crossrefFluids2025-08-28Cited by 22
Machine Learning in Fluid Dynamics—Physics-Informed Neural Networks (PINNs) Using Sparse Data: A Review
Mouhammad El Hassan, Ali Mjalled, Philippe Miron, Martin Mönnigmann, Nikolay Bukharin
Fluid mechanics often involves complex systems characterized by a large number of physical parameters, which are usually described by experimental and numerical sparse data (temporal or spatial). The difficulty of obtaining complete spatio-temporal datasets is a common issue with…