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Subject: Earth and Environmental Sciences Subject: Physics Subject: Computer and Information Science

1 to 10 of 13 Results

PDEBench Datasets Feb 13, 2024 - SciML PDE Benchmark Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Datasets", https://doi.org/10.18419/darus-2986, DaRUS, V8 This dataset contains benchmark data, generated with numerical simulation based on different PDEs, namely 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D shallow water equation. This...
PDEBench Pretrained Models Nov 30, 2023 - SciML PDE Benchmark Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Pretrained Models", https://doi.org/10.18419/darus-2987, DaRUS, V2 This dataset contains the pretrained baseline models, namely FNO, U-Net, and PINN. These models are trained on different PDEs, such as 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D...
micro-XRCT data sets and in situ measured ultrasonic wave propagation of pre-stressed monodisperse rubber and glass particle mixtures with 10%, 20%, and 30% volume rubber content: samples 2 and 3 May 4, 2023 - Publication: Particulate systems Ruf, Matthias; Taghizadeh, Kianoosh; Steeb, Holger, 2023, "micro-XRCT data sets and in situ measured ultrasonic wave propagation of pre-stressed monodisperse rubber and glass particle mixtures with 10%, 20%, and 30% volume rubber content: samples 2 and 3", https://doi.org/10.18419/darus-3437, DaRUS, V1, UNF:6:LyvQPm+lMHvJ9Z4neyxihA== [fileUNF] This dataset contains 12 micro X-ray Computed Tomography (micro-XRCT) data sets from scans of cylindrical particulate mixture samples (diameter 80 mm; unloaded height 80 mm) under different uniaxial compression loads. The samples consist of monodisperse stiff (glass) and soft (ru...
micro-XRCT data sets and in situ measured ultrasonic wave propagation of pre-stressed monodisperse rubber and glass particle mixtures with 10%, 20%, 40%, and 60% volume rubber content: sample 1 May 4, 2023 - Publication: Particulate systems Ruf, Matthias; Taghizadeh, Kianoosh; Steeb, Holger, 2023, "micro-XRCT data sets and in situ measured ultrasonic wave propagation of pre-stressed monodisperse rubber and glass particle mixtures with 10%, 20%, 40%, and 60% volume rubber content: sample 1", https://doi.org/10.18419/darus-3436, DaRUS, V1, UNF:6:B6SNTx6Co9kvBdKrEWyCwA== [fileUNF] This dataset contains 8 micro X-ray Computed Tomography (micro-XRCT) data sets from scans of cylindrical particulate mixture samples (diameter 80 mm; unloaded height 80 mm) under different uniaxial compression loads. The samples consist of monodisperse stiff (glass) and soft (rub...
micro-XRCT data sets and in situ measured ultrasonic wave propagation of a pre-stressed monodisperse rubber and glass particle mixture with 50% volume rubber content Sep 26, 2022 - Publication: Particulate systems Ruf, Matthias; Taghizadeh, Kianoosh; Steeb, Holger, 2021, "micro-XRCT data sets and in situ measured ultrasonic wave propagation of a pre-stressed monodisperse rubber and glass particle mixture with 50% volume rubber content", https://doi.org/10.18419/darus-2208, DaRUS, V2, UNF:6:Rf3VjhimtgZ3IVZt0sEaiw== [fileUNF] This dataset contains two micro X-ray Computed Tomography (micro-XRCT) data sets from scans of the identical cylindrical sample (diameter 80 mm; unloaded height 80 mm) under different uniaxial compression loads. The sample consists of monodisperse soft (rubber) and stiff (glass)...
micro-XRCT data sets and in situ measured ultrasonic wave propagation of a pre-stressed monodisperse rubber and glass particle mixture with 30% volume rubber content Sep 26, 2022 - Publication: Particulate systems Ruf, Matthias; Taghizadeh, Kianoosh; Steeb, Holger, 2022, "micro-XRCT data sets and in situ measured ultrasonic wave propagation of a pre-stressed monodisperse rubber and glass particle mixture with 30% volume rubber content", https://doi.org/10.18419/darus-2833, DaRUS, V1, UNF:6:V7YRRp377HBaXdVaRSc6ig== [fileUNF] This dataset contains two micro X-ray Computed Tomography (micro-XRCT) data sets from scans of the identical cylindrical sample (diameter 80 mm; unloaded height 80 mm) under different uniaxial compression loads. The sample consists of monodisperse soft (rubber) and stiff (glass)...
Replication Data for the numerical simulations in: Evaporation-driven density instabilities in saturated porous media Apr 6, 2022 - Density-driven instabilities Schollenberger, Theresa; Helmig, Rainer, 2022, "Replication Data for the numerical simulations in: Evaporation-driven density instabilities in saturated porous media", https://doi.org/10.18419/darus-2578, DaRUS, V1 This dataset contains the raw data of the results of the numerical simulations published in: Carina Bringedal, Theresa Schollenberger, G. J. M. Pieters, C. J. van Duijn and Rainer Helmig. Evaporation-driven density instabilities in saturated porous media. Transport in Porous Medi...
Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Thermal Humid Mechanical Cycle Jun 22, 2021 - Publication: Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling Fauser, Dominik; Steeb, Holger, 2021, "Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Thermal Humid Mechanical Cycle", https://doi.org/10.18419/darus-2023, DaRUS, V1, UNF:6:kJCrJ2myXSEklpfIfr7AfQ== [fileUNF] This data contains a Thermal Humid Mechanical Cycle (THMC) of Shape Memory Polymers (SMP). The SMP is a polyurethane-based Polymer, which is produced from SMP Technologies Inc. The SMP filament were processed with a 3D printer (Ultimaker 3, Ultimaker, Geldermarsen, Netherlands)....
Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Dynamic Mechanical Thermal Humidity Analysis Jun 22, 2021 - Publication: Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling Fauser, Dominik; Steeb, Holger, 2021, "Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Dynamic Mechanical Thermal Humidity Analysis", https://doi.org/10.18419/darus-2021, DaRUS, V1, UNF:6:YC87IXxORCLw3+woYmYT3A== [fileUNF] This data contains iso-thermal and iso-humid shear frequency-sweep measurements of Shape Memory Polymers (SMP). The SMP is a polyurethane-based Polymer, which is produced from SMP Technologies Inc. The SMP filament were processed with a 3D printer (Ultimaker 3, Ultimaker, Gelderm...
Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Diffusion measurements Jun 22, 2021 - Publication: Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling Fauser, Dominik; Kuhn, Moritz; Steeb, Holger, 2021, "Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Diffusion measurements", https://doi.org/10.18419/darus-2024, DaRUS, V1, UNF:6:ig+5CuLNRHaoCQtncwbvWA== [fileUNF] This data contains diffusion measurements of Shape Memory Polymers (SMP) immersed in demineralized water. The SMP is a polyurethane-based Polymer, which is produced from SMP Technologies Inc. The SMP filament were processed with a 3D printer (Ultimaker 3, Ultimaker, Geldermarsen,...

