Spatial distribution of inertial particles in turbulent Taylor–Couette flow

This study investigates the spatial distribution of inertial particles in turbulent Taylor–Couette flow. Direct numerical simulations are performed using a one-way coupled Eulerian–Lagrangian approach, with a fixed inner-wall Reynolds number of 2500 for the carrier flow, while the particle Stokes number ( $St$ ) varies from 0.034 to 1 for the dispersed phase. We first examine the issue of preferential concentration of particles near the outer-wall region. Employing two-dimensional Voronoï analysis, we observe a pronounced particle clustering with increasing $St$ , particularly evident in regions of low fluid velocity. Additionally, we investigate the concentration balance equation, inspired by the work of Johnson et al. ( J. Fluid Mech. , vol. 883, 2020, A27), to examine the particle radial distribution. We discern the predominant sources of influence, namely biased sampling, turbophoresis and centrifugal effects. Across all cases, centrifugal force emerges as the primary driver, causing particle migration toward the outer wall. Biased sampling predominantly affects smaller inertial particles, driving them toward the inner wall due to sampling within Taylor rolls with inward radial velocity. Conversely, turbophoresis primarily impacts larger inertial particles, inducing migration towards both walls where turbulent intensity is weaker compared with the bulk. With the revealed physics, our work provides a basis for predicting and controlling particle movement and distribution in industrial applications.

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Publication Details

Journal
Journal of Fluid Mechanics
Published
2025-03-04
DOI
https://doi.org/10.1017/jfm.2024.1143
Citations
3
Primary Topic
Particle Dynamics in Fluid Flows
Type
article
Field-Weighted Citation Impact
3.44
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article

Spatial distribution of inertial particles in turbulent Taylor–Couette flow

Hao Jiang, Kai Leong Chong, Bo-Fu Wang, Zhiming Lu et al.
3 citations
Journal of Fluid Mechanics
Particle Dynamics in Fluid Flows
3.44
article

Spatial distribution of inertial particles in turbulent Taylor–Couette flow

Hao Jiang, Kai Leong Chong, Bo-Fu Wang, Zhiming Lu, Xiaohui Meng, Jie Shen
article en
3 citations

Abstract

This study investigates the spatial distribution of inertial particles in turbulent Taylor–Couette flow. Direct numerical simulations are performed using a one-way coupled Eulerian–Lagrangian approach, with a fixed inner-wall Reynolds number of 2500 for the carrier flow, while the particle Stokes number ( $St$ ) varies from 0.034 to 1 for the dispersed phase. We first examine the issue of preferential concentration of particles near the outer-wall region. Employing two-dimensional Voronoï analysis, we observe a pronounced particle clustering with increasing $St$ , particularly evident in regions of low fluid velocity. Additionally, we investigate the concentration balance equation, inspired by the work of Johnson et al. ( J. Fluid Mech. , vol. 883, 2020, A27), to examine the particle radial distribution. We discern the predominant sources of influence, namely biased sampling, turbophoresis and centrifugal effects. Across all cases, centrifugal force emerges as the primary driver, causing particle migration toward the outer wall. Biased sampling predominantly affects smaller inertial particles, driving them toward the inner wall due to sampling within Taylor rolls with inward radial velocity. Conversely, turbophoresis primarily impacts larger inertial particles, inducing migration towards both walls where turbulent intensity is weaker compared with the bulk. With the revealed physics, our work provides a basis for predicting and controlling particle movement and distribution in industrial applications.

Journal of Fluid MechanicsVol. 1006
Shanghai University (CN), Southern University of Science and Technology (CN)
Openalex Percentile: Top 9%
Particle Dynamics in Fluid Flows
3.44
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Spatial distribution of inertial particles in turbulent Taylor–Couette flow — Hao Jiang, Kai Leong Chong, et al. · Journal of Fluid Mechanics (2025) | TGRS Research Map | TGRS