A fast approach to estimating Windkessel model parameters for patient-specific multi-scale CFD simulations of aortic flow

Computational fluid dynamics (CFD) study of hemodynamics in the aorta can provide a comprehensive analysis relevant cardiovascular diseases. One trending approach is to couple three-element Windkessel model with patient-specific CFD simulations form multi-scale that captures more realistic flow fields. However, case-specific parameters (e.g., Rc, Rp, and C) for must be tuned reflect conditions. In this study, we propose fast estimate these under both physiological pathological The consists following steps: (1) finding geometric resistances each branch using steady simulation; (2) pattern search algorithm from Matlab toolbox parameter spaces by solving circuit system consideration resistances; (3) performing modeling aortic optimized parameters. method was validated through series numerical experiments show flexibility robustness, including distributions at downstream healthy or stenosed geometries. This demonstrates flexible computationally efficient way capture aorta, facilitating personalized biomechanical flow.