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 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) 2.) HYMOSTRUC model, a vector-based hydration model developed by TU Delft, The Netherlands. 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 1.) "original" denoted the unprocessed extracted from the whole CT image originally provided by NIST. 2.) "denoised" denoted the denoised image of the "original" 3.) "segmented" denoted the segmented image of the denoised image. It contains 4 - 5 phases as described below, -----notation of segmented image-------- 0 = pore 1 = hydrates 2 = portlandite 3 = clinker 4 = large isolated air void --------- Example: reading a microstructure on Python IDE import numpy as np import matplotlib.pylab as plt file = input("Please input the file you want to analyze:") #load an image image = np.load(file + ".npy") #obtain the volume fraction by np.mean print("Segmented porosity =", np.mean(image == 0)) #visualize a slice of the 3D image plt.imshow(image[0], cmap = 'gray')