DaRUS

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This is the Data Repository of the University of Stuttgart.

SFB 1313 "Interface-Driven Multi-Field Processes in Porous Media"

SFB 1333 "Molecular heterogeneous catalysis in confined geometries"

Institute of Biochemistry

Institute of Applied Mechanics (MIB)

Institute of Thermodynamics and Thermal Process Engineering

Stuttgart Center for Simulation Science (SC SimTech)

Cluster of Excellence Integrative Computational Design and Construction for Transformative Architecture (EXC IntCDC)

SFB/Transregio 161 "Quantitative Methods for Visual Computing"

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71 to 80 of 3,058 Results

Replication Data for: Improved super-resolution reconstruction of turbulent flows with spectral loss function Apr 13, 2026 - Institute for Reactive Flows (IRST) Cheng, Ruyue, 2026, "Replication Data for: Improved super-resolution reconstruction of turbulent flows with spectral loss function", https://doi.org/10.18419/DARUS-5497, DaRUS, V1 This repository contains the data and python code to build/train/test the super-resolution model (deep neural network). Three tar.gz files are provided: code: contains the code to build/train/test super-resolution models caseSettings: contains the configuration files for the training and testing datasets: contains all the training/validation/test d...
Replication Data for: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software Apr 9, 2026 - Usability and Sustainability of Simulation Software Vinnitchenko, Niklas; Desai, Ishaan; Rodenberg, Benjamin; Hildebrand, Philip; Humbert, Angelika; Uekermann, Benjamin, 2026, "Replication Data for: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software", https://doi.org/10.18419/DARUS-5847, DaRUS, V1 This dataset contains software and result files for the publication: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software in the journal SoftwareX.
2025: Copilot for constraint-driven generation of architectural design evaluations and suggestions(Universität Stuttgart) Apr 8, 2026ITECH thesis Building design, engineering, and construction are highly regulated, requiring time-consuming checks and costly expert consultations, slowing design iterations and worsening the housing crisis. Architects often navigate conflicting advice from specialists, leading to revisions and delays. Occasionally, issues emerge after construction, causing cost...
ITECH thesis(Universität Stuttgart) Apr 8, 2026Institute of Computational Design and Construction This dataverse contains research data that was produced during master theses within the Integrative Technologies and Architectural Design Research (ITECH) program.
Three-Dimensional Shock-Drop Interaction Apr 8, 2026 - NRG DROPIT Dataverse Mossier, Pascal; Appel, Daniel, 2026, "Three-Dimensional Shock-Drop Interaction", https://doi.org/10.18419/DARUS-5848, DaRUS, V1 High-order sharp-interface simulation of a three-dimensional Ma=2.4 shock-droplet interaction, using an hp-adaptive level-set ghost-fluid method. Dataset corresponds to dimensionless time t=7.0 according to the setup described in section 5.5 of Mossier et al. (doi: 10.1007/s10915-023-02363-7) and serves to reproduce Fig. 31 therein.
Surface Tension-Driven Droplet Oscillation Apr 8, 2026 - NRG DROPIT Dataverse Zeifang, Jonas; Travnicek, Amalía, 2026, "Surface Tension-Driven Droplet Oscillation", https://doi.org/10.18419/DARUS-5850, DaRUS, V1 High-order sharp-interface simulation of a three-dimensional surface tension-driven droplet oscillation at Ma=0.005. Dataset provides fluid and level-set solution at timestamp t=1 according to the setup described in section 4.2 of Zeifang et al. (doi: 10.1007/s42967-021-00137-2) and serves to reproduce Fig. 7 therein.
Supplementary material to 'Machine Learning Prediction of Henry Coefficients of Polar and Nonpolar Gases in Covalent Organic Frameworks: Effects of Interlayer Shifts and Functionalization' Apr 7, 2026 - Institute of Thermodynamics and Thermal Process Engineering Nurhuda, Maryam; Teh, Tiong Wei; Packwood, Daniel; Hansen, Niels, 2026, "Supplementary material to 'Machine Learning Prediction of Henry Coefficients of Polar and Nonpolar Gases in Covalent Organic Frameworks: Effects of Interlayer Shifts and Functionalization'", https://doi.org/10.18419/DARUS-5781, DaRUS, V1, UNF:6:VGCNG6AIwbpDFjn2nWVA4w== [fileUNF] Electronic supplementary materials for the publication stated below. Henry coefficients are calculated by Widom insertion (in RASPA 2.0.47). Contents: - Henry coefficients (CSV) - CoRE-COF original, slipped, and functionalized files (CIF) - RASPA input files.
Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations Apr 7, 2026 - Coarse-grained non-equilibrium dynamics with generative machine learning Egenlauf, Patrick; Březinová, Iva; Andergassen, Sabine; Klopotek, Miriam, 2026, "Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations", https://doi.org/10.18419/DARUS-5613, DaRUS, V3 This dataset contains all relevant data to reproduce the results of the paper titled "Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations". It contains the exact time series data of the two-particle reduced density matrix (2RDM) for each parameter configuration of the parameter scan, with...
NRG DROPIT Dataverse(Universität Stuttgart) Apr 2, 2026Numerics Research Group Exemplary output data of high-order sharp-interface simulations of compressible multiphase flows, produced in the course of DFG-GRK 2160 "DROPIT"
SVS: SWOT Validation Set for Global River Discharge Evaluation Apr 2, 2026 - Institute of Geodesy Saemian, Peyman; Tourian, Mohammad J., 2026, "SVS: SWOT Validation Set for Global River Discharge Evaluation", https://doi.org/10.18419/DARUS-5843, DaRUS, V1 The SWOT Validation Set (SVS) is a global gauge-based dataset created for validating river discharge estimates derived from the SWOT mission. It provides discharge time series, gauge metadata, information on the matching of gauges to SWORD river reaches, and auxiliary attributes needed for systematic comparison between satellite-based and in situ d...

