Prediction of Pore Volume Dispersion and Microstructural Characteristics of Concrete Using Image Processing Technique

Concrete has served an essential role in many infrastructural projects. Factors including pore percentage, pore distribution, and cracking affect concrete durability. This research aims to better understand pore size distribution in cement-based materials. Micro-computed tomography (micro-CT) pictures were utilised to characterise the interior structure of specimens without destroying them. The pore dispersion of the specimens was displayed in 3D, utilising the data and imaging techniques collected, and the pore volume dispersion was examined using a volume-based approach. Another way to describe heterogeneous pore features is the chord-length distribution, which was calculated from three-dimensional micro-CT scans and correlated with the traditional method. The collected specimens were subjected to physical and mechanical testing. In addition, image processing techniques were used to conduct the studies. The results showed that the chord-length distribution-based pore size distribution is very successful than the traditional volume-based technique. The acquired data could be used for research and to forecast the characteristics of the materials.

Experimental and model-based investigation of the links between snow bidirectional reflectance and snow microstructure

Snow stands out from materials at the Earth’s surface owing to its unique optical properties. Snow optical properties are sensitive to the snow microstructure, triggering potent climate feedbacks. The impacts of snow microstructure on its optical properties such as reflectance are, to date, only partially understood. However, precise modelling of snow reflectance, particularly bidirectional reflectance, are required in many problems, e.g. to correctly process satellite data over snow-covered areas. This study presents a dataset that combines bidirectional reflectance measurements over 500–2500 nm and the X-ray tomography of the snow microstructure for three snow samples of two different morphological types. The dataset is used to evaluate the stereological approach from Malinka (2014) that relates snow optical properties to the chord length distribution in the snow microstructure. The mean chord length and specific surface area (SSA) retrieved with this approach from the albedo spectrum and those measured by the X-ray tomography are in excellent agreement. The analysis of the 3D images has shown that the random chords of the ice phase obey the gamma distribution with the shape parameter m taking the value approximately equal to or a little greater than 2. For weak and intermediate absorption (high and medium albedo), the simulated bidirectional reflectances reproduce the measured ones accurately but tend to slightly overestimate the anisotropy of the radiation. For such absorptions the use of the exponential law for the ice chord length distribution instead of the one measured with the X-ray tomography does not affect the simulated reflectance. In contrast, under high absorption (albedo of a few percent), snow microstructure and especially facet orientation at the surface play a significant role in the reflectance, particularly at oblique viewing and incidence.

Experimental and model-based investigation of the links between snow bidirectional reflectance and snow microstructure

Snow stands out from materials at the Earth's surface owing to its unique optical properties. Snow optical properties are sensitive to the snow microstructure, triggering potent climate feedbacks. The impacts of snow microstructure on its optical properties such as reflectance are, to date, only partially understood. However, precise modelling of snow reflectance, particularly bidirectional one, are required in many problems, e.g. to process correctly satellite data over snow-covered areas. This study presents a dataset that combines bidirectional reflectance measurements over 500–2500 nm and the X-ray tomography of the snow microstructure for three snow samples of two different morphological types. The dataset is used to evaluate the stereological approach from Malinka (2014) that relates snow optical properties to the chord length distribution in the snow microstructure. The mean chord length and SSA retrieved with this approach from the albedo spectrum and those measured by the X-ray tomography are in excellent agreement. The analysis of the 3D images has shown that the random chords of the ice phase obey the gamma distribution with the shape parameter m taking the value approximately equal or a little greater than 2. For weak and intermediate absorption (high and medium albedo), the simulated bidirectional reflectances reproduce the measured ones accurately but tend to slightly overestimate the anisotropy of the radiation. For such absorptions the use of the exponential law for the ice chord length distribution instead of the one measured with the X-ray tomography does not affect the simulated reflectance. In contrast, under high absorption (albedo of a few percent), snow microstructure and especially facet orientation at the surface, plays a significant role for the reflectance, particularly at oblique viewing and incidence.

