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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.
Chinesta et al. (Thu,) studied this question.
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