Transport enhancement mechanisms in open 
cavities

Horner, Marc; Metcalfe, Guy; Wiggins, Stephen; Ottino, Julio M.

doi:10.1017/s0022112001006917

Cited by 59 publications

(63 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since Aref's famous paper on chaotic advection (Aref 1984), KAM and Poincaré-Birkhoff fixed-point theorems have found many uses in describing the breakup of particle paths into self-similar structures within Lagrangian fluid mechanics. For larger perturbations, this geometry disintegrates to chaotic advection of particles as can be witnessed, for example, within a fixed rectangular cavity at moderate Reynolds numbers, which has been described by Ottino (1989) and Horner et al (2002).…”

Section: Particle Motion In the Perturbed Flowmentioning

confidence: 74%

Particle transport in a moving corner

Laine-Pearson¹,

Hydon²

2006

J. Fluid Mech.

View full text Add to dashboard Cite

This paper describes particle transport in Stokes flow in a two-dimensional corner whose walls oscillate, which is a simple model for particle transport in the pulmonary alveoli. Formally speaking, the wall motion produces a perturbation to the wellknown Moffatt corner eddies. However, this 'perturbation' is dominant as the corner is approached. The motion of particles is regular near to the corner. Far from the corner, chaotic motion within the main part of the flow is restricted to very small regions. We deduce that there is competition between the far-field motion that generates eddies and the wall motion. The relative strengths of these two motions determines whether a given particle moves regularly or chaotically. Consequently, there is an intermediate region in which chaotic transport is maximized. IntroductionThis mathematical study is motivated by an ongoing investigation into particle motion in the lung, led by Tsuda, that combines physiological, mathematical and computational studies of chaos in alveoli. These are cavities in the lower airway walls in which recirculation can occur. Tsuda, Henry & Butler (1995) examined the effects of cyclic expansion and contraction of alveolar walls on fluid flow in such a cavity by developing a numerical model. It was observed that low-Reynolds-number alveolar flow can be extremely complex; it was presumed that the alveolated duct structure and its time-dependent motion induced this complexity. In a related study, Haber et al. (2000) developed an analytical model of a cyclically expanding and contracting spherical alveolus and its vicinity. Their results supported the observation that there is a level of complexity of particle mixing in this region of the lungs. Moreover, the geometric features of structural alveolation and rhythmic expansion were given as the mechanism for chaotic mixing of particles. The numerical simulations of Henry, quantified the effects of cyclic expansion and contraction of an alveolated duct upon particle motion in the model alveoli. Lagrangian tracking of fluid particles indicated that the trajectories exhibit unpredictable stretched and folded patterns. These observations led Tsuda et al. (2002) to hypothesize that chaotic flow can occur in alveolated airways, and that this can result in flow-induced aerosol mixing and deposition deep in the lung. Tsuda's group tested this hypothesis by performing flow visualization experiments in excised animal lungs. They ventilated lungs with ultra-low-viscosity, polymerizable, Newtonian fluids of two colours. Each lung was first filled with white fluid, then ventilated with blue fluid for a number of cycles, ensuring that the Reynolds number remained low throughout the experiment. Then ventilation was halted and the fluids were polymerized to make casts that showed the final position of fluid particles. Recirculation had occurred in many alveoli, and there was substantial mixing of the fluids after just two cycles of inspiration and expiration.

show abstract

Section: Particle Motion In the Perturbed Flowmentioning

confidence: 74%

Particle transport in a moving corner

Laine-Pearson¹,

Hydon²

2006

J. Fluid Mech.

View full text Add to dashboard Cite

show abstract

“…Cavities, in general, are stagnant pockets, which show weak transport unless modified by some form of temporal perturbation. 7 The extent of mixing achieved by low-Re acinar flow, under normal breathing conditions, reversible wall motion and perfectly sinusoidal ductal flow is the topic of the current investigation. Improved understanding of acinar mixing helps in better prediction of particle transport, dispersion, and the ultimate deposition of fine particles deep in the lung.…”

Section: Discussionmentioning

confidence: 99%

Steady streaming: A key mixing mechanism in low-Reynolds-number acinar flows

et al. 2011

View full text Add to dashboard Cite

Study of mixing is important in understanding transport of submicron sized particles in the acinar region of the lung. In this article, we investigate transport in view of advective mixing utilizing Lagrangian particle tracking techniques: tracer advection, stretch rate and dispersion analysis. The phenomenon of steady streaming in an oscillatory flow is found to hold the key to the origin of kinematic mixing in the alveolus, the alveolar mouth and the alveolated duct. This mechanism provides the common route to folding of material lines and surfaces in any region of the acinar flow, and has no bearing on whether the geometry is expanding or if flow separates within the cavity or not. All analyses consistently indicate a significant decrease in mixing with decreasing Reynolds number ͑Re͒. For a given Re, dispersion is found to increase with degree of alveolation, indicating that geometry effects are important. These effects of Re and geometry can also be explained by the streaming mechanism. Based on flow conditions and resultant convective mixing measures, we conclude that significant convective mixing in the duct and within an alveolus could originate only in the first few generations of the acinar tree as a result of nonzero inertia, flow asymmetry, and large Keulegan-Carpenter ͑K C ͒ number.

show abstract

“…Chang and Sen (1994) called attention to the types of resistances to transfer from flows to solid surfaces and across fluid-fluid interfaces, identifying boundary layers, recirculation regions and stagnation streamlines, and also noted that chaotic mixing leads to lower resistances than non-chaotic mixing. As the introduction of chaotic trajectories requires modulation, and, therefore, a frequency of modulation, many groups have investigated the optimal frequency for increasing rates of transfer in a given system (Bryden and Brenner 1996, Ghosh et al 1992, Horner et al 2002. Although many have noted significant increases in rates of transfer with the introduction of chaotic trajectories (Bryden and Brenner 1999, Ganesan et al 1997, Lefevre et al 2003, others (ourselves included) have cautioned against equating increases in mixing efficiency due to chaotic flows with increased rates of transfer (Ganesan et al 1997, Ghosh et al 1998, Kirtland et al 2006.…”

Section: Introductionmentioning

confidence: 99%