41 to 50 of 647 Results
Feb 2, 2026 -
Supplemental data for "Accelerating Conjugate Gradient Solvers for Homogenization Problems with Unitary Neural Operators"
Unknown - 159.5 MB -
MD5: b2bd3b2ace213ded7cf7dddd52703427
Learned UNO weights for the mechanical problem in 3D with Dirichlet BC |
Feb 2, 2026 -
Supplemental data for "Accelerating Conjugate Gradient Solvers for Homogenization Problems with Unitary Neural Operators"
Unknown - 81.4 MB -
MD5: 579a8264e01eeb76b14cef10a8d6d325
Learned UNO weights for the mechanical problem in 3D with mixed BC |
Feb 2, 2026 -
Supplemental data for "Accelerating Conjugate Gradient Solvers for Homogenization Problems with Unitary Neural Operators"
Unknown - 486.0 MB -
MD5: 161f7b3a0c2a279e3406445ae7b0ff26
Learned UNO weights for the mechanical problem in 3D with periodic BC |
Feb 2, 2026 -
Supplemental data for "Accelerating Conjugate Gradient Solvers for Homogenization Problems with Unitary Neural Operators"
Unknown - 2.4 MB -
MD5: 3c8bda6aed28f796fd8e059d5f6b26d2
Learned UNO weights for the thermal problem in 2D with periodic BC (naive training) |
Feb 2, 2026 -
Supplemental data for "Accelerating Conjugate Gradient Solvers for Homogenization Problems with Unitary Neural Operators"
Unknown - 1.2 MB -
MD5: 2006ce8ce17bffe09ef775a6305a8401
Learned UNO weights for the thermal problem in 2D with periodic BC |
Feb 2, 2026 -
Supplemental data for "Accelerating Conjugate Gradient Solvers for Homogenization Problems with Unitary Neural Operators"
Unknown - 53.2 MB -
MD5: 8a257ace5547a6634fb7902f2b587cf9
Learned UNO weights for the thermal problem in 3D with Dirichlet BC |
Feb 2, 2026 -
Supplemental data for "Accelerating Conjugate Gradient Solvers for Homogenization Problems with Unitary Neural Operators"
Unknown - 108.0 MB -
MD5: 598c06283c4395ee752ac35773937cd1
Learned UNO weights for the thermal problem in 3D with periodic BC |
Oct 30, 2025 -
micro-XRCT data set of Carrara marble with artificially created crack network: fast cooling down from 500°C
Gzip Archive - 292.0 MB -
MD5: d9bef158aa03934a8487776af9a867fc
Binarization of "reconstructed.tar.gz" showing the extracted crack network in 8 bit *.tif file format. 2940x2940x2141 voxels with uniform voxel size of 2.0 µm. Binarization was achieved using the published code, "Fracture network segmentation," available at https://doi.org/10.18419/darus-1847. |
Oct 30, 2025 -
micro-XRCT data set of Carrara marble with artificially created crack network: fast cooling down from 500°C
Gzip Archive - 17.3 GB -
MD5: 59747bae51f2832e020ddf0706d75160
Projection images (360 deg, angle increment 0.2 deg), dark image (di) and open beam image (ob) in 16 bit *.tif file format. (Internal ID: "20220601_01/projections") |
Oct 30, 2025 -
micro-XRCT data set of Carrara marble with artificially created crack network: fast cooling down from 500°C
Gzip Archive - 25.4 GB -
MD5: dd4ff7991cab38e0a58d5b0e8c4ceea6
Reconstructed micro-XRCT data set in 16 bit *.tif file format. 2940x2940x2141 voxels with the uniform voxel size of 2.0 µm. (Internal ID: "20220601_01/reconstructed") |
