Computational mechanics empowered by artificial intelligence

The present paper revisits recent challenges in computational mechanics where data-driven modeling offers unexpected possibilities. For that purpose, the main concepts related to data and learning are first introduced. Then, physics-based, data-driven, and hybrid modeling approaches in the different domains of mechanics: solids and structures, fluids and flow, and processing and manufacturing will be addressed. Finally, technology needs, recent advances, and remaining challenges in the industrial sector will be highlighted.