The effect of turbulence modelling on the assessment of platelet activation.
J Biomech
; 128: 110704, 2021 11 09.
Article
em En
| MEDLINE
| ID: mdl-34482226
Pathological platelet activation by abnormal shear stresses is regarded as a main clinical complication in recipients of cardiovascular mechanical devices. In order to improve their performance computational fluid dynamics (CFD) are used to evaluate flow fields and related shear stresses. CFD models are coupled with mathematical models that describe the relation between fluid dynamics variables, and in particular shear stresses, and the platelet activation state (PAS). These models typically use a Lagrangian approach to compute the shear stresses along possible platelet trajectories. However, in the case of turbulent flow, the choice of the proper turbulence closure is still debated for both concerning its effect on shear stress calculation and Lagrangian statistics. In this study different numerical simulations of the flow through a mechanical heart valve were performed and then compared in terms of Eulerian and Lagrangian quantities: a direct numerical simulation (DNS), a large eddy simulation (LES), two Reynolds-averaged Navier-Stokes (RANS) simulations (SST k-ω and RSM) and a "laminar" (no turbulence modelling) simulation. Results exhibit a large variability in the PAS assessment depending on the turbulence model adopted. "Laminar" and RSM estimates of platelet activation are about 60% below DNS, while LES is 16% less. Surprisingly, PAS estimated from the SST k- ω velocity field is only 8% less than from DNS data. This appears more artificial than physical as can be inferred after comparing frequency distributions of PAS and of the different Lagrangian variables of the mechano-biological model of platelet activation. Our study indicates how much turbulence closures may affect platelet activation estimates, in comparison to an accurate DNS, when assessing blood damage in blood contacting devices.
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MEDLINE
Assunto principal:
Hidrodinâmica
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Modelos Teóricos
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article