FEM-GAN: A Physics-Supervised Deep Learning Generative Model for Elastic Porous Materials.

X-ray μCT imaging is a common technique that is used to gain access to the full-field characterization of materials. Nevertheless, the process can be expensive and time-consuming, thus limiting image availability. A number of existing generative models can assist in mitigating this limitation, but they often lack a sound physical basis.

Predicting the Non-Deterministic Response of a Micro-Scale Mechanical Model Using Generative Adversarial Networks.

Recent improvements in micro-scale material descriptions allow to build increasingly refined multiscale models in geomechanics. This often comes at the expense of computational cost which can eventually become prohibitive. Among other characteristics, the non-determinism of a micro-scale response makes its replacement by a surrogate particularly challenging.

Bounding the Multi-Scale Domain in Numerical Modelling and Meta-Heuristics Optimization: Application to Poroelastic Media with Damageable Cracks.

It is very common for natural or synthetic materials to be characterized by a periodic or quasi-periodic micro-structure. This micro-structure, under the different loading conditions may play an important role on the apparent, macroscopic behaviour of the material. Although, fine, detailed information can be implemented at the micro-structure level, it still remains a challenging task to obtain experimental metrics at this scale.

Dewatering model for optimal operation of sludge treatment wetlands.

Sludge treatment wetlands (STW) are used as a dewatering technology in some European countries since the 80's. Although the efficiency of this technology in terms of sludge dewatering and mineralisation is well known, design and operation parameters are yet to be standardised. The aim of this study is to develop a mathematical model capable of predicting the water loss with time, in order to optimise the feeding frequency enhancing sludge dewatering and expanding the lifespan of the system.