Replication Data for: Improved super-resolution reconstruction of turbulent flows with spectral loss function

Apr 13, 2026 - Institute for Reactive Flows (IRST)

Cheng, Ruyue, 2026, "Replication Data for: Improved super-resolution reconstruction of turbulent flows with spectral loss function", https://doi.org/10.18419/DARUS-5497, DaRUS, V1

This repository contains the data and python code to build/train/test the super-resolution model (deep neural network). Three tar.gz files are provided: code: contains the code to build/train/test super-resolution models caseSettings: contains the configuration files for the training and testing datasets: contains all the training/validation/test d...

Replication Data for: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software

Apr 9, 2026 - Usability and Sustainability of Simulation Software

Vinnitchenko, Niklas; Desai, Ishaan; Rodenberg, Benjamin; Hildebrand, Philip; Humbert, Angelika; Uekermann, Benjamin, 2026, "Replication Data for: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software", https://doi.org/10.18419/DARUS-5847, DaRUS, V1

This dataset contains software and result files for the publication: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software in the journal SoftwareX.

2025: Copilot for constraint-driven generation of architectural design evaluations and suggestions(Universität Stuttgart)

Apr 8, 2026ITECH thesis

Building design, engineering, and construction are highly regulated, requiring time-consuming checks and costly expert consultations, slowing design iterations and worsening the housing crisis. Architects often navigate conflicting advice from specialists, leading to revisions and delays. Occasionally, issues emerge after construction, causing cost...

ITECH thesis(Universität Stuttgart)

Apr 8, 2026Institute of Computational Design and Construction

This dataverse contains research data that was produced during master theses within the Integrative Technologies and Architectural Design Research (ITECH) program.

Three-Dimensional Shock-Drop Interaction

Apr 8, 2026 - NRG DROPIT Dataverse

Mossier, Pascal; Appel, Daniel, 2026, "Three-Dimensional Shock-Drop Interaction", https://doi.org/10.18419/DARUS-5848, DaRUS, V1

High-order sharp-interface simulation of a three-dimensional Ma=2.4 shock-droplet interaction, using an hp-adaptive level-set ghost-fluid method. Dataset corresponds to dimensionless time t=7.0 according to the setup described in section 5.5 of Mossier et al. (doi: 10.1007/s10915-023-02363-7) and serves to reproduce Fig. 31 therein.

Surface Tension-Driven Droplet Oscillation

Apr 8, 2026 - NRG DROPIT Dataverse

Zeifang, Jonas; Travnicek, Amalía, 2026, "Surface Tension-Driven Droplet Oscillation", https://doi.org/10.18419/DARUS-5850, DaRUS, V1

High-order sharp-interface simulation of a three-dimensional surface tension-driven droplet oscillation at Ma=0.005. Dataset provides fluid and level-set solution at timestamp t=1 according to the setup described in section 4.2 of Zeifang et al. (doi: 10.1007/s42967-021-00137-2) and serves to reproduce Fig. 7 therein.

Supplementary material to 'Machine Learning Prediction of Henry Coefficients of Polar and Nonpolar Gases in Covalent Organic Frameworks: Effects of Interlayer Shifts and Functionalization'

Apr 7, 2026 - Institute of Thermodynamics and Thermal Process Engineering

Nurhuda, Maryam; Teh, Tiong Wei; Packwood, Daniel; Hansen, Niels, 2026, "Supplementary material to 'Machine Learning Prediction of Henry Coefficients of Polar and Nonpolar Gases in Covalent Organic Frameworks: Effects of Interlayer Shifts and Functionalization'", https://doi.org/10.18419/DARUS-5781, DaRUS, V1, UNF:6:VGCNG6AIwbpDFjn2nWVA4w== [fileUNF]

Electronic supplementary materials for the publication stated below. Henry coefficients are calculated by Widom insertion (in RASPA 2.0.47). Contents: - Henry coefficients (CSV) - CoRE-COF original, slipped, and functionalized files (CIF) - RASPA input files.

Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations

Apr 7, 2026 - Coarse-grained non-equilibrium dynamics with generative machine learning

Egenlauf, Patrick; Březinová, Iva; Andergassen, Sabine; Klopotek, Miriam, 2026, "Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations", https://doi.org/10.18419/DARUS-5613, DaRUS, V3

This dataset contains all relevant data to reproduce the results of the paper titled "Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations". It contains the exact time series data of the two-particle reduced density matrix (2RDM) for each parameter configuration of the parameter scan, with...

NRG DROPIT Dataverse(Universität Stuttgart)

Apr 2, 2026Numerics Research Group

Exemplary output data of high-order sharp-interface simulations of compressible multiphase flows, produced in the course of DFG-GRK 2160 "DROPIT"

SVS: SWOT Validation Set for Global River Discharge Evaluation

Apr 2, 2026 - Institute of Geodesy

Saemian, Peyman; Tourian, Mohammad J., 2026, "SVS: SWOT Validation Set for Global River Discharge Evaluation", https://doi.org/10.18419/DARUS-5843, DaRUS, V1

The SWOT Validation Set (SVS) is a global gauge-based dataset created for validating river discharge estimates derived from the SWOT mission. It provides discharge time series, gauge metadata, information on the matching of gauges to SWORD river reaches, and auxiliary attributes needed for systematic comparison between satellite-based and in situ d...

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