Computational mechanics empowered by artificial intelligence
Abstract
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.
Fields of Study & Subjects
Model Reduction and Neural Networks
Machine Learning in Materials Science
Generative Adversarial Networks and Image Synthesis
Publication details
- Journal / source
- Mechanics & Industry
- Publisher
- EDP Sciences
- Volume
- 27
- Pages
- 26–26
- Publication date
- 1 January 2026
- Language
- EN