  This study introduces a first step for constructing a hybrid reduced-order
models (ROMs) for segregated fluid-structure interaction in an Arbitrary
Lagrangian-Eulerian (ALE) approach at a high Reynolds number using the Finite
Volume Method (FVM). The ROM is driven by proper orthogonal decomposition (POD)
with hybrid techniques that combines the classical Galerkin projection and two
data-driven methods (radial basis networks , and neural networks/ long short
term memory). Results demonstrate the ROM ability to accurately capture the
physics of fluid-structure interaction phenomena. This approach is validated
through a case study focusing on flow-induced vibration (FIV) of a pitch-plunge
airfoil at a high Reynolds number 10000000.
