A texture tensor to quantify deformations
Miguel Aubouy, Yi Jiang, James A.Glazier, and Fran\c{c}ois Graner

TL;DR
This paper introduces a statistical texture tensor that unifies microscopic and macroscopic descriptions of material deformation, capturing both elastic and fluid-like responses.
Contribution
It proposes a new formalism based on the texture tensor that extends elastic strain definitions to include fluid-like deformations from microscopic principles.
Findings
Defines the statistical texture tensor for deformation quantification
Links microscopic and macroscopic deformation descriptions
Extends elastic strain concept to fluid-like responses
Abstract
Under mechanical deformation, most materials exhibit both elastic and fluid (or plastic) responses. No existing formalism derived from microscopic principles encompasses both their fluid-like and solid-like aspects. We define the {\it statistical texture tensor} to quantify the intuitive notion of stored deformation. This tensor links microscopic and macroscopic descriptions of the material, and extends the definition of elastic strain.
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Taxonomy
TopicsElasticity and Material Modeling · Medical Image Segmentation Techniques
