Published June 19, 2024 | Version v1
Journal article Open

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

  • 1. Czech Technical University in Prague
  • 2. Institute for clinical and experimental medicine - IKEM

Description

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.

Notes

The work was supported by: the Ministry of Health of the Czech Republic project No. NV19-08-00071; the project National Institute for Research of Metabolic and Cardiovascular Diseases (Programme EX-CELES, Project No. LX22NPO5104) - Funded by the European Union (Next Generation EU) ; the Ministry of Education, Youth and Sports of the Czech Republic (MEYS) under the OP RDE grant number CZ.02.1.01/0.0/0.0/16_019/0000765 Research Center for Informatics; and by the project SGS20/184/OHK4/3T/14 of the Student Grant Agency of the Czech Technical University in Prague. This work was also supported by the Inria-UTSW Associated Team TOFMOD and by Institutional Support MHCZ-DRO (Institute for Clinical and Experimen-tal Medicine - IKEM, IN 00023001) .

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