Classical analytical solutions of linear elasticity are used as auxiliary solutions to solve non‐linear, and elastically heterogeneous problems on fluid‐saturated media. The 2D Kelvin's solution for a homogeneous space is considered here for simplicity sake. The material non‐linearity could be due to irreversible deformations or non‐linear elasticity response typical of 4D analysis as it is done here. The general procedure relies on a discrete collocation method and a fixed point iterative approach to construct the displacement field. The method is validated by comparing the numerical results with the analytical solution for a layered cylinder embedded in an infinite space. The h‐convergence is checked numerically illustrating the strong influence of the number of facets used to discretize the boundaries. The convergence of the iterative process based on the displacement norm is of a quasi‐quadratic rate for near homogeneous materials and declines to sub‐linear rates as the contrast in elasticity modulus exceeds 15% of the values considered for the Green's function. The method is then applied to a 2D tilted block region where the depleting reservoir has elasticity parameters function of the volumetric strain, to shed some light on the 4D effects. It is shown that the velocity changes are sensitive to the volumetric strain as well as to the strain in the wave propagating direction. Differences, including the anisotropy due to the structural response at the field scale, between the predictions based on this non‐linear isotropic elasticity and the classical R‐factor approach are finally discussed.

RESUMO:No Brasil, os resíduos de construção civil e demolição (RCD) chegam a atingir 60% da massa total de resíduos sólidos urbanos (RSU) produzidos, com geração per capita em torno de 500 kg/(hab. ano). O objetivo desse trabalho foi analisar a viabilidade técnica da utilização de agregados produzidos pela britagem de RCD em substituição aos materiais convencionais (areia, seixo, pedra britada e pó de pedra) na produção de blocos vazados de concreto simples para alvenaria de vedação. O agregado reciclado foi caracterizado e, a partir de um traço padrão utilizado por uma empresa de pré-moldados, foram produzidos cinco novos traços de concreto em que se variou a relação entre os agregados naturais (areia artificial e areia lavada) e os agregados de RCD. Os blocos produzidos foram levados à ruptura aos 28 dias, tendo apresentado valores de resistência característica à compressão entre 2,5 MPa (com adição de areia e sem RCD) e 4,3 MPa (com RCD e sem a adição de areia), superiores ao estabelecido em norma. Conclui-se que a utilização de agregados reciclados de RCD é uma alternativa viável para substituir a brita convencional na produção de blocos vazados de vedação, contribuindo para minimizar o passivo ambiental, dando um destino adequado para os RCD e, principalmente, reduzindo a extração de agregados naturais.

This research work presents a method that modifies a classical numerical method using artificial intelligence (AI) and takes advantage of an analytical method to minimize the usual need for increasing discretization. Its formulation is based on the integration of two main concepts: the reciprocity theorem and the generalization capability of artificial neural networks (ANNs). The reciprocity theorem is used to formulate the mathematical expression governing the geomechanical problem, which is then discretized in space into intelligent elements. The behavior of the strain field inside these new elements is predicted using an ANN. To make these predictions, the neural network uses displacement boundary conditions, material properties, and the geometric shape of the element as input data. The comparison was performed for two examples, in which the first had a uniform depletion of the reservoir, while the second had a non-uniform variation of the pore pressure. For the same level of accuracy, the proposed method was 10 times faster than the traditional method for the first example and five times faster for the second example on a computer with 12 threads of 2.6 GHz and 32 GB RAM.

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