Stochastic models for capturing dispersion in particle-laden flows
| Autor: | Vahid Tavanashad, Shankar Subramaniam, Jesse Capecelatro, Aaron M. Lattanzi |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Physics
Inertial frame of reference Stochastic modelling Mechanical Engineering Direct numerical simulation Particle-laden flows Mechanics Condensed Matter Physics 01 natural sciences 010305 fluids & plasmas Mechanics of Materials Drag 0103 physical sciences Dispersion (optics) Particle velocity 010306 general physics Stokes number |
| Zdroj: | Journal of Fluid Mechanics. 903 |
| ISSN: | 1469-7645 0022-1120 |
| DOI: | 10.1017/jfm.2020.625 |
| Popis: | This study provides a detailed account of stochastic approaches that may be utilized in Eulerian–Lagrangian simulations to account for neighbour-induced drag force fluctuations. The frameworks examined here correspond to Langevin equations for the particle position (PL), particle velocity (VL) and fluctuating drag force (FL). Rigorous derivations of the particle velocity variance (granular temperature) and dispersion resulting from each method are presented. The solutions derived herein provide a basis for comparison with particle-resolved direct numerical simulation. The FL method allows for the most complex behaviour, enabling control of both the granular temperature and dispersion. A Stokes number , the fluctuating drag forces are highly inertial and the FL scheme departs significantly from the VL scheme. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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