Lagrangian Cascade in Three-Dimensional Homogeneous and Isotropic Turbulence
arXiv:1401.4210 · doi:10.1017/jfm.2014.1
Abstract
In this work, the scaling statistics of the dissipation along Lagrangian trajectories are investigated by using fluid tracer particles obtained from a high resolution direct numerical simulation with . Both the energy dissipation rate and the local time averaged agree rather well with the lognormal distribution hypothesis. Several statistics are then examined. It is found that the autocorrelation function of and variance of obey a log-law with scaling exponent compatible with the intermittency parameter . The th-order moment of has a clear power-law on the inertial range . The measured scaling exponent agrees remarkably with where is the scaling exponent estimated using the Hilbert methodology. All these results suggest that the dissipation along Lagrangian trajectories could be modelled by a multiplicative cascade.
10 pages with 7 figures accepted for Journal of Fluid Mechanics as Rapids
References in corpus (5)
- Multifractal statistics of Lagrangian velocity and acceleration in turbulence
- Lagrangian dynamics and statistical geometric structure of turbulence
- Lagrangian Velocity Statistics in Turbulent Flows: Effects of Dissipation
- Second order structure function in fully developed turbulence
- A causal multifractal stochastic equation and its statistical properties
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