This paper formulates an efficient numerical method for solving the convection diffusion solute transport equations coupled to blood flow equations in vessel networks.The reduced coupled model describes the variations...This paper formulates an efficient numerical method for solving the convection diffusion solute transport equations coupled to blood flow equations in vessel networks.The reduced coupled model describes the variations of vessel cross-sectional area,radially averaged blood momentum and solute concentration in large vessel networks.For the discretization of the reduced transport equation,we combine an interior penalty discontinuous Galerkin method in space with a novel locally implicit time stepping scheme.The stability and the convergence are proved.Numerical results show the impact of the choice for the steady-state axial velocity profile on the numerical solutions in a fifty-five vessel network with physiological boundary data.展开更多
基金Puelz was supported in part by the Research Training Group in Modeling and Simulation funded by NSF via grant RTG/DMS-1646339Riviere acknowledged the support of NSF via Grant DMS 1913291.
文摘This paper formulates an efficient numerical method for solving the convection diffusion solute transport equations coupled to blood flow equations in vessel networks.The reduced coupled model describes the variations of vessel cross-sectional area,radially averaged blood momentum and solute concentration in large vessel networks.For the discretization of the reduced transport equation,we combine an interior penalty discontinuous Galerkin method in space with a novel locally implicit time stepping scheme.The stability and the convergence are proved.Numerical results show the impact of the choice for the steady-state axial velocity profile on the numerical solutions in a fifty-five vessel network with physiological boundary data.
