Effect of computational domain size on inertial particle one-point statistics in open channel flow

Guiquan Wang*, Hyungwon John Park, David H. Richter

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

11 Citations (Scopus)
79 Downloads (Pure)

Abstract

Effects of the computational domain size on inertial particle one-point statistics are presented for direct numerical simulations of turbulent open channel flow at a moderate Reynolds number, which are seeded with two-way coupled particles at low volume concentration (less than 1.5×10−3, for such particle load the one-way coupled particles scheme is also valid). Particle one-point statistics across a wide range of Stokes numbers for a small domain (which captures only one or two large-scale motions (LSMs) in the inner layer) and a medium domain (which captures only one or two very large-scale motions (VLSMs) in the outer layer), are compared with those from a reference large domain. Although in single-phase flow the medium domain size simulation reproduces the same fluid one-point statistics as those in a large domain size, in particle-laden flow, comparisons show certain discrepancies in the particle one-point statistics, such as particle accumulation close to the wall (y+<10), maximum values of particle mean-squared streamwise velocity fluctuation, and particle Reynolds shear stress in the inner layer. The difference is larger for moderate Stokes numbers (St+=24.2 and 60.5) compared to low (St+=2.42) and very high (St+=908) Stokes numbers, which is also enhanced by using a small domain size.

Original languageEnglish
Article number103195
JournalInternational journal of multiphase flow
Volume125
Early online date9 Jan 2020
DOIs
Publication statusPublished - Apr 2020

Keywords

  • Domain size
  • Inertial particles
  • One-point statistics
  • Simulations
  • Wall turbulence
  • UT-Hybrid-D
  • 22/2 OA procedure

Fingerprint

Dive into the research topics of 'Effect of computational domain size on inertial particle one-point statistics in open channel flow'. Together they form a unique fingerprint.

Cite this