Algebraic approximations of a polyhedron correlation function stemming from its chord-length distribution

An algebraic approximation, of order K, of a polyhedron correlation function (CF) can be obtained from γ′′(r), its chord-length distribution (CLD), considering first, within the subinterval [D i−1, D i ] of the full range of distances, a polynomial in the two variables (r − D i−1)1/2 and (D i − r)1/2 such that its expansions around r = D i−1 and r = D i simultaneously coincide with the left and right expansions of γ′′(r) around D i−1 and D i up to the terms O(r − D i−1) K/2 and O(D i − r) K/2, respectively. Then, for each i, one integrates twice the polynomial and determines the integration constants matching the resulting integrals at the common end-points. The 3D Fourier transform of the resulting algebraic CF approximation correctly reproduces, at large q's, the asymptotic behaviour of the exact form factor up to the term O[q −(K/2+4)]. For illustration, the procedure is applied to the cube, the tetrahedron and the octahedron.

Chord length distribution and the distance between two random points in a convex body in Rn

In this article for n-dimensional convex body D the relation between the chord length distribution function and the distribution function of the distance between two random points in D was found. Also the relation between their moments was found.

Microstructure Comparison Using Dissimilarity Metric for Additive Manufacturing of Metals

Additive Manufacturing (AM) simulations are often employed to replace the expensive experiments to study the effects of processing conditions. In process modeling, one of the key limitations is the lack of reliable validation techniques. The stochastic nature and the spatial heterogeneity of microstructures make it difficult to validate the simulated microstructures against experimentally obtained images through statistical measures (e.g. average and standard deviation of grain sizes). In this work, a validation metric is proposed that can effectively quantify the dissimilarity between two AM microstructures. The methodology involves first calculating the Angularly Resolved Chord Length Distribution (ARCLD) at representative angles and then computing the Earth Mover’s Distance (EMD) to obtain the final unitless score that is named Dissimilarity Score (DS). The efficacy of the proposed methodology was first tested on synthetic microstructures, and then on AM simulations that employ the solidification model-Cellular Automaton (CA) with IN625. Results show that DS effectively measures the dissimilarity between different microstructures. The use of DS is also extended to calibrate the CA processing simulation code to match with experimental AM images from NIST AM-Bench Challenge.

The chord-length distribution of a polyhedron

The chord-length distribution function [γ′′(r)] of any bounded polyhedron has a closed analytic expression which changes in the different subdomains of the r range. In each of these, the γ′′(r) expression only involves, as transcendental contributions, inverse trigonometric functions of argument equal to R[r, Δ1], Δ1 being the square root of a second-degree r polynomial and R[x, y] a rational function. As r approaches δ, one of the two end points of an r subdomain, the derivative of γ′′(r) can only show singularities of the forms |r − δ|−n and |r − δ|−m+1/2, with n and m appropriate positive integers. Finally, the explicit analytic expressions of the primitives are also reported.

Effect of Pre-Shear on Agglomeration and Rheological Parameters of Cement Paste

Cementitious pastes are multiphase suspensions that are rheologically characterized by viscosity and yield stress. They tend to flocculate during rest due to attractive interparticle forces, and desagglomerate when shear is induced. The shear history, e.g., mixing energy and time, determines the apparent state of flocculation and accordingly the particle size distribution of the cement in the suspension, which itself affects suspension’s plastic viscosity and yield stress. Thus, it is crucial to understand the effect of the mixing procedure of cementitious suspensions before starting rheological measurements. However, the measurement of the in-situ particle agglomeration status is difficult, due to rapidly changing particle network structuration. The focused beam reflectance measurement (FBRM) technique offers an opportunity for the in-situ investigation of the chord length distribution. This enables to detect the state of flocculation of the particles during shear. Cementitious pastes differing in their solid fraction and superplasticizer content were analyzed after various pre-shear histories, i.e., mixing times. Yield stress and viscosity were measured in a parallel-plate-rheometer and related to in-situ measurements of the chord length distribution with the FBRM-probe to characterize the agglomeration status. With increasing mixing time agglomerates were increasingly broken up in dependence of pre-shear: After 300 s of pre-shear the agglomerate sizes decreased by 10 µm to 15 µm compared to a 30 s pre-shear. At the same time dynamic yield stress and viscosity decreased up to 30% until a state of equilibrium was almost reached. The investigations show a correlation between mean chord length and the corresponding rheological parameters affected by the duration of pre-shear.