Comparison of reduced models for blood flow using Runge-Kutta discontinuous Galerkin methods
For researchers modeling blood flow in vascular networks, this study highlights which reduced models are most accurate under realistic conditions, but the comparison is incremental as it applies existing methods to known model variants.
This paper systematically compares several one-dimensional blood flow models (conservation vs. velocity-based, with different velocity profiles) using Runge-Kutta discontinuous Galerkin methods, finding that model choice significantly affects accuracy for physiologically relevant parameters and network topologies.
One-dimensional blood flow models take the general form of nonlinear hyperbolic systems but differ greatly in their formulation. One class of models considers the physically conserved quantities of mass and momentum, while another class describes mass and velocity. Further, the averaging process employed in the model derivation requires the specification of the axial velocity profile; this choice differentiates models within each class. Discrepancies among differing models have yet to be investigated. In this paper, we systematically compare several reduced models of blood flow for physiologically relevant vessel parameters, network topology, and boundary data. The models are discretized by a class of Runge-Kutta discontinuous Galerkin methods.