PDEBench Datasets

Feb 13, 2024 - SciML PDE Benchmark

Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Datasets", https://doi.org/10.18419/darus-2986, DaRUS, V8

This dataset contains benchmark data, generated with numerical simulation based on different PDEs, namely 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D shallow water equation. This...

PDEBench Pretrained Models

Nov 30, 2023 - SciML PDE Benchmark

Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Pretrained Models", https://doi.org/10.18419/darus-2987, DaRUS, V2

This dataset contains the pretrained baseline models, namely FNO, U-Net, and PINN. These models are trained on different PDEs, such as 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D...

micro-XRCT data sets and in situ measured ultrasonic wave propagation of pre-stressed monodisperse rubber and glass particle mixtures with 10%, 20%, and 30% volume rubber content: samples 2 and 3

May 4, 2023 - Publication: Particulate systems

Ruf, Matthias; Taghizadeh, Kianoosh; Steeb, Holger, 2023, "micro-XRCT data sets and in situ measured ultrasonic wave propagation of pre-stressed monodisperse rubber and glass particle mixtures with 10%, 20%, and 30% volume rubber content: samples 2 and 3", https://doi.org/10.18419/darus-3437, DaRUS, V1, UNF:6:LyvQPm+lMHvJ9Z4neyxihA== [fileUNF]

This dataset contains 12 micro X-ray Computed Tomography (micro-XRCT) data sets from scans of cylindrical particulate mixture samples (diameter 80 mm; unloaded height 80 mm) under different uniaxial compression loads. The samples consist of monodisperse stiff (glass) and soft (ru...

micro-XRCT data sets and in situ measured ultrasonic wave propagation of pre-stressed monodisperse rubber and glass particle mixtures with 10%, 20%, 40%, and 60% volume rubber content: sample 1

May 4, 2023 - Publication: Particulate systems

Ruf, Matthias; Taghizadeh, Kianoosh; Steeb, Holger, 2023, "micro-XRCT data sets and in situ measured ultrasonic wave propagation of pre-stressed monodisperse rubber and glass particle mixtures with 10%, 20%, 40%, and 60% volume rubber content: sample 1", https://doi.org/10.18419/darus-3436, DaRUS, V1, UNF:6:B6SNTx6Co9kvBdKrEWyCwA== [fileUNF]

