A physics-informed neural framework reconstructs unsteady fluid-structure interactions from sparse off-body Lagrangian particle tracks by combining modal surface models with coordinate neural representations constrained by fluid governing equations and interface conditions.
Flow reconstruction and particle characterization from inertial Lagrangian tracks,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.flu-dyn 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Neural inference of fluid-structure interactions from sparse off-body measurements
A physics-informed neural framework reconstructs unsteady fluid-structure interactions from sparse off-body Lagrangian particle tracks by combining modal surface models with coordinate neural representations constrained by fluid governing equations and interface conditions.