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This work was developed with the aim of the doctoral grant SFRH/BD/144431/2019 and the projects UIDB/04436/2020, UIDB/04077/2020, funded by the Portuguese Foundation for Science and Technology (FCT) . This work was partially funded by Junta de Extremadura through grant IB20105 (partially financed by FEDER) . We thank the Programa Propio-Universidad Politecnica de Madrid, and the Ayuda Primeros Proyectos de Investigacion ETSII-UPM. We also thank Programa de Excelencia para el Profesorado Universitario de la Comunidad de Madrid for its financial support.

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Comparison of RANS and LES turbulent flow models in a real stenosis

Publicat a:International Journal Of Heat And Fluid Flow. 107 109340- - 2024-07-01 107(), DOI: 10.1016/j.ijheatfluidflow.2024.109340

Autors: Lopes, D; Puga, H; Teixeira, J; Lima, R; Grilo, J; Duenas-Pamplona, J; Ferrera, C

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This study focuses on the performance of various turbulence models in predicting hemodynamic variables within a patient-specific geometry of the Brachiocephalic trunk exhibiting a severe stenosis. Numerical simulations employing Reynolds-averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) models were conducted, comparing four RANS with two LES models. Results indicated significant differences in turbulent structures between RANS and LES models, with the k-omega RANS model closely approximating LES throughout the cardiac cycle. The velocity and Turbulent Kinetic Energy (TKE) results were consistent in the stenosis region due to the proximity to the inlet and plug flow conditions. However, notable disparities were observed in bifurcation and outlet regions. Time-Averaged Wall Shear Stress (TAWSS) comparisons revealed that the k-omega-based models provided closer agreement with LES, particularly in atherosclerosis-prone areas. The study highlights the limitations and strengths of each turbulence model, emphasizing the importance of model selection in simulating complex cardiovascular conditions. While RANS models demonstrated computational efficiency, their accuracy varied across regions. The effectiveness of the k-omega model in capturing the intricacies of such a complex flow field suggests its potential as a reliable and accurate tool for simulating physiological conditions with strong curvature and advanced stenosis.

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