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Dispersion in the large-deviation regime. Part I: shear flows and periodic flows

机译:在大偏差制度中的分散。第一部分:剪切流动和   周期性流动

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摘要

The dispersion of a passive scalar in a fluid through the combined action ofadvection and molecular diffusion is often described as a diffusive process,with an effective diffusivity that is enhanced compared to the molecular value.However, this description fails to capture the tails of the scalarconcentration distribution in initial-value problems. To remedy this, wedevelop a large-deviation theory of scalar dispersion that provides anapproximation to the scalar concentration valid at much larger distances awayfrom the centre of mass, specifically distances that are $O(t)$ rather than$O(t^{1/2})$, where $t \gg 1$ is the time from the scalar release. The theorycentres on the calculation of a rate function obtained by solving aone-parameter family of eigenvalue problems which we derive using twoalternative approaches, one asymptotic, the other probabilistic. We emphasisethe connection between large deviations and homogenisation: a perturbativesolution of the eigenvalue problems reduces at leading order to the cellproblem of homogenisation theory. We consider two classes of flows in somedetail: shear flows and cellular flows. In both cases, large deviationgeneralises classical results on effective diffusivity and captures newphenomena relevant to the tails of the scalar distribution. These includeapproximately finite dispersion speeds arising at large P\'eclet number$\mathrm{Pe}$ (corresponding to small molecular diffusivity) and, fortwo-dimensional cellular flows, anisotropic dispersion. Explicit asymptoticresults are obtained for shear flows in the limit of large $\mathrm{Pe}$. (Acompanion paper, Part II, is devoted to the large-$\mathrm{Pe}$ asymptotictreatment of cellular flows.) The predictions of large-deviation theory arecompared with Monte Carlo simulations that estimate the tails of concentrationaccurately using importance sampling.
机译:通过对流和分子扩散的结合作用,无源标量在流体中的分散通常被描述为扩散过程,与分子值相比,有效扩散率得到了增强。但是,该描述未能捕获标量浓度的尾巴。初值问题中的分布。为了解决这个问题,我们开发了一个标量色散的大偏差理论,该理论提供了一个标量浓度的近似值,该标量浓度在距质心更大的距离处有效,尤其是$ O(t)$而不是$ O(t ^ {1 / 2})$,其中$ t \ gg 1 $是标量释放的时间。理论中心是通过求解特征值问题的单参数族而获得的速率函数的计算,我们使用两种替代方法(一种渐近方法,另一种概率方法)推导了该特征参数问题。我们强调大偏差与均质化之间的联系:特征值问题的摄动解在均质化理论的细胞问题中处于领先地位。我们详细考虑了两类流:剪切流和细胞流。在这两种情况下,大的偏差一般化了有效扩散率的经典结果,并捕获了与标量分布的尾部相关的新现象。这些包括在大的Peclet数$ \ mathrm {Pe} $(对应于较小的分子扩散率)时产生的近似有限的分散速度,以及对于二维细胞流,各向异性的分散。在大\ mathrm {Pe} $的极限下,剪切流获得了显式渐近结果。 (伴奏论文的第二部分专门研究细胞流的大渐进处理。)大偏离理论的预测与蒙特卡洛模拟相比较,后者使用重要性抽样准确地估计了浓度的尾部。

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  • 作者

    Haynes, P. H.; Vanneste, J.;

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  • 年度 2014
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  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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