(6ab) Multiscale Multiphysics Modeling of Blood Clotting and Thrombus Bio-Chemomechanics in the Vasculature

• Multiphysics and Multiscale Modeling of Biological Systems and Complex Fluids (e.g., Blood)

• Coarse-grained Particle-based Methods (e.g., DPD) in Cellular and sub-cellular Modeling

• High-order Spectral Element Methods in Fluid Mechanics, Elastodynamics and Fluid-solid Interaction (FSI)

• Patient-specific and Probabilistic Modeling of Blood Flow in Arterial Network such as Coronary Arteries

Teaching Interests:

• Fluid Mechanics and Transport Phenomena

• Thermodynamics and Heat Transfer

• Introductory and Advanced Numerical Methods for Chemical Engineers

• Multiscale Modeling in Biophysics and Biomedical Engineering

ABSTRACT:

The process of clot formation and growth at the site of injury on a blood vessel wall involves a number of multiscale simultaneous processes including: multiple chemical reactions in the coagulation cascade, species transport, platelet adhesion as well as the hemodynamics and blood rheology. We model these processes at different levels of description (e.g. macro- vs. micro-scales). At continuum level, we solve Navier-Stokes equations for blood flow as well as the PDEs associated with advection-diffusion-reaction (ADR) of multiple species in the coagulation cascade using a spectral element solver. Depending on the required degrees of fidelity, platelets could be modeled either as a continuum concentration field or their transport and adhesion could be addressed by looking at individual platelets in a Lagrangian framework. At cellular and sub-cellular levels, however, particle-based methods such as Dissipative Particle Dynamics (DPD) have proven themselves to be more effective in addressing complex biological systems. I will discuss the recent developments in DPD framework that extends its applicability to transport problems, and discrete models of soft biological tissues. The major drawback of modeling such fully-resolved systems at the cellular scale, however, is the long-term computation of their whole course of evolutions. There are numerous biological and materials systems that evolve at slow rates (e.g. clotting), which make the simulations prohibitively long. I propose a multidelity technique based on co-krigging information fusion approach in statistical learning in order to facilitate acceleration in time. The multiscale framework's implications and future directions will also be discussed.