most citedSimulation of multi-species flow and heat transfer using physics-informed neural networks

198 citations · 203 across the 4 of their papers we have counts for

collaborators

4 papers

physics.med-ph20223 cited

Non-invasive estimation of left ventricle elastance using a multi-compartment lumped parameter model and gradient-based optimization with forward-mode automatic differentiation

Ryno Laubscher, Johan Van Der Merwe, Jacques Liebenberg +1

Accurate estimates of left ventricle elastances based on non-invasive measurements are required for clinical decision-making during treatment of valvular diseases. The present stud…

physics.med-ph20221 cited

Dynamic simulation of aortic valve stenosis using a lumped parameter cardiovascular system model with flow regime dependent valve pressure loss characteristics

Ryno Laubscher, Jacques Liebenberg, Philip Herbst

Valvular heart diseases are growing concern in impoverished parts of the world, such as Southern-Africa, claiming more than 31 % of total deaths related to cardiovascular diseases.…

physics.flu-dyn2021198 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-dyn20211 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…