Non-Newtonian turbulent flow through aortic phantom: Experimental and computational study using magnetic resonance imaging and lattice Boltzmann method

Pavel Eichler, Radek Galabov, Radek Fučík, Kateřina Škardová, Tomáš Oberhuber, Petr Pauš, Jaroslav Tintěra, Radomír Chabiniok

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The necessity of using non-Newtonian models for hemodynamics in geometries mimicking large vessels is investigated. Phase-contrast magnetic resonance imaging (PC-MRI) measurements are performed on a specially-designed phantom representing the aorta while using several types of fluids. These measurements are compared against the results of the lattice Boltzmann method (LBM) computational fluid dynamics (CFD) simulator in 3D. On the phantom side, two types of non-Newtonian fluids (water-based solutions of glycerine with xanthan gum and sucrose with xanthan gum) and Newtonian fluid (clear water) are used in the experiments; three different acrylic plates are inserted to represent aortic stenosis of varying degrees; and two constant flow regimes with high and low flow rates are used. The CFD simulations in the geometry and inflow boundary conditions corresponding to each experiment are performed both with non-Newtonian and Newtonian approaches. Additionally, the accuracy of the PC-MRI flow measurements is assessed and discussed with respect to the known PC-MRI flow underestimation due to turbulence. Based on the type of stenosis and inflow rate, the results indicate that the Newtonian models produce comparable results with the experimentally acquired data, which is in favor of overall less expensive Newtonian models.

Original languageEnglish (US)
Pages (from-to)80-94
Number of pages15
JournalComputers and Mathematics with Applications
Volume136
DOIs
StatePublished - Apr 15 2023

Keywords

  • Carreau-Yasuda model
  • Lattice Boltzmann method
  • Non-Newtonian flow
  • Phase-contrast magnetic resonance imaging
  • Turbulent fluid flow

ASJC Scopus subject areas

  • Modeling and Simulation
  • Computational Theory and Mathematics
  • Computational Mathematics

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