A stable and convergent method for Hodge decomposition of fluid-solid interaction

• Published in: arXiv.org
• Main Authors: Yoon, Gangjoon, Chohong Min, Kim, Seick
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 11.10.2016
• Subjects: Boundary conditions; Computational fluid dynamics; Convergence; Decomposition; Fields (mathematics); Fluid flow; Fluid-solid interactions; Incompressible flow; Incompressible fluids; Kinetic energy; Mathematics - Numerical Analysis; Numerical analysis; Numerical methods; Orthogonality; Poisson equation; Projection; Rigid structures; Stability
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.1610.03195

Fluid-solid interaction has been a challenging subject due to their strong nonlinearity and multidisciplinary nature. Many of the numerical methods for solving FSI problems have struggled with non-convergence and numerical instability. In spite of comprehensive studies, it has been still a challenge to develop a method that guarantees both convergence and stability. Our discussion in this work is restricted to the interaction of viscous incompressible fluid flow and a rigid body. We take the monolithic approach by Gibou and Min that results in an extended Hodge projection. The projection updates not only the fluid vector field but also the solid velocities. We derive the equivalence of the extended Hodge projection to the Poisson equation with non-local Robin boundary condition. We prove the existence, uniqueness, and regularity for the weak solution of the Poisson equation, through which the Hodge projection is shown to be unique and orthogonal. Also, we show the stability of the projection in a sense that the projection does not increase the total kinetic energy of fluid and solid. Also, we discusse a numerical method as a discrete analogue to the Hodge projection, then we show that the unique decomposition and orthogonality also hold in the discrete setting. As one of our main results, we prove that the numerical solution is convergent with at least the first order accuracy. We carry out numerical experiments in two and three dimensions, which validate our analysis and arguments.