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401 to 410 of 501 Results

Publication: Porosity and Permeability of Subflorescent Salt Crusts Formed by Evaporation From Porous Media(Universität Stuttgart) Aug 26, 2021 This dataverse includes the underlying XRCT data sets of the publication: Piotrowski, J., Lee, D., Pohlmeier, A., Vereecken, H., Steeb, H., & Huisman, J.A. (2021). Porosity and Permeability of Subflorescent Salt Crusts Formed by Evaporation from Porous Media. (in preparation).
Publication: Effects of Thermal Treatment on Acoustic Waves in Carrara Marble(Universität Stuttgart) Aug 24, 2021 This dataverse includes the underlying measurment data of the publication: Ruf, M., & Steeb, H. (2022). Effects of thermal treatment on acoustic waves in Carrara marble. International Journal of Rock Mechanics and Mining Sciences, 159, 105205. https://doi.org/10.1016/j.ijrmms.2022.105205
Fracture network segmentation Jul 7, 2021 - Publication: Detecting micro fractures with X-ray computed tomography Lee, Dongwon; Nikolaos, Karadimitriou; Steeb, Holger, 2021, "Fracture network segmentation", https://doi.org/10.18419/DARUS-1847, DaRUS, V1 This dataset contains the codes to reproduce the five different segmentation results of the paper Lee et al (2021). The original dataset before applying these segmentation codes could be found in Ruf & Steeb (2020). The adopted segmentation methods in order to identify the micro fractures within the original dataset are the Local threshold, Sato, C...
Chan_vese.m Jul 7, 2021 - Fracture network segmentation Plain Text - 5.3 KB - MD5: 42ba2403995ffbc255edfddfb575efa6 This file contains the workflow of Chan-Vese method
classifier.model Jul 7, 2021 - Fracture network segmentation Unknown - 1.9 GB - MD5: 9c0aaff5be02d37f4dd76756a142da01 This is the trained model with the Random forest method. This file could be loaded in the open source program ImageJ with TrainableWeka library. The predictions can be generated with processing.bsh code.
Frac_Unet_postprocess.py Jul 7, 2021 - Fracture network segmentation Plain Text - 3.0 KB - MD5: 8af741da7af5db62a1855a4c4eed56d0 With the code, the predictions of trained model for given input files can be generated and saved.
Frac_Unet_preprocess.py Jul 7, 2021 - Fracture network segmentation Plain Text - 2.2 KB - MD5: a269c380d683920ac900d3539a4fdc6a Preparation of training data can be done with the code
Frac_Unet_training.py Jul 7, 2021 - Fracture network segmentation Plain Text - 5.6 KB - MD5: 0d2949b2c023b9f5b67ccefb8487d803 With the pre-processed training data, the code performs training of U-net model and saves a trained model after training.
img_seg.py Jul 7, 2021 - Fracture network segmentation Plain Text - 15.4 KB - MD5: 9a20bdaef7a1f87ecfdd053873a642bf This file contains the load/save functions and core functions of the Sato and the Local threshold methods.
Local_threshold.py Jul 7, 2021 - Fracture network segmentation Plain Text - 1.5 KB - MD5: 68ae24ecafdaa06a04bf09504eb44fd2 This file contains the workflow of the local threshold method

Publication: Porosity and Permeability of Subflorescent Salt Crusts Formed by Evaporation From Porous Media(Universität Stuttgart)

Aug 26, 2021

This dataverse includes the underlying XRCT data sets of the publication: Piotrowski, J., Lee, D., Pohlmeier, A., Vereecken, H., Steeb, H., & Huisman, J.A. (2021). Porosity and Permeability of Subflorescent Salt Crusts Formed by Evaporation from Porous Media. (in preparation).

Publication: Effects of Thermal Treatment on Acoustic Waves in Carrara Marble(Universität Stuttgart)

Aug 24, 2021

This dataverse includes the underlying measurment data of the publication: Ruf, M., & Steeb, H. (2022). Effects of thermal treatment on acoustic waves in Carrara marble. International Journal of Rock Mechanics and Mining Sciences, 159, 105205. https://doi.org/10.1016/j.ijrmms.2022.105205

Fracture network segmentation

Jul 7, 2021 - Publication: Detecting micro fractures with X-ray computed tomography

Lee, Dongwon; Nikolaos, Karadimitriou; Steeb, Holger, 2021, "Fracture network segmentation", https://doi.org/10.18419/DARUS-1847, DaRUS, V1

This dataset contains the codes to reproduce the five different segmentation results of the paper Lee et al (2021). The original dataset before applying these segmentation codes could be found in Ruf & Steeb (2020). The adopted segmentation methods in order to identify the micro fractures within the original dataset are the Local threshold, Sato, C...

Chan_vese.m