Stochastic modeling and generation of random fields of elasticity tensors: A unified information-theoretic approach

TitleStochastic modeling and generation of random fields of elasticity tensors: A unified information-theoretic approach
Publication TypeJournal Article
Year of Publication2017
AuthorsB Staber, and J Guilleminot
JournalComptes Rendus Mécanique
Volume345
Start Page399
Issue6
Pagination399 - 416
Date Published06/2017
ISSN16310721
Abstract

In this Note, we present a unified approach to the information-theoretic modeling and simulation of a class of elasticity random fields, for all physical symmetry classes. The new stochastic representation builds upon a Walpole tensor decomposition, which allows the maximum entropy constraints to be decoupled in accordance with the tensor (sub)algebras associated with the class under consideration. In contrast to previous works where the construction was carried out on the scalar-valued Walpole coordinates, the proposed strategy involves both matrix-valued and scalar-valued random fields. This enables, in particular, the construction of a generation algorithm based on a memoryless transformation, hence improving the computational efficiency of the framework. Two applications involving weak symmetries and sampling over spherical and cylindrical geometries are subsequently provided. These numerical experiments are relevant to the modeling of elastic interphases in nanocomposites, as well as to the simulation of spatially dependent wood properties for instance.

URLhttp://linkinghub.elsevier.com/retrieve/pii/S1631072117300773http://api.elsevier.com/content/article/PII:S1631072117300773?httpAccept=text/xmlhttp://api.elsevier.com/content/article/PII:S1631072117300773?httpAccept=text/plain
DOI10.1016/j.crme.2017.05.001
Short TitleComptes Rendus Mécanique