Microstructure dataset CCC-D-23-00329

Microstructure dataset supporting the readers of the journal article [CCC-D-23-00329]: Effective diffusivity of hardened cement paste from 3D microstructures: a critical comparison of real and virtual microstructures by Pakpoom Limtong, Ravi A. Patel, Yuya Takahashi, Tetsuya Ishida<br> <br> This data set contains 3D hardened cement paste microstructures with the water-to-cement mass ratio (w/c) of 0.30, 0.40, and 0.45. Three microstructure entities (µCT, HYMOSTRUC, and CEMHYD3D) are provided with the same voxel resolution of 1 µm/voxel and the same degree of hydration. 1.) µCT from The NIST Visible Cement Data Set (https://visiblecement.nist.gov/cement.html)<br> 2.) HYMOSTRUC model, a vector-based hydration model developed by TU Delft, The Netherlands.<br> 3.) CEMHYD3D model, a voxel-based hydration model developed by NIST, USA. The data set is given in an 8-bit numpy file format. For more details, please refer to the description of each sample. Nomenclature: image_w/c_size.npy<br> 1.) "original" denoted the unprocessed extracted from the whole CT image originally provided by NIST.<br> 2.) "denoised" denoted the denoised image of the "original"<br> 3.) "segmented" denoted the segmented image of the denoised image. It contains 4 - 5 phases as described below,<br> -----notation of segmented image-------- 0 = pore 1 = hydrates 2 = portlandite 3 = clinker 4 = large isolated air void ---------<br> <br> Example: reading a microstructure on Python IDE<br> import numpy as np<br> import matplotlib.pylab as plt<br> file = input("Please input the file you want to analyze:")<br> #load an image<br> image = np.load(file + ".npy")<br> #obtain the volume fraction by np.mean<br> print("Segmented porosity =", np.mean(image == 0))<br> #visualize a slice of the 3D image<br> plt.imshow(image[0], cmap = 'gray')