A Reduced Order Model formulation for left atrium flow: an Atrial Fibrillation case

TL;DR

This paper develops a data-driven Reduced Order Model using POD-RBF to efficiently analyze blood flow in atrial fibrillation, capturing key hemodynamic patterns with high accuracy and speed.

Contribution

It introduces a novel ROM framework combining POD and RBF for patient-specific atrial fibrillation blood flow analysis, including non-Newtonian effects.

Findings

High accuracy in reconstructing blood flow patterns.

Significant computational speed-up over full models.

Effective handling of both Newtonian and non-Newtonian blood laws.

Abstract

A data-driven Reduced Order Model (ROM) based on a Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) approach is adopted in this paper for the analysis of blood flow dynamics in a patient-specific case of Atrial Fibrillation (AF). The Full Order Model (FOM) is represented by incompressible Navier-Stokes equations, discretized with a Finite Volume (FV) approach. Both the Newtonian and the Casson's constitutive laws are employed. The aim is to build a computational tool able to efficiently and accurately reconstruct the patterns of relevant hemodynamics indices related to the stasis of the blood in a physical parametrization framework including the cardiac output in the Newtonian case and also the plasma viscosity and the hematocrit in the non-Newtonian one. Many FOM-ROM comparisons are shown to analyze the performance of our approach as regards errors and computational speed-up.