Adaptive Immersed Mesh Method (AIMM) for Fluid Structure Interaction
R. Nemer, A. Larcher, E. Hachem
TL;DR
The paper introduces the Adaptive Immersed Mesh Method (AIMM), a hybrid Fluid-Structure Interaction framework that couples a Lagrangian solid solver with an Eulerian fluid solver by immersing the solid in a shared fluid–solid mesh and tracking the interface via a level-set function. Both solvers are stabilized with Variational Multi-Scale (VMS) methods to enable first-order unstructured elements while maintaining stability, and anisotropic mesh adaptation concentrates refinement along the interface using an edge-based error estimator and gradient recovery. The AIMM coupling enforces two-way velocity and stress continuity at the FSI interface and leverages a moving mesh approach to accurately resolve boundary layers and contact surfaces. The method is validated on 2D benchmarks and demonstrated on 3D FSI problems (pillar and flap configurations), showing good agreement with literature and experimental data, and highlighting its potential for robust, scalable FSI in complex, slender structures.
Abstract
Our paper proposes an innovative approach for modeling Fluid-Structure Interaction (FSI). Our method combines both traditional monolithic and partitioned approaches, creating a hybrid solution that facilitates FSI. At each time iteration, the solid mesh is immersed within a fluid-solid mesh, all while maintaining its independent Lagrangian hyperelastic solver. The Eulerian mesh encompasses both the fluid and solid components and accommodates various physical phenomena. We enhance the interaction between solid and fluid through anisotropic mesh adaptation and the Level-Set methods. This enables a more accurate representation of their interaction. Together, these components constitute the Adaptive Immersed Mesh Method (AIMM). For both solvers, we utilize the Variational Multi-Scale (VMS) method, mitigating potential spurious oscillations common with piecewise linear tetrahedral elements. The framework operates in 3D with parallel computing capabilities. Our methods accuracy, robustness, and capabilities are assessed through a series of 2D numerical problems. Furthermore, we present various three-dimensional test cases and compare their results to experimental data.
