Crucial Aspects for Using Computational Fluid Dynamics as a Predictive Evaluation Tool for Blood Pumps.

ASAIO J 2019 Jun 6. Epub 2019 Jun 6.

From the Department of Cardiovascular Engineering, Institute of Applied Medical Engineering, Helmholtz Institute, RWTH Aachen University, Aachen, Germany.

The suitability of computational fluid dynamics (CFD) as a regulatory tool for safety assessment of medical devices is still limited: A lack of standardized validation and evaluation methods impairs the quantitative comparability and reliability of simulation studies, particularly regarding the assessment of hemocompatibility. This study investigated important aspects of validation and verification for three common turbulence modeling approaches (laminar, k-ω shear stress transport [SST] and stress-blended eddy simulation [SBES]) and three different mesh refinements. Simulation results for pressure head, characteristic velocity, and shear stress for the benchmark blood pump model of the FDA critical path initiative were compared with its published experimental results. For the highest mesh resolution, all three models predicted the hydraulic pump characteristics with a relative deviation averaged over six operating conditions below 6.1%. In addition, the SBES model showed an accurate agreement of the characteristic velocity field in the pump's diffusor region (relative error <2.9%), while the laminar and SST model calculated significantly elevated and deviating velocity amplitudes (>43.6%). The ability to quantify shear stress is fundamental for the prediction of blood damage. In this respect, this study demonstrated that: 1) a close agreement and validation of both pressure head and characteristic velocity was feasible and 2) the shear stress quantification demanded higher near-wall mesh resolutions, although such high resolutions were not required for the validation of only pressure heads or velocity. Hence, a mesh verification analysis for shear stresses may prove significant for the development of credible CFD blood damage predictions in the future.

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http://dx.doi.org/10.1097/MAT.0000000000001023DOI Listing
June 2019
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