{
  "id": "2205.04979",
  "version": "v1",
  "published": "2022-05-10T15:36:03.000Z",
  "updated": "2022-05-10T15:36:03.000Z",
  "title": "Multi-fidelity uncertainty quantification of particle deposition in turbulent pipe flow",
  "authors": [
    "Yuan Yao",
    "Xun Huan",
    "Jesse Capecelatro"
  ],
  "categories": [
    "physics.flu-dyn"
  ],
  "abstract": "Particle deposition in fully-developed turbulent pipe flow is quantified taking into account uncertainty in electric charge, van der Waals strength, and temperature effects. A framework is presented for obtaining variance-based sensitivity in multiphase flow systems via a multi-fidelity Monte Carlo approach that optimally manages model evaluations for a given computational budget. The approach combines a high-fidelity model based on direct numerical simulation and a lower-order model based on a one-dimensional Eulerian description of the two-phase flow. Significant speedup is obtained compared to classical Monte Carlo estimation. Deposition is found to be most sensitive to electrostatic interactions and exhibits largest uncertainty for mid-sized (i.e., moderate Stokes number) particles.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2022-05-10T15:36:03.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "turbulent pipe flow",
      "multi-fidelity uncertainty quantification",
      "particle deposition",
      "van der waals strength",
      "multi-fidelity monte carlo approach"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}