An image-guided computational approach to inversely determine in vivo material properties and model flow-structure interactions of fish fins

Abstract We present an image-guided computational approach for inversely determining in vivo material properties of fish fins and simulating flow-structure interactions (FSI) of fin deformations based on a highly realistic hybrid membrane-beam structure. This approach is established by coupling an imaged-based reconstruction, a genetic-algorithm (GA)-based optimization, a finite-element-method (FEM)-based computational structural dynamics model and an immersed-boundary-method (IBM)-based computational fluid dynamics (CFD) solver. An inverse-problem procedure is developed to determine material properties from prescribed kinematic motions obtained from high-speed images. The procedure is validated through two tests including a flexible pitching plate and a shell-beam structured flexible plate in heaving motion. The FSI model (forward problem) is validated through two benchmark tests including flow-induced vibration of a flexible beam attached to a fixed cylinder and a flexible pitching plate in a uniform flow. This integrated method is then applied to the FSI analysis of propulsion of a rainbow trout caudal fin with a specific focus on the fin material properties, fin deformations, hydrodynamic performances and flow structures. We demonstrate that, by using reconstructed kinematics and deformation obtained from the high-speed videos, the non-uniform material properties of the fin can be determined through the inverse problem procedure. A fully-coupled FSI simulation is then carried out based on the outcome of the inverse problem. The results have shown the feasibility of the present integrated approach in accurately modeling and quantitatively evaluating flexible-fin kinematics and hydrodynamics in swimming in terms of both chordwise and spanwise deformations, thrust and lateral forces, and vortex dynamics.