Evaluation of three-point correlation functions from structural images on CPU and GPU architectures: Accounting for anisotropy effects.

Structures, or spatial arrangements of matter and energy, including some fields (e.g., velocity or pressure) are ubiquitous in research applications and frequently require description for subsequent analysis, or stochastic reconstruction from limited data.

Mechanism of overscreening breakdown by molecular-scale electrode surface morphology in asymmetric ionic liquids.

The interfacial nature of the electric double layer (EDL) assumes that electrode surface morphology significantly impacts the EDL properties. Since molecular-scale roughness modifies the structure of EDL, it is expected to disturb the overscreening effect and alter differential capacitance (DC). In this paper, we present a model that describes EDL near atomically rough electrodes with account for short-range electrostatic correlations.

Measuring structural nonstationarity: The use of imaging information to quantify homogeneity and inhomogeneity.

Heterogeneity is the concept we encounter in numerous research areas and everyday life. While "not mixing apples and oranges" is easy to grasp, a more quantitative approach to such segregation is not always readily available. Consider the problem from a different angle: To what extent does one have to make apples more orange and oranges more "apple-shaped" to put them into the same basket (according to their appearance alone)? This question highlights the central problem of the blurred interface between heterogeneous and homogeneous, which also depends on the metrics used for its identification.

Robust surface-correlation-function evaluation from experimental discrete digital images.

Correlation functions (CFs) are universal structural descriptors; surface-surface F_{ss} and surface-void F_{sv} CFs are a subset containing additional information about the interface between the phases. The description of the interface between pores and solids in porous media is of particular importance and recently Ma and Torquato [Phys. Rev.

Pore-network extraction using discrete Morse theory: Preserving the topology of the pore space.

Pore-scale modeling based on the 3D structural information of porous materials has enormous potential in assessing physical properties beyond the capabilities of laboratory methods. Such capabilities are pricey in terms of computational expenses, and this limits the applicability of the direct simulations to a small volume and requires high-performance computational resources, especially for multiphase flow simulations. The only pore-scale technique capable of dealing with large representative volumes of porous samples is pore-network (PNM) based modeling.

Application of percolation, critical-path, and effective-medium theories for calculation of two-phase relative permeability.

There has been active development of numerical pore-network simulation of two-phase immiscible flows in porous media in recent years. These models allow for generation of capillary pressure and relative permeability curves. However, percolation models provide an efficient alternative, with reduced reliance on numerical techniques.

Calculation of tensorial flow properties on pore level: Exploring the influence of boundary conditions on the permeability of three-dimensional stochastic reconstructions.

While it is well known that permeability is a tensorial property, it is usually reported as a scalar property or only diagonal values are reported. However, experimental evaluation of tensorial flow properties is problematic. Pore-scale modeling using three-dimensional (3D) images of porous media with subsequent upscaling to a continuum scale (homogenization) is a valuable alternative.

Hierarchical Optimization: Fast and Robust Multiscale Stochastic Reconstructions with Rescaled Correlation Functions.

Stochastic reconstructions based on universal correlation functions allow obtaining spatial structures based on limited input data or to fuse multiscale images from different sources. Current application of such techniques is severely hampered by the computational cost of the annealing optimization procedure. In this study we propose a novel hierarchical annealing method based on rescaled correlation functions, which improves both accuracy and computational efficiency of reconstructions while not suffering from disadvantages of existing speeding-up techniques.

The dynamic nature of crystal growth in pores.

The kinetics of crystal growth in porous media controls a variety of natural processes such as ore genesis and crystallization induced fracturing that can trigger earthquakes and weathering, as well as, sequestration of CO2 and toxic metals into geological formations. Progress on understanding those processes has been limited by experimental difficulties of dynamically studying the reactive surface area and permeability during pore occlusion. Here, we show that these variables cause a time-dependency of barite growth rates in microporous silica.

Universal Stochastic Multiscale Image Fusion: An Example Application for Shale Rock.

Spatial data captured with sensors of different resolution would provide a maximum degree of information if the data were to be merged into a single image representing all scales. We develop a general solution for merging multiscale categorical spatial data into a single dataset using stochastic reconstructions with rescaled correlation functions. The versatility of the method is demonstrated by merging three images of shale rock representing macro, micro and nanoscale spatial information on mineral, organic matter and porosity distribution.

Universal spatial correlation functions for describing and reconstructing soil microstructure.

Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport.