Rotation of Nonspherical Particles in Turbulent Channel Flow

Zhao, Lihao; Challabotla, Niranjan Reddy; Andersson, Helge I.; Variano, Evan

doi:10.1103/physrevlett.115.244501

Cited by 108 publications

(113 citation statements)

References 38 publications

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“…[25] were in very good agreement with the experimental data in all regimes, even at low particle aspect ratios, i.e. A = O(10), and large particle Reynolds number, i.e., Re = O (10). Moreover, the pseudolinear formulation using a generalized mobility matrix that was introduced in this work provided excellent results while reducing considerably the computational cost.…”

Section: -18supporting

confidence: 73%

“…Conversely, there is an abundant literature on numerical studies with fibers and ellipsoids of different aspect ratios in turbulence. These studies have provided a better knowledge of the particle rotational dynamics, showing a preferential alignment of rods with the local vorticity and of disks perpendicular to vorticity in isotropic turbulence [6,7] as well as wall turbulence [8][9][10]. In most of these studies, inertia is added to the problem by considering a finite Stokes number, characterizing the response time of the particle compared to the flow time scale, while keeping a low particle Reynolds number.…”

Section: Introductionmentioning

confidence: 99%

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Inertial effects on fibers settling in a vortical flow

López

Guazzelli

2017

Phys. Rev. Fluids

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Particle sedimentation under a turbulent flow is a fundamental problem that has numerous applications in natural and industrial processes. In particular, the motion of anisotropic particles yields complex dynamics whose features are not completely understood in the presence of inertia. While inertia is generally introduced through a finite particle response time, many processes involve particles with a low response time but a finite particle Reynolds number. In this case, theoretical models are rather sparse, and their validity has never been tested against controlled experiments. This work precisely proposes a careful testing of fiber sedimentation and advection models at finite particle Reynolds number against well-controlled two-dimensional experiments. We show that the slender body limit model has strong limitations at finite aspect ratio and Reynolds number, and we identify the main corrections that need to be incorporated into this basic model by expanding on the work of Khayat and Cox [J. Fluid Mech. 209, 435 (1989)]. Additionally, we present the different models under a uniform framework, providing a simpler and clearer use. Using the validated inertial model, we show the importance of the ratio between the settling speed and the typical flow velocity for describing the fiber motion.

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Section: -18supporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Inertial effects on fibers settling in a vortical flow

López

Guazzelli

2017

Phys. Rev. Fluids

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“…This condition ensures that the gradient dynamics is 'persistent' [70], in the sense that the fluid-velocity gradients change much more slowly than the angular particle dynamics relaxes. Equation (35) indicates that the persistent limit is achieved provided that A | |Sv is large enough, at least for the overdamped dynamics (26). For smaller values of Sv the overdamped theory is modified in at least two ways.…”

Section: Two-dimensional Dynamics In the Overdamped Limitmentioning

confidence: 99%

“…Second, the time scale at which the particle samples the fluid-velocity gradients is different: at small Sv this time scale is no longer τ s . Instead the Kolmogorov time τ K must be used in equation (35). Here we do not discuss this limit further.…”

Section: Two-dimensional Dynamics In the Overdamped Limitmentioning

confidence: 99%

“…The nature of the turbulent velocity fluctuations is determined by the Taylor-scale Reynolds number l Re . If the particles are so small that they just follow the flow and that any inertial corrections to the fluid torque are negligible ( = = Re Re 0 p s ), then the angular dynamics of small crystals in turbulence is well understood [10,[29][30][31][32][33][34][35][36][37][38]. The particle orientation responds to local vorticity and strain through Jeffery's equation [29].…”

Section: Introductionmentioning

confidence: 99%

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Effect of fluid inertia on the orientation of a small prolate spheroid settling in turbulence

et al. 2019

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We study the angular dynamics of small non-spherical particles settling in a turbulent flow, such as ice crystals in clouds, aggregates of organic material in the oceans, or fibres settling in turbulent pipe flow. Most solid particles encountered in Nature are not spherical, and their orientations affect their settling speeds, as well as their collision and aggregation rates in suspensions. Whereas the random action of turbulent eddies favours an isotropic distribution of orientations, gravitational settling breaks the rotational symmetry. The precise nature of the symmetry breaking, however, is subtle. We demonstrate here that the fluid-inertia torque plays a dominant role in the problem. As a consequence rod-like particles tend to settle in turbulence with horizontal orientation, the more so the larger the settling number Sv (a dimensionless measure of the settling speed). For large Sv we determine the fluctuations around this preferential horizontal orientation for prolate particles with arbitrary aspect ratios, assuming small Stokes number St (a dimensionless measure of particle inertia). Our theory is based on a statistical model representing the turbulent velocity fluctuations by Gaussian random functions. This overdamped theory predicts that the orientation distribution is very narrow at large Sv, with a variance proportional to -Sv 4 . By considering the role of particle inertia, we analyse the limitations of the overdamped theory, and determine its range of applicability. Our predictions are in excellent agreement with numerical simulations of simplified models of turbulent flows. Finally we contrast our results with those of an alternative theory predicting that the orientation variance is proportional to -Sv 2 at large Sv.

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