9 papers · 1 filter
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…
Three-dimensional variational data assimilation of separated flows using time-averaged experimental data
Uttam Cadambi Padmanaban, Bharathram Ganapathisubramani, Sean Symon
We present a novel framework for assimilating planar PIV experimental data using a variational approach to enhance the predictions of the Spalart-Allmaras RANS turbulence model. Ou…
Effects of fetch length on turbulent boundary layer recovery past a step-change in surface roughness
Martina Formichetti, Dea D. Wangsawijaya, Sean Symon +1
Recent studies focusing on the response of turbulent boundary layers (TBL) to a step-change in roughness have provided insight into the scaling and characterisation of TBLs and the…
Energy transfer in turbulent channel flows and implications for resolvent modelling
Sean Symon, Simon J. Illingworth, Ivan Marusic
We analyse the inter-scale transfer of energy for two types of plane Poiseuille flow: the P4U exact coherent state of Park and Graham (2015) and turbulent flow in a minimal channel…
Energy transfer mechanisms and resolvent analysis in the cylinder wake
Bo Jin, Sean Symon, Simon J. Illingworth
Energy transfer mechanisms for vortex shedding behind a 2D cylinder at a Reynolds number of Re=100 are investigated. We first characterize the energy balances achieved by the true…