The modelling of layered rocks using a numerical homogenisation technique and an artificial neural network
Author
Urbański, Aleksander
Ligęza, Szymon
Przecherski, Piotr
Published in
Technical Transactions
Numbering
Vol. 120, iss. 1
Release date
2023
Place of publication
Warsaw
Publisher
Sciendo
Magazine section
Civil Engineering
Language
English
eISSN
2353-737X
DOI
https://doi.org/10.37705/TechTrans/e2023007
Keywords
layered rocks, finite element method, homogenisation, artificial neural network
Abstract
A method of creating a constitutive model of layered rocks based on an artificial neural network (ANN) is reported in this work. The ANN gives an implicit constitutive function Ʃⁿ⁺¹= F( Ʃⁿ , ΔE), relating the new state of homogenized stresses Ʃⁿ⁺¹ with the old state Ʃⁿ and with the increment of homogenized strains ΔƩ. The first step is to repeatedly run a strain- controlled homogenisation on an uni-dimensional finite element model of a periodic cell with elastic-plastic models (Drucker-Prager) of the components. Paths are created in (Ʃ, E) space, from which, a set of patterns is formed to train the ANN. A description of how to prepare this data and a discussion on ANN training issues are presented. Finally, the procedure based on trained ANN is put into a finite-element code (ZSoil.PC) as a user-delivered constitutive function. The approach is verified by comparing the results of the developed model basing on ANN with a direct (single-scale) analysis, which showed acceptable accuracy.
