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Clustering by Mixing Flows

机译:通过混合流进行聚类

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We calculate the Lyapunov exponents for particles suspended in a random three-dimensional flow, concentrating on the limit where the viscous damping rate is small compared to the inverse correlation time. In this limit Lyapunov exponents are obtained as a power series in ε, a dimensionless measure of the particle inertia. Although the perturbation generates an asymptotic series, we obtain accurate results from a Pade-Borel summation. Our results prove that particles suspended in an incompressible random mixing flow can show pronounced clustering when the Stokes number is large and we characterize two distinct clustering effects which occur in that limit.
机译:我们计算了悬浮在随机三维流中的粒子的Lyapunov指数,重点是粘性阻尼速率与逆相关时间相比较小的极限。在此极限下,Lyapunov指数作为ε的幂级数获得,即粒子惯性的无量纲度量。尽管摄动产生一个渐近级数,但我们从Pade-Borel求和中获得了准确的结果。我们的结果证明,当斯托克斯数很大时,悬浮在不可压缩的随机混合流中的颗粒可以显示出明显的聚类,并且我们表征了在该极限内发生的两种不同的聚类效果。

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