In 2008 the International Collaboration for Turbulence Research compared eight data sets — three particle-tracking experiments and five direct numerical simulations spanning Taylor-scale Reynolds numbers – — and found that Lagrangian velocity structure functions up to order collapse onto a common behavior, and that a multifractal description extended to the dissipative range, with a free crossover parameter controlling the transition near the Kolmogorov time, captures intermittency over three decades of time lags. The issues the Letter itself identified remain unresolved. First, it is not known whether a strong mean flow or persistent large-scale anisotropy, as in turbulent jets and wall-bounded turbulence, breaks the recovery of small-scale Lagrangian universality, or whether the multifractal parametrization must be modified in such flows. Second, the proposed physical identification of — different values corresponding to different statistical weights of vortex-filament trapping along particle trajectories — has never been established quantitatively. Third, higher-order Lagrangian moments () were beyond statistical convergence in 2008; direct numerical simulations now reach and orders near , but the multifractal prediction for dissipative-range and acceleration statistics is contested, and converged experimental high-order data remain scarce. The problem is to settle the universality and the physical content of the multifractal description of Lagrangian intermittency outside the regime in which it was validated.
Background
A fluid particle advected by a turbulent flow defines Lagrangian velocity increments ; the moments are the Lagrangian velocity structure functions (LVSF). Scale separation is measured by the Taylor-scale Reynolds number , since the ratio of the large integral time to the Kolmogorov dissipative time (the shortest dynamically relevant time, set by the mean energy dissipation rate and the viscosity) grows as . Dimensional (Kolmogorov 1941) reasoning predicts in the inertial range , but measured increment distributions develop increasingly heavy, non-Gaussian tails at small — intermittency — which manifests as anomalous scaling exponents . Intermittency can be monitored scale by scale through the local exponent , which flattens toward an inertial-range plateau only for well above and shows a pronounced dip around .
In the Parisi–Frisch multifractal (MF) picture, Eulerian velocity increments scale as on sets of fractal dimension , and the dimensional bridge extends this to time increments along trajectories, with the dissipative time itself fluctuating, . To describe Lagrangian data at all lags, including the dissipative range, Chevillard et al. (2003) and Biferale et al. (2004) introduced a smooth crossover formula for the conditional increment — Eq. (4) of the source Letter — built from the powers and joined through a free parameter that controls the sharpness of the transition near : it reduces to inertial-range scaling at large lags and to smooth, differentiable behavior at small lags, and it fixes the depth of the dip of around . Vortex filaments — intense, thin, tube-like vortical structures at dissipative scales — can trap tracer particles for times of order ; simulations cited in the Letter showed that depleting or enhancing the probability of particle trapping in filaments depletes or enhances exactly this dip.
The source Letter (International Collaboration for Turbulence Research, Phys. Rev. Lett. 100, 254504 (2008)) compared eight data sets — three experiments (particle tracking velocimetry, the optical reconstruction of tracer trajectories, and acoustic Doppler tracking, which infers tracer velocity from the Doppler shift of sound scattered by the tracers; –) and five direct numerical simulations (DNS, –) — and found (i) that the local exponents , fourth order being the highest order converged in all data sets, collapse across flows with isotropy recovered at small lags, evidencing universality of the Lagrangian energy cascade; and (ii) that the MF description, with and Eulerian taken from longitudinal or transverse fits to the log-Poisson cascade spectrum (a standard intermittent-cascade ansatz for ), captures the data across three decades of for (with asymptotic predictions and from the two spectra). The validated regime is thus statistically quasi-isotropic homogeneous flows and moments up to , with the crossover parameter a fitted constant of contested physical meaning (a related review, Chevillard et al. 2012, denotes the analogous sharpness parameter and reports fitted values from about 1 to 4 across data sets, attributing some of the variation to finite-tracer-size filtering).
Problem Statement
Determine whether the universal multifractal description of small-scale Lagrangian intermittency established by the International Collaboration for Turbulence Research (Phys. Rev. Lett. 100, 254504 (2008)) extends beyond the regime in which it was validated — statistically quasi-isotropic flows and velocity-increment moments up to order — by addressing three linked questions on the validation and physical grounding of that description:
(1) Strong mean flow and persistent anisotropy. Does the observed collapse of the normalized local exponents across independent data sets — the recovery of small-scale Lagrangian universality, with isotropy restored at small time lags — survive flows with a strong mean flow or persistent large-scale anisotropy, such as turbulent jets and wall-bounded turbulence? If it does not, determine how the multifractal parametrization (including the crossover parameter ) must be modified for such flows.
(2) Physical content of the crossover parameter. The source Letter proposed that different values of correspond to different statistical weights of vortex filaments along particle trajectories. Establish or refute this quantitatively: relate — or equivalently the crossover shape it controls near , including the dip of — to measurable statistics of particle trapping in vortex filaments (for example, residence-time or trapping-event statistics conditioned on flow topology along trajectories).
(3) Higher-order statistics. Test whether (i) universality across flows and (ii) the multifractal description, including its dissipative-range crossover, hold at orders (and for derived high-order statistics such as acceleration moments), using the converged Lagrangian velocity-structure-function moments available at Taylor-scale Reynolds numbers beyond those of the 2008 data sets — recent DNS already provides Lagrangian exponents up to at (Buaria and Sreenivasan 2023), while converged experimental high-order data and independent cross-data-set coverage remain the outstanding gap; existing experimental data, where available, may be re-analyzed.
These three questions are jointly required: resolving the objective requires addressing all three together, and an answer to any subset resolves only that component. Reducing the methodological biases that limit the 2008 comparison (finite measurement-volume effects in experiments, tracer-interpolation and subgrid-dissipation differences in simulations) is not a separate requirement but a scope qualifier that sets the lag ranges, orders, and flow configurations over which the comparison can be made.
References
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