{
  "id": "2406.12701",
  "version": "v1",
  "published": "2024-06-18T15:14:28.000Z",
  "updated": "2024-06-18T15:14:28.000Z",
  "title": "A hybrid reduced-order model for segregated fluid-structure interaction solvers in an ALE approach at high Reynolds number",
  "authors": [
    "Valentin Nkana Ngan",
    "Giovanni Stabile",
    "Andrea Mola",
    "Gianluigi Rozza"
  ],
  "categories": [
    "physics.flu-dyn",
    "cs.NA",
    "math.NA"
  ],
  "abstract": "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.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2024-06-18T15:14:28.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "high reynolds number",
      "hybrid reduced-order model",
      "segregated fluid-structure interaction solvers",
      "ale approach",
      "long short term memory"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}