In this paper, the authors present an extension of the scope of the previously conducted research to the full three-dimensional computer simulation (using the finite element method), which takes into account the interaction between: heavy caterpillar tracks system – working platform – weak subsoil. The article presents a computer model considering two caterpillars, resting on elastic-plastic sub-soil, with standard Mohr-Coulomb yield conditions, allowing for computer simulation of the behavior of the system up to achievement of ultimate limit state. The results of the above model are treated as the reference for a simplified Analytical Models of estimating the limit state, which might be used in design procedures. In turn, these Analytical Models are enhancements of previously presented one. The most important results concluding form the Analytical Model are simple interaction formulas, in the space of moments acting on the machine-subsoil system, limiting a domain of safety in given soil conditions.

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.