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This document reviews the integration of artificial intelligence (AI) in solving partial differential equations (PDEs) within computational mechanics, highlighting its significance in various applications like solid mechanics, fluid mechanics, and biomechanics. It discusses methodologies such as Physics-Informed Neural Networks (PINNs), operator learning, and physics-informed neural operators, emphasizing their potential to enhance traditional numerical methods. The review also addresses challenges such as

Author

Shweta Pandey

Language

EN