DARUS-5099, DaRUS, V1
The provided video shows an experimental result of a Model Predictive Path-Following Controller (MPPFC) applied to a Crazyflie Quadrotor. The objective is to fly along the lemniscate path. The lemniscate is defined as a time-independent geometric curve, parameterized by a so-called timing law. Based on this, the MPPFC generates a dynamically feasib... |
Jun 23, 2025 - PN 7-6
Kneifl, Jonas; Rettberg, Johannes; Fehr, Jörg, 2024, "Coupled thermo-mechanical simulation results of a finite element discbrake", https://doi.org/10.18419/DARUS-4418, DaRUS, V3
Simulation Results of a Finite Element Discbrake This dataset contains simulation results from a finite element (FE) model of a heated disc brake, represented in two configurations: Simple Discbrake A lower-resolution FE model featuring a single heated area. 1 layer, 60 elements, 146 nodes 7 degrees of freedom (DOFs) per node, 998 DOFs in total Dis... |
