Modeling Heterogeneous Materials via Two-Point Correlation Functions: I. Basic Principles
arXiv:0705.2434 · doi:10.1103/PhysRevE.76.031110
Abstract
Heterogeneous materials abound in nature and man-made situations. Examples include porous media, biological materials, and composite materials. Diverse and interesting properties exhibited by these materials result from their complex microstructures, which also make it difficult to model the materials. In this first part of a series of two papers, we collect the known necessary conditions on the standard two-point correlation function S2(r) and formulate a new conjecture. In particular, we argue that given a complete two-point correlation function space, S2(r) of any statistically homogeneous material can be expressed through a map on a selected set of bases of the function space. We provide new examples of realizable two-point correlation functions and suggest a set of analytical basis functions. Moreover, we devise an efficient and isotropy- preserving construction algorithm, namely, the Lattice-Point algorithm to generate realizations of materials from their two- point correlation functions based on the Yeong-Torquato technique. Subsequent analysis can be performed on the generated images to obtain desired macroscopic properties. These developments are integrated here into a general scheme that enables one to model and categorize heterogeneous materials via two-point correlation functions.
37 pages, 26 figures
References in corpus (2)
Cited by in corpus (44)
- A Superior Descriptor of Random Textures and Its Predictive Capacity
- Modeling Heterogeneous Materials via Two-Point Correlation Functions: II. Algorithmic Details and Applications
- Microstructural Materials Design via Deep Adversarial Learning Methodology
- Hyperuniformity in point patterns and two-phase random heterogeneous media
- Classical Disordered Ground States: Super-Ideal Gases, and Stealth and Equi-Luminous Materials
- Inferring low-dimensional microstructure representations using convolutional neural networks
- Designing Disordered Hyperuniform Two-Phase Materials with Novel Physical Properties
- Microstructure synthesis using style-based generative adversarial network
- Hyperuniformity, quasi-long-range correlations, and void-space constraints in maximally random jammed particle packings. I. Polydisperse spheres
- Disordered Hyperuniform Heterogeneous Materials
- Prediction of local elasto-plastic stress and strain fields in a two-phase composite microstructure using a deep convolutional neural network
- Heterogeneous Force Chains in Cellularized Biopolymer Network
- Geometrical Ambiguity of Pair Statistics. I. Point Configurations
- Geometrical Ambiguity of Pair Statistics. II. Heterogeneous Media
- Precise algorithms to compute surface correlation functions of two-phase heterogeneous media and their applications
- Fractal Heterogeneous Media
- Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers
- Two-stage 2D-to-3D reconstruction of realistic microstructures: Implementation and numerical validation by effective properties
- Microstructure reconstruction using entropic descriptors
- Radial Covariance Functions Motivated by Spatial Random Field Models with Local Interactions
- Regularity conditions in the realisability problem with applications to point processes and random closed sets
- Generation and Structural Characterization of Debye Random Media
- Wang tiling aided statistical determination of the Representative Volume Element size of random heterogeneous materials
- Dynamic Measure of Hyperuniformity and Nonhyperuniformity in Heterogeneous Media via the Diffusion Spreadability
- Quantifying Microstructural Evolution via Time-Dependent Reduced-Dimension Metrics Based on Hierarchical -Point Polytope Functions
- Enhancing Mechanical Metamodels with a Generative Model-Based Augmented Training Dataset
- Neural Cellular Automata for Solidification Microstructure Modelling
- Effect of the image resolution on the statistical descriptors of heterogeneous media
- Information Content of Hierarchical n-Point Polytope Functions for Quantifying and Reconstructing Disordered Systems
- A Degradation Performance Model With Mixed-type Covariates and Latent Heterogeneity
- Level-set based design of Wang tiles for modelling complex microstructures
- Parameter-aware high-fidelity microstructure generation using stable diffusion
- Deep-subwavelength engineering of stealthy hyperuniformity
- Non-local energetics of random heterogeneous lattices
- The convex class of realisable unit covariances
- A Metric on the Polycrystalline Microstructure State Space
- Pores for thought: The use of generative adversarial networks for the stochastic reconstruction of 3D multi-phase electrode microstructures with periodic boundaries
- Diffusion Spreadability as a Probe of the Microstructure of Complex Media Across Length Scales
- The realization problem for tail correlation functions
- AI-driven Bayesian inference of statistical microstructure descriptors from finite-frequency waves
- Understanding Degeneracy of Two-Point Correlation Functions via Debye Random Media
- Novel Hierarchical Correlation Functions for Quantitative Representation of Complex Heterogeneous Materials and Microstructural Evolution
- Microstructure Design of Low-Melting-Point Alloy (LMPA)/ Polymer Composites for Dynamic Dry Adhesion Tuning in Soft Gripping
- Random Measurable Sets and Covariogram Realisability Problems