Compressing Random Microstructures via Stochastic Wang Tilings

TL;DR

This paper introduces a stochastic Wang tiling method to efficiently compress and reconstruct disordered microstructures, capturing long-range order by using multiple tiles instead of a single unit cell.

Contribution

It proposes a novel stochastic tiling approach that improves microstructure representation accuracy and extensibility over traditional single-unit-cell methods.

Findings

Accurately reproduces long-range orientation orders.

Efficiently compresses microstructures with multiple tiles.

Framework extensible to multi-dimensional media.

Abstract

This paper presents a stochastic Wang tiling based technique to compress or reconstruct disordered microstructures on the basis of given spatial statistics. Unlike the existing approaches based on a single unit cell, it utilizes a finite set of tiles assembled by a stochastic tiling algorithm, thereby allowing to accurately reproduce long-range orientation orders in a computationally efficient manner. Although the basic features of the method are demonstrated for a two-dimensional particulate suspension, the present framework is fully extensible to generic multi-dimensional media.