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Abdullah Alqubalee

Publications and source records attributed to Abdullah Alqubalee.

2 recordsLinked to original sources

Stationarity-constrained representative volume elements for image-based homogenization of granular microstructures

We present an image-based workflow for representative elementary volume (REV) sizing in chemically mapped granular microstructures, applied to Arabian dune-sand samples characterized by mineralogical and textural heterogeneity. The REV is treated as a finite-window convergence scale within approximately stationary material domains, rather than as a global length assigned to a non-stationary image. Full-resolution backscattered-electron (BSE) gray-level maps are screened by local mean and standard-deviation compatibility to identify stationary domains. Candidate windows are sampled only inside these domains, and the representative support is selected using a persistent mean--spectral criterion requiring both the apparent-mean residual and the low-wavenumber covariance-spectrum residual to remain within tolerance over the non-reference tail. Ensemble reproducibility is used as an auxiliary check. Applied to seven full-resolution BSE images of dune-sand microstructures, the strict stationary-domain criterion gives $(L_{\rm REV}=1536~\mathrm{pixels})$, corresponding to $(\ell_{\rm REV}\approx2.01~\mathrm{mm})$ for a BSE pixel size of $(1.31~\mu\mathrm{m})$. Property-level homogenization on QEMSCAN-derived numerical maps independently supports this millimetre-scale estimate: the converted support is $(L_{\rm REV}^{\rm prop}=201.2)$ pixels and is snapped to the nearest tested size, $(L_{\rm REV}^{\rm prop}=204)$ pixels $(\ell_{\rm REV}^{\rm prop}=2.04~\mathrm{mm})$. This length lies in the large-window regime of the apparent conductivity, stiffness, and directional Young-modulus curves. The workflow provides a reproducible route for REV sizing while making explicit its dependence on stationarity, image field, window sequence, and target observable.

cond-mat.mtrl-sci

Representative-volume sizing in finite cylindrical computed tomography by low-wavenumber spectral convergence

Choosing a representative element volume (REV) from finite cylindrical Computed Tomography (CT) scans becomes ambiguous when a key field variable exhibits a slow axial trend, reflecting either geological variability or CT acquisition/reconstruction artifacts. In such cases, estimated statistics may vary systematically with subvolume size and position rather than converging by simple averaging. We present a practical workflow for sizing an REV under nonstationary conditions by first suppressing axial drift/trend to obtain a residual field suitable for second-order analysis, and then selecting the smallest analysis diameter for which the low-wavenumber spectral content stabilizes within a prescribed tolerance. The method is demonstrated on \textit{Thalassinoides}-bearing rocks, where branching burrow networks introduce heterogeneity at length scales comparable to laboratory core diameters, making imaging-based microstructural statistics and digital-rock estimates sensitive to subvolume choice. From segmented data, we define a scalar ``burrowsity'' field capturing burrow-related pore spaces and infills. Axial detrending, with optional normalization, mitigates acquisition drift and nonstationary trends, while covariance/spectral convergence is evaluated on nested cylinders consistent with the core geometry. Representativeness is posed as diameter convergence on nested inscribed cylinders: the two-point covariance and isotropic spectrum $\widehat{C}$ are estimated, and the smallest diameter at which the low-wavenumber plateau becomes stable is selected. Applied to a segmented \textit{Thalassinoides} core, the method gives $D_{\mathrm{REV}}\simeq 93~\mathrm{mm}$ and $H_{\mathrm{REV}}\simeq 83~\mathrm{mm}$, enabling reproducible correlation-scale reporting and connectivity-sensitive property estimation.

cond-mat.soft