flow field reconstruction 1hemodynamic indicators 1incompressible navier-stokes 1physics-informed neural networks 1wall shear stress estimation 1
From the 1 of 2 linked papers with an AI index.
2 papers
math.NA2026
Physics-Informed Neural Networks for the High-Resolution Reconstruction of Flow Measurement Indicators in Fluid Dynamics
Irena RadiÅ¡iÄ, Raffaele Tirotta, Alberto Zingaro +2
The paper introduces a physics-informed neural network (PINN) framework that combines incompressible Navier‑Stokes equations with sparse experimental velocity data to reconstruct h…
physics.flu-dyn2025
A Multi-Component, Multi-Physics Computational Model for Solving Coupled Cardiac Electromechanics and Vascular Haemodynamics
Sharp C. Y. Lo, Alberto Zingaro, Jon W. S. McCullough +5
The circulatory system, comprising the heart and blood vessels, is vital for nutrient transport, waste removal, and homeostasis. Traditional computational models often treat cardia…