198 citations · 203 across the 5 of their papers we have counts for
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physics.flu-dyn2021★ 198 cited
Simulation of multi-species flow and heat transfer using physics-informed neural networks
Ryno Laubscher
In the present work, single- and segregated-network PINN architectures are applied to predict momentum, species and temperature distributions of a dry air humidification problem in…
physics.flu-dyn2021★ 1 cited
Application of mixed-variable physics-informed neural networks to solve normalised momentum and energy transport equations for 2D internal convective flow
Ryno Laubscher, Pieter Rousseau
The prohibitive cost and low fidelity of experimental data in industry scale thermofluid systems limit the usefulness of pure data-driven machine learning methods. Physics-informed…