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Related papers: Modeling Heterogeneous Materials via Two-Point Cor…

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In the first part of this series of two papers, we proposed a theoretical formalism that enables one to model and categorize heterogeneous materials (media) via two-point correlation functions S2 and introduced an efficient…

Materials Science · Physics 2009-11-13 Y. Jiao , F. H. Stillinger , S. Torquato

The versatile physical properties of heterogeneous materials are intimately related to their complex microstructures, which can be statistically characterized and modelled using various spatial correlation functions containing key…

Materials Science · Physics 2019-10-01 Yang Jiao

By using the most sensitive two-point correlation functions introduced to date, we reconstruct the microstructures of two-phase random media with heretofore unattained accuracy. Such media arise in a host of contexts, including porous and…

Materials Science · Physics 2015-06-03 Chase E. Zachary , Salvatore Torquato

This paper considers the open challenge of identifying complete, concise, and explainable quantitative microstructure representations for disordered heterogeneous material systems. Completeness and conciseness have been achieved through…

Materials Science · Physics 2021-09-07 Sheng Cheng , Yang Jiao , Yi Ren

In their seminal paper on scattering by an inhomogeneous solid, Debye and coworkers proposed a simple exponentially decaying function for the two-point correlation function of an idealized class of two-phase random media. Such {\it Debye…

Disordered Systems and Neural Networks · Physics 2020-10-22 Zheng Ma , Salvatore Torquato

It is well-known that the degeneracy of two-phase microstructures with the same volume fraction and two-point correlation function $S_2(\mathbf{r})$ is generally infinite. To elucidate the degeneracy problem explicitly, we examine Debye…

Soft Condensed Matter · Physics 2021-10-15 Murray Skolnick , Salvatore Torquato

In a previous paper [Jiao, Stillinger and Torquato, PRE 81, 011105 (2010)], we considered the geometrical ambiguity of pair statistics associated with point configurations. Here we focus on the analogous problem for heterogeneous media…

Statistical Mechanics · Physics 2010-07-09 Yang Jiao , Frank H. Stillinger , Sal Torquato

The quantitative characterization of the microstructure of random heterogeneous media in $d$-dimensional Euclidean space $\mathbb{R}^d$ via a variety of $n$-point correlation functions is of great importance, since the respective infinite…

Soft Condensed Matter · Physics 2018-08-07 Zheng Ma , Salvatore Torquato

The two-scale computational homogenization method is proposed for modelling of locally periodic fluid-saturated media subjected a to large deformation induced by quasistatic loading. The periodic heterogeneities are relevant to the…

Numerical Analysis · Mathematics 2022-02-11 Vladimír Lukeš , Eduard Rohan

The capabilities of additive manufacturing have facilitated the design and production of mechanical metamaterials with diverse unit cell geometries. Establishing linkages between the vast design space of unit cells and their effective…

Computational Engineering, Finance, and Science · Computer Science 2025-05-05 Hooman Danesh , Maruthi Annamaraju , Tim Brepols , Stefanie Reese , Surya R. Kalidindi

Two-point correlation functions provide crucial yet incomplete characterization of microstructures because different microstructures may have the same correlation function. In an earlier Letter [Phys. Rev. Lett. 108, 080601 (2012)], we…

Statistical Mechanics · Physics 2012-05-16 Cedric J. Gommes , Yang Jiao , Salvatore Torquato

A fascinating inverse problem that has been receiving considerable attention is the construction of realizations of random two-phase heterogeneous media with a target two-point correlation function. However, not every hypothetical two-point…

Disordered Systems and Neural Networks · Physics 2007-05-23 Salvatore Torquato

To leverage advancements in machine learning for metallic materials design and property prediction, it is crucial to develop a data-reduced representation of metal microstructures that surpasses the limitations of current physics-based…

The paper presents two-scale numerical algorithms for stress-strain analysis of porous media featured by self-contact at pore level. The porosity is constituted as a periodic lattice generated by a representative cell consisting of elastic…

Analysis of PDEs · Mathematics 2023-01-18 Eduard Rohan , Jan Heczko

The application of machine learning in materials presents a unique challenge of dealing with scarce and varied materials data - both experimental and theoretical. Nevertheless, several state-of-the-art machine learning models for materials…

Two-phase random textures abound in a host of contexts, porous and composite media, ecological structures, biological media and astrophysical structures. Questions surrounding the spatial structure of such textures continue to pose many…

Materials Science · Physics 2012-01-04 Yang Jiao , Sal Torquato , Frank H. Stillinger

Characterizing microstructure-material-property relations calls for software tools which extract point-cloud- and continuum-scale-based representations of microstructural objects. Application examples include atom probe, electron, and…

Modification of physical properties of materials and design of materials with on-demand characteristics is at the heart of modern technology. Rare application relies on pure materials--most devices and technologies require careful design of…

Effective and accurate characterization and quantification of complex microstructure of a heterogeneous material and its evolution under external stimuli are very challenging, yet crucial to achieving reliable material performance…

Materials Science · Physics 2019-05-20 Pei-En Chen , Wenxiang Xu , Nikhilesh Chawla , Yi Ren , and Yang Jiao

We consider a strongly heterogeneous medium saturated by an incompressible viscous fluid as it appears in geomechanical modeling. This poroelasticity problem suffers from rapidly oscillating material parameters, which calls for a thorough…

Numerical Analysis · Mathematics 2018-12-27 Robert Altmann , Eric Chung , Roland Maier , Daniel Peterseim , Sai-Mang Pun
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