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.

翻译：本研究提出了在高雷诺数下，基于有限体积法（FVM）的任意拉格朗日-欧拉（ALE）框架中，为分离式流固耦合问题构建混合降阶模型（ROM）的初步步骤。该降阶模型由本征正交分解（POD）驱动，并采用混合技术，结合了经典的伽辽金投影与两种数据驱动方法（径向基函数网络，以及神经网络/长短期记忆网络）。结果表明，该降阶模型能够准确捕捉流固耦合现象的物理本质。此方法通过一个专注于高雷诺数（Re = 10000000）下俯仰-沉浮翼型流致振动（FIV）的案例研究得到了验证。