Macroscopic Modeling

Particle-Continuum Modeling of Thrombus Formation in Dissections using a Force Coupling Method

In an ongoing NIH project we have been developing new multiscale biofluid mechanics models to predict thrombus size & shape in murine dissected arteries obtained at Professor Humphrey’s laboratory at Yale University. This work is focused mostly on biophysical modeling at different spatio-temporal scales. In particular, we examine in-silico hemodynamic conditions under which an intramural thrombus forms in aortic dissections and the bio-chemomechanical consequences of thrombus on the remnant wall. We have simulated the continuum hemodynamics with flowing platelets in reconstructed aortic geometries that are captured by multimodal ultrasound and OCT imaging techniques. To study the platelet motion and adhesion in a dissected vessel, we use a particle-continuum strategy based on a Force Coupling Method (FCM). FCM provides a flexible platform for “two-way” coupling of platelets, treated as rigid spherical particles, with the background flow. In FCM, translational velocities of a platelet are estimated by the local average of the fluid velocity weighted by a Gaussian kernel, which largely reduce the computational cost.

3D, 1D and Coupled 3D/1D Modeling of Arterial Blood Flow

With the advances in numerical methods and imaging techniques, image-based patient-specific computational fluid and solid mechanics permitted an entirely new application of vascular mechanics (e.g., in coronary artery disease and in cerebral aneurysms), where we can predict outcomes of alternate therapeutic interventions for individual patients, and design/evaluate medical devices. At the macroscale regime, blood predominately behaves as a Newtonian fluid, while the arterial wall constitutive law may be represented by linear elastic or hyperelastic materials. Typically, 3D simulations require considerable computational resources; hence, blood flow simulations in coronary trees can be performed using computationally inexpensive 1D models with lumped parameter networks used as the boundary conditions. In general, 1D models offer a robust predictive tool in computing pressure and flow distributions across the arterial tree. Moreover, they are computationally efficient tools that help us bridge the spatial gap and resolve blood flow from large arteries to small arterioles and capillaries in a 3D/1D coupled framework.