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License: CC BY 4.0

1 to 10 of 737 Results

Datasets: 100 Heat Pumps + Synthetic Permeability Fields, Simulation - Raw, 3 + 1 Data Points 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...
Datasets: 100 Heat Pumps + Real Permeability Fields, Simulation - Raw, 4 + 1 Data Points 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...
Trained Vanilla Models on Synthetic Permeability Fields, 101 Data Points 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.
Trained Models on Real Permeability Fields, 4+1 Data Points 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...
Trained Models on Synthetic Permeability Fields, 3+1 Data Points 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...
Datasets: 100 Heat Pumps + Synthetic Permeability Fields, Simulation - Raw, 101 Data Points 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...
Data for: Intermittent flow paths in biofilms grown in a microfluidic channel Jul 2, 2025 - Publication: Intermittent flow paths in biofilms grown in a microfluidic channel Bozkurt, Kerem; Lohrmann, Christoph; Weinhardt, Felix; Hanke, Daniel; Hopp, Raphael; Gerlach, Robin; Holm, Christian; Class, Holger, 2025, "Data for: Intermittent flow paths in biofilms grown in a microfluidic channel", https://doi.org/10.18419/DARUS-4314, DaRUS, V1 Content: This dataset includes images of 10 different biofilm growth experiments to observe intermittent flow paths in a microfluidic channel. All images taken by optical microscopy per five minutes. The experiments took in avarage 4-5 days. The published data is the raw images of the experiments. The images names were related to the timestamps as...
Supplemental data for "Spectral Normalization and Voigt–Reuss net: A universal approach to microstructure‐property forecasting with physical guarantees" 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...
Experiment Video for Model Predictive Path-Following Control of a Quadrotor 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...
Data from the MetSpec Experiments Jun 24, 2025 - HEFDiG Loehle, Stefan; Leiser, David; Toth, Juraj; Matlovič, Pavol; Pisarčíková, Adriana; Vaubaillon, Jeremie; Grigat, Felix; Eberhart, Martin; Hufgard, Fabian; Ravichandran, Ranjith; Poloni, Erik; Hörner, Igor; Dürnhofer, Christian; Delahaie, Sara; Ferrière, Ludovic; Sylvian Rommeluere; Rambaux, Nicolas, 2025, "Data from the MetSpec Experiments", https://doi.org/10.18419/DARUS-5100, DaRUS, V1, UNF:6:uEwTKTW4z6RxtYl8SAGfaQ== [fileUNF] Data from ground testing of meteorites. It comprises video, still frames and spectroscopic data from 31 experiments examining 28 meteorite samples of various origins. The three experimental campaigns took place between 2020 and 2022.

Datasets: 100 Heat Pumps + Synthetic Permeability Fields, Simulation - Raw, 3 + 1 Data Points

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...

Datasets: 100 Heat Pumps + Real Permeability Fields, Simulation - Raw, 4 + 1 Data Points

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...

Trained Vanilla Models on Synthetic Permeability Fields, 101 Data Points

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.

Trained Models on Real Permeability Fields, 4+1 Data Points

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...

Trained Models on Synthetic Permeability Fields, 3+1 Data Points

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...

Datasets: 100 Heat Pumps + Synthetic Permeability Fields, Simulation - Raw, 101 Data Points

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...

Data for: Intermittent flow paths in biofilms grown in a microfluidic channel

Jul 2, 2025 - Publication: Intermittent flow paths in biofilms grown in a microfluidic channel

Bozkurt, Kerem; Lohrmann, Christoph; Weinhardt, Felix; Hanke, Daniel; Hopp, Raphael; Gerlach, Robin; Holm, Christian; Class, Holger, 2025, "Data for: Intermittent flow paths in biofilms grown in a microfluidic channel", https://doi.org/10.18419/DARUS-4314, DaRUS, V1

Content: This dataset includes images of 10 different biofilm growth experiments to observe intermittent flow paths in a microfluidic channel. All images taken by optical microscopy per five minutes. The experiments took in avarage 4-5 days. The published data is the raw images of the experiments. The images names were related to the timestamps as...

Supplemental data for "Spectral Normalization and Voigt–Reuss net: A universal approach to microstructure‐property forecasting with physical guarantees"

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...

Experiment Video for Model Predictive Path-Following Control of a Quadrotor

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...

Data from the MetSpec Experiments

Jun 24, 2025 - HEFDiG

Loehle, Stefan; Leiser, David; Toth, Juraj; Matlovič, Pavol; Pisarčíková, Adriana; Vaubaillon, Jeremie; Grigat, Felix; Eberhart, Martin; Hufgard, Fabian; Ravichandran, Ranjith; Poloni, Erik; Hörner, Igor; Dürnhofer, Christian; Delahaie, Sara; Ferrière, Ludovic; Sylvian Rommeluere; Rambaux, Nicolas, 2025, "Data from the MetSpec Experiments", https://doi.org/10.18419/DARUS-5100, DaRUS, V1, UNF:6:uEwTKTW4z6RxtYl8SAGfaQ== [fileUNF]

Data from ground testing of meteorites. It comprises video, still frames and spectroscopic data from 31 experiments examining 28 meteorite samples of various origins. The three experimental campaigns took place between 2020 and 2022.

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