73 citations · 236 across the 14 of their papers we have counts for
4 papers · 1 filter
Efficient three-dimensional variational data assimilation of multi-plane PIV data
Uttam Cadambi Padmanaban, Samaresh Midya, Ping He +2
We perform three-dimensional variational data assimilation (3DVar) using a discrete adjoint approach to optimise the time-averaged momentum equations. The experimental data consist…
To stall-cell or not to stall-cell: Variational data assimilation of 3D mean flow past a stalled airfoil
Uttam Cadambi Padmanaban, Craig Thompson, Bharathram Ganapathisubramani +1
The full-field reconstruction of three-dimensional (3D) turbulent flows from sparse experimental measurements remains a significant challenge, particularly for flows exhibiting com…
Assimilating rough features: A data-driven framework to infer rough wall properties from sparse experimental data
Martina Formichetti, Uttam Cadambi Padmanaban, Ping He +2
Surface roughness influences turbulent boundary layers (TBLs) primarily through the roughness function and the equivalent sand-grain roughness height \(k_s\). Direct determi…
Mixed data-source transfer learning for a turbulence model augmented physics-informed neural network
Christian Toma, Bharathram Ganapathisubramani, Sean Symon
Physics-informed neural networks (PINNs) have recently emerged as a promising alternative for extracting unknown quantities from experimental data. Despite this potential, much of…