Published online by Cambridge University Press: 12 February 2014
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  $\mathit{Re}_{\lambda }=400$. Both the energy dissipation rate
$\mathit{Re}_{\lambda }=400$. Both the energy dissipation rate  $\epsilon $ and the local time-averaged
$\epsilon $ and the local time-averaged  $\epsilon _{\tau }$ agree rather well with the lognormal distribution hypothesis. Several statistics are then examined. It is found that the autocorrelation function
$\epsilon _{\tau }$ agree rather well with the lognormal distribution hypothesis. Several statistics are then examined. It is found that the autocorrelation function  $\rho (\tau )$ of
$\rho (\tau )$ of  $\ln (\epsilon (t))$ and variance
$\ln (\epsilon (t))$ and variance  $\sigma ^2(\tau )$ of
$\sigma ^2(\tau )$ of  $\ln (\epsilon _{\tau }(t))$ obey a log-law with scaling exponent
$\ln (\epsilon _{\tau }(t))$ obey a log-law with scaling exponent  $\beta '=\beta =0.30$ compatible with the intermittency parameter
$\beta '=\beta =0.30$ compatible with the intermittency parameter  $\mu =0.30$. The
$\mu =0.30$. The  $q{\rm th}$-order moment of
$q{\rm th}$-order moment of  $\epsilon _{\tau }$ has a clear power law on the inertial range
$\epsilon _{\tau }$ has a clear power law on the inertial range  $10<\tau /\tau _{\eta }<100$. The measured scaling exponent
$10<\tau /\tau _{\eta }<100$. The measured scaling exponent  $K_L(q)$ agrees remarkably with
$K_L(q)$ agrees remarkably with  $q-\zeta _L(2q)$ where
$q-\zeta _L(2q)$ where  $\zeta _L(2q)$ is the scaling exponent estimated using the Hilbert methodology. All of these results suggest that the dissipation along Lagrangian trajectories could be modelled by a multiplicative cascade.
$\zeta _L(2q)$ is the scaling exponent estimated using the Hilbert methodology. All of these results suggest that the dissipation along Lagrangian trajectories could be modelled by a multiplicative cascade.