This dataset contains 8 micro X-ray Computed Tomography (micro-XRCT) data sets from scans of cylindrical particulate mixture samples (diameter 80 mm; unloaded height 80 mm) under different uniaxial compression loads. The samples consist of monodisperse stiff (glass) and soft (rub...

micro-XRCT data sets and in situ measured ultrasonic wave propagation of a pre-stressed monodisperse rubber and glass particle mixture with 50% volume rubber content

Sep 26, 2022 - Publication: Particulate systems

Ruf, Matthias; Taghizadeh, Kianoosh; Steeb, Holger, 2021, "micro-XRCT data sets and in situ measured ultrasonic wave propagation of a pre-stressed monodisperse rubber and glass particle mixture with 50% volume rubber content", https://doi.org/10.18419/darus-2208, DaRUS, V2, UNF:6:Rf3VjhimtgZ3IVZt0sEaiw== [fileUNF]

This dataset contains two micro X-ray Computed Tomography (micro-XRCT) data sets from scans of the identical cylindrical sample (diameter 80 mm; unloaded height 80 mm) under different uniaxial compression loads. The sample consists of monodisperse soft (rubber) and stiff (glass)...

micro-XRCT data sets and in situ measured ultrasonic wave propagation of a pre-stressed monodisperse rubber and glass particle mixture with 30% volume rubber content

Sep 26, 2022 - Publication: Particulate systems

Ruf, Matthias; Taghizadeh, Kianoosh; Steeb, Holger, 2022, "micro-XRCT data sets and in situ measured ultrasonic wave propagation of a pre-stressed monodisperse rubber and glass particle mixture with 30% volume rubber content", https://doi.org/10.18419/darus-2833, DaRUS, V1, UNF:6:V7YRRp377HBaXdVaRSc6ig== [fileUNF]

Replication Data for the numerical simulations in: Evaporation-driven density instabilities in saturated porous media

Apr 6, 2022 - Density-driven instabilities

Schollenberger, Theresa; Helmig, Rainer, 2022, "Replication Data for the numerical simulations in: Evaporation-driven density instabilities in saturated porous media", https://doi.org/10.18419/darus-2578, DaRUS, V1

This dataset contains the raw data of the results of the numerical simulations published in: Carina Bringedal, Theresa Schollenberger, G. J. M. Pieters, C. J. van Duijn and Rainer Helmig. Evaporation-driven density instabilities in saturated porous media. Transport in Porous Medi...

Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Thermal Humid Mechanical Cycle

Jun 22, 2021 - Publication: Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling

Fauser, Dominik; Steeb, Holger, 2021, "Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Thermal Humid Mechanical Cycle", https://doi.org/10.18419/darus-2023, DaRUS, V1, UNF:6:kJCrJ2myXSEklpfIfr7AfQ== [fileUNF]

This data contains a Thermal Humid Mechanical Cycle (THMC) of Shape Memory Polymers (SMP). The SMP is a polyurethane-based Polymer, which is produced from SMP Technologies Inc. The SMP filament were processed with a 3D printer (Ultimaker 3, Ultimaker, Geldermarsen, Netherlands)....

Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Dynamic Mechanical Thermal Humidity Analysis

Jun 22, 2021 - Publication: Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling

Fauser, Dominik; Steeb, Holger, 2021, "Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Dynamic Mechanical Thermal Humidity Analysis", https://doi.org/10.18419/darus-2021, DaRUS, V1, UNF:6:YC87IXxORCLw3+woYmYT3A== [fileUNF]

This data contains iso-thermal and iso-humid shear frequency-sweep measurements of Shape Memory Polymers (SMP). The SMP is a polyurethane-based Polymer, which is produced from SMP Technologies Inc. The SMP filament were processed with a 3D printer (Ultimaker 3, Ultimaker, Gelderm...

Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Diffusion measurements

Jun 22, 2021 - Publication: Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling

Fauser, Dominik; Kuhn, Moritz; Steeb, Holger, 2021, "Humidity and thermal triggered Shape Memory Effect - Rheology-based numerical modelling - Diffusion measurements", https://doi.org/10.18419/darus-2024, DaRUS, V1, UNF:6:ig+5CuLNRHaoCQtncwbvWA== [fileUNF]

This data contains diffusion measurements of Shape Memory Polymers (SMP) immersed in demineralized water. The SMP is a polyurethane-based Polymer, which is produced from SMP Technologies Inc. The SMP filament were processed with a 3D printer (Ultimaker 3, Ultimaker, Geldermarsen,...

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