Preliminary Implementation of Novel Bifurcation Pressure Loss Model in a Reduced-Order Cardiovascular Flow Model

Reduced-order models are valuable tools in cardiovascular modeling when high-fidelity simulations are prohibitively expensive, but they often suffer reduced accuracy due to the simplifications in their formulations.One such assumption is that pressure is constant over a bifurcation.The resistor-resistor-inductor model was recently proposed to predict the pressure difference over bifurcations as a function of flow rate, using coefficients extracted from the bifurcation geometry using machine learning.We implemented the resistor-resistor-inductor model (previously only tested on isolated bifurcations) in a reducedorder cardiovascular model for an idealized test geometry and compare the results to those achieved with standard bifurcation handling.We found improved accuracy (defined by comparison to high-fidelity simulations) for both steady and transient flows.