Abstract
Model verification, validation, and uncertainty quantification are essential procedures to estimate errors within cardiovascular flow modeling, where acceptable confidence levels are needed for clinical reliability. While more turbulent-like studies are frequently observed within the biofluid community, practical modeling guidelines are scarce. Verification procedures determine the agreement between the conceptual model and its numerical solution by comparing for example, discretization and phase-averaging-related errors of specific output parameters. This computational fluid dynamics (CFD) study presents a comprehensive and practical verification approach for pulsatile turbulent-like blood flow predictions by considering the amplitude and shape of the turbulence-related tensor field using anisotropic invariant mapping. These procedures were demonstrated by investigating the Reynolds stress tensor characteristics in a patient-specific aortic coarctation model, focusing on modeling-related errors associated with the spatiotemporal resolution and phase-averaging sampling size. Findings in this work suggest that attention should also be put on reducing phase-averaging related errors, as these could easily outweigh the errors associated with the spatiotemporal resolution when including too few cardiac cycles. Also, substantially more cycles are likely needed than typically reported for these flow regimes to sufficiently converge the phase-instant tensor characteristics. Here, higher degrees of active fluctuating directions, especially of lower amplitudes, appeared to be the most sensitive turbulence characteristics.
Highlights
Flow-phenotypes associated to highly disturbed hemodynamics play a essential role in the initiation and progression of many cardiovascular disease [1,2,3]
State-of-the-art modeling praxis has been well covered for laminar vascular flows [8,12,13], while general guidelines related to numerical predictions of turbulent-like hemodynamics have received less attention, in spite of the growing number of published turbulence-related computational fluid dynamics (CFD) studies within the research community
The present study aimed to investigate the Reynolds stress tensor characteristics impact from different CFD modeling strategies conventionally used for verification of pulsatile blood flow predictions, that is, the spatiotemporal resolution and phase-averaging sampling size
Summary
Flow-phenotypes associated to highly disturbed (chaotic and irregular) hemodynamics play a essential role in the initiation and progression of many cardiovascular disease [1,2,3]. Several recent studies have pointed to the importance of having adequate numerical solution strategies (e.g., proper spatial and temporal resolution as well as non-dissipative/diffusive discretization methods) to be able to capture weaker transitional flow regimes as well as high-frequency content in more developed turbulent flows [17,18,19,20,21]; which commonly used CFD methods may fail to predict. Part of these shortcomings may arguably be related to insufficient verification procedures. Such verification studies may manifest in misleading results and conclusions
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