Structure of the stretching field in chaotic cavity flows

Liu, M.; Peskin, Richard L.; Muzzio, Fernando J.; Leong, C. W.

doi:10.1002/aic.690400802

Cited by 79 publications

(39 citation statements)

References 31 publications

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“…Induced by mixing, crystal growth progresses in an environment where the dispersion of magmas proceeds by chaotic stretching and folding (Liu 1994b;Perugini and Poli 2004;Perugini et al 2002;Perugini et al 2003). As a result, magma domains with differing characteristics may occur simultaneously and/or sequentially close to the growing mineral surface, and elements from all domains are incorporated due to their advection and diffusive fractionation (Perugini et al 2006).…”

Section: Introductionmentioning

confidence: 99%

Chaotic three-dimensional distribution of Ba, Rb, and Sr in feldspar megacrysts grown in an open magmatic system

Słaby

Śmigielski

Śmigielski³

et al. 2011

Contrib Mineral Petrol

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As has been demonstrated in recent years, the heterogeneities of coeval magmas can be more successfully revealed by zoned megacrysts rather than by analysis of the whole rocks hosting them. Here, the geochemical heterogeneities of feldspar megacrysts from the Karkonosze granite, Poland, are investigated by LA-ICP-MS. The crystals are the product of migration and growth in regions of poorly mixed magmas. 3D-modeling of the Ba, Sr, and Rb distributions emphasizes the importance of micro-domain growth morphologies. Two models of element behavior-a relative concentration model and a composition gradient model-provide a potentially effective tool for tracking the mixing process on a microscale. Measured concentrations of elements of different mobilities do not agree with what might be expected from the mixing of two end-member magmas. If mixing was the only process occurring, linear correlations between the concentrations of any two elements should be observed; this, however, is not the case. For combinations of any two of the three elements, modeling reveals differing non-linear correlations between concentrations. The megacryst heterogeneities provide an insight into how mixing magmas are chaotically advected to growing crystals and the degree of inter-magma element exchange between the magmas.

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Section: Introductionmentioning

confidence: 99%

Chaotic three-dimensional distribution of Ba, Rb, and Sr in feldspar megacrysts grown in an open magmatic system

Słaby

Śmigielski

Śmigielski³

et al. 2011

Contrib Mineral Petrol

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“…In order to compute, for instance, the yield of R at early time, it is useful to reformulate (23), (24) in terms of the independent variables η and T , giving …”

Section: Early Timementioning

confidence: 99%

“…First, there are two obvious candidates: an (averaged) Lyapunov exponent, which represents local stretching, and the topological entropy, which represents the growth rate of finite material lines, and which generally exceeds the Lyapunov exponent [43][44][45]. Second, the distribution of stretch rates along any material line is nonuniform [24], which causes difficulties in choosing a single value for µ. Third, it is not clear that exponential (rather than linear) growth of the interface is appropriate at early times, when this model is intended to be valid [46].…”

Section: Single Planar Interfacementioning

confidence: 99%

“…In this paper, we compare full twodimensional simulations with corresponding one-dimensional simulations of lamellar models (of varying degrees of sophistication), to evaluate the lat-ter. It is not a priori obvious how quantitatively accurate one should expect the lamellar models to be, given that they generally ignore many details of the striations generated by the flow, for instance: the curvature of the striations [22,23], the nonuniformity of the stretching [24], the nonuniformity of the striation widths [16], the presence of islands in the flow [6,9], and the continual regeneration of striations (by fluid mechanical stretching and folding, which lead to more, thinner striations, which then recombine diffusively). One would not be surprised to find that they perform well at low Péclet numbers, where diffusion rapidly homogenises the reactant distribution, and poorly at high Péclet numbers, where the flow details cited above become more significant.…”

Section: Introductionmentioning

confidence: 99%

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Chaotic mixing of a competitive–consecutive reaction

Cox

2004

Physica D: Nonlinear Phenomena

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The evolution of a competitive-consecutive chemical reaction is computed numerically in a two-dimensional chaotic fluid flow with initially segregated reactants. Results from numerical simulations are used to evaluate a variety of reduced models commonly adopted to model the full advection-reaction-diffusion problem. Particular emphasis is placed upon fast reactions, where the yield varies most significantly with Péclet number (the ratio of diffusive to advective time scales). When effects of the fluid mechanical mixing are strongest, we find that the yield of the reaction is underestimated by a one-dimensional lamellar model that ignores the effects of fluid mixing, but overestimated by two other lamellar models that include fluid mixing.

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“…Based on the results of Jana et al (19941, it is reasonable to anticipate that the presence of minor phase bodies may destabilize islands and thereby lead to improved mixing conditions in regions of the cavity occupied by similar fluids. Liu et al (1994b) examined in detail the stretching fields in a rectangular cavity filled with a single fluid to assess mixing efficiencies. Stretching was measured as the deformation in a population of advected material elements scattered throughout the cavity referenced to a very small initial length.…”

Section: Introductionmentioning

confidence: 99%