A comprehensive review of advances in physics-informed neural networks and their applications in complex fluid dynamics
C Zhao, F Zhang, W Lou, X Wang, J Yang - Physics of Fluids, 2024 - pubs.aip.org
Physics-informed neural networks (PINNs) represent an emerging computational paradigm
that incorporates observed data patterns and the fundamental physical laws of a given …
that incorporates observed data patterns and the fundamental physical laws of a given …
Physics‐informed neural networks trained with time‐lapse geo‐electrical tomograms to estimate water saturation, permeability and petrophysical relations at …
C Sakar, N Schwartz, Z Moreno - Water Resources Research, 2024 - Wiley Online Library
Determining soil hydraulic properties is complex, posing ongoing challenges in managing
subsurface and agricultural practices. Electrical resistivity tomography (ERT) is an appealing …
subsurface and agricultural practices. Electrical resistivity tomography (ERT) is an appealing …