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A Computational Study of Blood Flow Dynamics in the Pulmonary Arteries.

Fabio Marcinno'Alberto ZingaroIvan FumagalliLuca Dede'Christian Vergara
Published in: Vietnam journal of mathematics (2022)
In this work we study the blood dynamics in the pulmonary arteries by means of a 3D-0D geometric multiscale approach, where a detailed 3D model for the pulmonary arteries is coupled with a lumped parameters (0D) model of the cardiovascular system. We propose to investigate three strategies for the numerical solution of the 3D-0D coupled problem: the Splitting-Explicit and Implicit algorithms, where information are exchanged between 3D and 0D models at each time step at the interfaces, and the One-Way algorithm, where the 0D is solved first off-line. In our numerical experiments performed in a realistic patient-specific 3D domain with a physiologically calibrated 0D model, we discuss first the issue on instabilities that may arise when not suitable connections are considered between 3D and 0D models; second we compare the performance and accuracy of the three proposed numerical strategies. Finally, we report a comparison between a healthy and a hypertensive case, providing a preliminary result highlighting how our method could be used in future for clinical purposes.
Keyphrases
  • blood flow
  • pulmonary hypertension
  • machine learning
  • deep learning
  • blood pressure
  • health information