Multi-scale modelling of brick masonry using a numerical homogenisation technique and an artificial neural network

Archives of civil engineering

article

Aleksander Urbański¹  Szymon Ligęza²  Marcin Drabczyk³ 

[1] Cracow University of Technology, Faculty of Civil Engineering;AGH University of Science and Technology, Faculty of Drilling, Oil and Gas ,(doctoral student);Idealogic Ltd.

关键词: artificial neural network;    finite element method;    homogenisation;    masonry;   

DOI  :  10.24425/ace.2022.143033

学科分类：建筑学

来源: Polska Akademia Nauk * Instytut Podstawowych Problemow Techniki / Polish Academy of Sciences, Institute of Fundamental Technological Research

【 摘 要 】

A new method of creating constitutive model of masonry is reported in this work. The model is not an explicit orthotropic elastic-plastic one, but with an artificial neural network (ANN) giving an implicit constitutive function. It relates the new state of generalised stresses Σ n +1 with the old state Σ n and with an increment of generalised strains ΔE (plane-stress conditions are assumed). The first step is to run a strain- controlled homogenisation, repeatedly, on a three-dimensional finite element model of a periodic cell, with elastic-plastic models (Drucker–Prager) of the components; thus a set of paths is created in (Σ, ΔE) space. From these paths, a set of patterns is formed to train the ANN. A description of how to prepare these data and a discussion on ANN training issues are presented. Finally, the procedure based on trained ANN is put into a finite-element code as a constitutive function. This enables the analysis of arbitrarily large masonry systems. The approach is verified by comparing the results of the developed model basing on ANN with a direct (single-scale) one, which showed acceptable accuracy.

【 授权许可】

Unknown