Particle dispersion in a multidimensional random flow with arbitrary temporal correlations
G. Falkovich,
V. Kazakov and
V. Lebedev
Physica A: Statistical Mechanics and its Applications, 1998, vol. 249, issue 1, 36-46
Abstract:
We study the statistics of relative distances R(t) between fluid particles in a spatially smooth random flow with arbitrary temporal correlations. Using the space dimensionality d as a large parameter we develop an effective description of Lagrangian dispersion. We describe the exponential growth of relative distances 〈R2(t)〉∝exp2λ̄t at different values of the ratio between the correlation and turnover times. We find the stretching correlation time which determines the dependence of R1R2 on the difference t1−t2. The calculation of the next cumulant of R2 shows that statistics of R2 is nearly Gaussian at small times (as long as d⪢1) and becomes log-normal at large times when large-d approach fails for high-order moments. The crossover time between the regimes is the stretching correlation time which surprisingly appears to depend on the details of the velocity statistics at t⪡τ. We establish the dispersion of the ln(R2) in the log-normal statistics.
Date: 1998
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437197004299
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:249:y:1998:i:1:p:36-46
DOI: 10.1016/S0378-4371(97)00429-9
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().