Cellular Blood Flow Modeling with Smoothed Dissipative Particle Dynamics

Abstract

Computational modeling and simulation of cellular blood ow is highly desirable for understanding blood microcirculation and blood-related diseases, such as anemia, thrombosis and tumor, but it remains a challenge because the blood requires to be described as a dense suspension of di_erent types of cells and the microvessels continually bifurcate or merge into a complex network. A smoothed dissipative particle dynamics-immersed boundary method (SDPD-IBM) has been developed, integrating the uid ow and cell behavior to simulate physiological and pathological phenomena involved in blood ow. The SDPD is used to model the uid ow, the IBM is used to model the interactions between the uid and cells, and three phenomena are taken into account, cell deformation, aggregation and adhesion. The simulations consist of two parts: validation studies for the _delity of the SDPD-IBM, and case studies for its potential Computational modeling and simulation of cellular blood ow is highly desirable for understanding blood microcirculation and blood-related diseases, such as anemia, thrombosis and tumor, but it remains a challenge because the blood requires to be described as a dense suspension of di_erent types of cells and the microvessels continually bifurcate or merge into a complex network. A smoothed dissipative particle dynamics-immersed boundary method (SDPD-IBM) has been developed, integrating the uid ow and cell behavior to simulate physiological and pathological phenomena involved in blood ow. The SDPD is used to model the uid ow, the IBM is used to model the interactions between the uid and cells, and three phenomena are taken into account, cell deformation, aggregation and adhesion. The simulations consist of two parts: validation studies for the _delity of the SDPD-IBM, and case studies for its potential and usefulness. The validation studies consider the ow of pure uid, the mechanical behavior of cells, and the multi-outlet cellular ow, while the case studies include cells passing through simple vessels, successive bifurcations, and even a complex microvascular network. These studies concern the formation of a thrombus, the partitioning of red blood cells, and the metastasis of tumor cells. The SDPD-IBM has special advantages in modeling uid ows in complex domains and with uid-structure interactions, because the SDPD is convenient to model a complex domain by discrete particles, while the IBM is exible to model the interactions between the uid and structures.and usefulness. The validation studies consider the ow of pure uid, the mechanical behavior of cells, and the multi-outlet cellular ow, while the case studies include cells passing through simple vessels, successive bifurcations, and even a complex microvascular network. These studies concern the formation of a thrombus, the partitioning of red blood cells, and the metastasis of tumor cells. The SDPD-IBM has special advantages in modeling uid ows in complex domains and with uid-structure interactions, because the SDPD is convenient to model a complex domain by discrete particles, while the IBM is exible to model the interactions between the uid and structures.