Poroelastic material characterisation by means of Artificial Neural Network

Poroelastic problems require multiscale and multiphysics techniques that are expensive and time-consuming, which result in either several simplifications or costly experimental tests. The latter motivates us to develop a more efficient approach to address more complex problems with an acceptable computational cost.
In this manuscript, first, the necessary equations derived from Asymptotic homogenisation for poroelastic media are mentioned. Then, the variational formulation of the cell problems is carried out and solved by the open-source FE package FEniCS. This is followed by presenting the advantages and downsides of macroscale properties identification via asymptotic homogenisation and the application of Artificial Neural Network (ANN) to solve the issues stated as its downsides by means of bypassing the process of solving the cell problems. Finally, we study a practical example, namely, spatial dependent porosity (in macroscale) to demonstrate the feasibility of using the provided framework to include more details. Further applications, including growth and remodelling, are subjects of future articles.