CFD Simulations AC7-04: Difference between revisions
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=CFD Simulations= | =CFD Simulations= | ||
==Overview of CFD Simulations== | ==Overview of CFD Simulations== | ||
Large Eddy Simulations were carried out using the in-house, massively parallel and multiphysics YALES2BIO solver based on YALES2 [4] developed at CORIA (Rouen, France). YALES2BIO is dedicated to the simulation of blood flows at the macroscopic and microscopic scales. The base is a solver for the incompressible Navier-Stokes equations. The equations are discretised using a finite-volume fourth-order scheme, adapted to unstructured meshes [5,6]. The divergence-free | |||
property of the velocity field is ensured thanks to the projection method introduced by Chorin [7]. The velocity field is first advanced in time using a low-storage | |||
fourth-order Runge-Kutta scheme [6,8] in a prediction step. This predicted field is then corrected by a pressure gradient, obtained by solving a Poisson equation to calculate pressure. This equation is solved with the Deflated Preconditioned Conjugate Gradient algorithm [9]. YALES2BIO was validated and successfully used in many configurations relevant to cardiovascular biomechanics (see [10] for a list of publications). The boundary conditions applied at the inlet came from the data acquired during the experiment (2D cine PC-MRI). | |||
==Solution Strategy== | ==Solution Strategy== | ||
==Computational Domain== | ==Computational Domain== | ||
Revision as of 12:26, 26 July 2021
A pulsatile 3D flow relevant to thoracic hemodynamics: CFD - 4D MRI comparison
Application Challenge AC7-04 © copyright ERCOFTAC 2021
CFD Simulations
Overview of CFD Simulations
Large Eddy Simulations were carried out using the in-house, massively parallel and multiphysics YALES2BIO solver based on YALES2 [4] developed at CORIA (Rouen, France). YALES2BIO is dedicated to the simulation of blood flows at the macroscopic and microscopic scales. The base is a solver for the incompressible Navier-Stokes equations. The equations are discretised using a finite-volume fourth-order scheme, adapted to unstructured meshes [5,6]. The divergence-free property of the velocity field is ensured thanks to the projection method introduced by Chorin [7]. The velocity field is first advanced in time using a low-storage fourth-order Runge-Kutta scheme [6,8] in a prediction step. This predicted field is then corrected by a pressure gradient, obtained by solving a Poisson equation to calculate pressure. This equation is solved with the Deflated Preconditioned Conjugate Gradient algorithm [9]. YALES2BIO was validated and successfully used in many configurations relevant to cardiovascular biomechanics (see [10] for a list of publications). The boundary conditions applied at the inlet came from the data acquired during the experiment (2D cine PC-MRI).
Solution Strategy
Computational Domain
Boundary Conditions
Application of Physical Models
Numerical Accuracy
CFD Results
Contributed by: Morgane Garreau — University of Montpellier, France
© copyright ERCOFTAC 2021