171 to 180 of 293 Results
Oct 28, 2022 - FAIR Fluids
Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Densities of experimental aqueous methanol mixtures", https://doi.org/10.18419/DARUS-3116, DaRUS, V1
In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol... |
Oct 28, 2022 - FAIR Fluids
Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Densities of experimental aqueous glycerol mixtures", https://doi.org/10.18419/DARUS-3117, DaRUS, V1
In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol... |
Oct 28, 2022 - FAIR Fluids
Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Tracer-diffusion coefficients of experimental aqueous methanol mixtures", https://doi.org/10.18419/DARUS-3118, DaRUS, V1
In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol... |
Oct 28, 2022 - FAIR Fluids
Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Self-diffusion coefficients of experimental aqueous glycerol mixtures", https://doi.org/10.18419/DARUS-3119, DaRUS, V1
In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol... |
Oct 28, 2022 - FAIR Fluids
Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Viscosities of experimental aqueous methanol mixtures", https://doi.org/10.18419/DARUS-3120, DaRUS, V1
In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol... |
Oct 28, 2022 - FAIR Fluids
Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Viscosities of experimental aqueous glycerol mixtures", https://doi.org/10.18419/DARUS-3121, DaRUS, V1
In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol... |
Oct 28, 2022 - FAIR Fluids
Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Densities of simulated aqueous glycerol mixtures", https://doi.org/10.18419/DARUS-3113, DaRUS, V1
In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol... |
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 dependency versions. |
Oct 26, 2022 - Projects without PN Affiliation
Davis, Kyle; Schulte, Miriam, 2022, "COM-4 model to replicate simulation results for the GEO.KW project", https://doi.org/10.18419/DARUS-3185, DaRUS, V1
This data repository contains the COM-4 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs simulation setup, spack build environment and spack build mirror to replicate the software build environment. A README file is provided, explaining the spack building procedure and running the simulation. |
Oct 26, 2022 - Projects without PN Affiliation
Davis, Kyle; Schulte, Miriam, 2022, "REG-30 model to replicate simulation results for the GEO.KW project", https://doi.org/10.18419/DARUS-3195, DaRUS, V1
This data repository contains the REG-30 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs software and simulation setup. Instructions for building the spack environment and running the simulation are provided in the README. |
