COMPUTATIONAL FLUID-STRUCTURE INTERACTION OF SOFT TISSUES USING AN IMMERSED-BOUNDARY METHOD
Fluid—structure interaction (FSI) of a soft tissue exists in many places in human body (e.g., heart and venous valves, vocal fold, blood vessels, kidney, aneurysm, sleep apnea). Computational modeling of these FSI problems has potential applications in diagnostics, disease management, surgical planning, and device design, and so on. We use an immersed-boundary method coupled with the finite-element method to solve the three-dimensional (3D) FSI problems involving complex anatomy and tissue deformations. A 3D domain decomposition strategy is incorporated in parallel computing to greatly accelerate the flow simulation. We consider specifically the FSI of aortic valve and vocal fold using the same computational framework, where blood and air are governed by the viscous incompressible Navier—Stokes equation. In the case of aortic valve, we focused on effect of the leaflets’ bending rigidity on blood flow, valve deformation, and the hemodynamic force on the valve. The thickness of the leaflets is varied to span a wide range of non-dimensional bending rigidity that is normalized by the transvalvular pressure gradient. The results suggest that there is an optimal range of bending rigidity for the valve. In addition to 3D simulations, we have also developed a novel one-dimensional (1D) unsteady flow model, which takes into consideration of valve movement and pressure loss. We use this 1D flow model in place of 3D flow in the FSI simulation. The results show that the hybrid simulation is able to capture reasonably well deformation of the leaflets, the valve opening area, and the flow rate. In the case of vocal fold, we aim to develop patient-specific modeling tools to simulate vibration of vocal fold during phonation. We have developed an efficient 1D flow model that can be used in estimation of unknown tissue stiffness or optimization of the implant in medialization laryngoplasty. Both idealized and realistic laryngeal models are set up to test the performance of the reduced-order FSI simulation. Results show that our model produces results that match well either with the 3D FSI simulation or with the in vivo phonation experiment.