Reduced order modeling of parametrized pulsatile blood flows: Hematocrit percentage and heart rate

Catalina Farías, Camilo Bayona-Roa, Ernesto Castillo, Roberto C. Cabrales, Ricardo Reyes

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This paper numerically evaluates the accuracy and performance of a stabilized finite element Reduced Order Modelling (ROM) approach that is designed to simulate pulsatile blood flows. The method is able to estimate fluid flow parametric solutions of interest in hemodynamics by considering the hematocrit percentage (Hct%) and the heart rate (fc) as parameters. The method estimates off-trained parametric scenarios which have not been included in the training data set composing the ROM basis and that can adopt arbitrary values from specific patient conditions. The hematocrit percentages modifies the viscous properties of blood, which are incorporated into the problem physics through a power-law model. The hematocrit percentages are 5≤Hct%≤50, ranging from severe anemia to physiological values. The pulsatile flow condition is modeled via a Womersley function, with fcbpm (beats per minute) ranging between 60bpm≤fc≤120bpm. These frequencies comprise physiological conditions of patients at rest and tachycardia or moderate exercise. Two-and-three-dimensional flows are simulated inside a representative geometry of a carotid artery, where the accuracy is tested by studying the effect of the number of components of the ROM approximating basis and the number of sampling points composing the training data set. The parametric calculation verifies that the proposed approach constitutes a valuable computational tool for simulating complex fluid flow hemodynamics and can be applied to clinical decision-making.

Original languageEnglish
Article number103943
JournalInternational Journal of Engineering Science
Volume193
DOIs
StatePublished - 01 Dec 2023

Keywords

  • Blood Rheology
  • Hemodynamics
  • Parametrized Solutions
  • Reduced-order-modeling
  • Variational Multiscale Method

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