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Multiplicative cascades have been introduced in turbulence to generate random or deterministic fields having intermittent values and long-range power-law correlations. Generally this is done using discrete construction rules leading to…

Statistical Mechanics · Physics 2007-05-23 Francois G. Schmitt

Spontaneous stochasticity is a modern paradigm for turbulent transport at infinite Reynolds numbers. It suggests that tracer particles advected by rough turbulent flows and subject to additional thermal noise, remain non-deterministic in…

Fluid Dynamics · Physics 2023-06-21 André Luís Peixoto Considera , Simon Thalabard

We present a simple stochastic algorithm for generating multiplicative processes with multiscaling both in space and in time. With this algorithm we are able to reproduce a synthetic signal with the same space and time correlation as the…

Chaotic Dynamics · Physics 2007-05-23 Roberto Benzi , Luca Biferale , Federico Toschi

Motivated by the modeling of three-dimensional fluid turbulence, we define and study a class of stochastic partial differential equations (SPDEs) that are randomly stirred by a spatially smooth and uncorrelated in time forcing term. To…

Probability · Mathematics 2021-12-24 Gabriel B. Apolinário , Laurent Chevillard , Jean-Christophe Mourrat

The present article concerns the stochastic modeling of the turbulent dissipation field and in particular its temporal evolution. To do so, we will be calling for a random distribution, ubiquitous in several aspects of physics and…

Fluid Dynamics · Physics 2026-04-08 Wandrille Ruffenach , Laurent Chevillard

The characterization of intermittency in turbulence has its roots in the K62 theory, and if no proper definition is to be found in the literature, statistical properties of intermittency were studied and models were developed in attempt to…

Fluid Dynamics · Physics 2021-07-14 Roxane Letournel , Ludovic Goudenège , Rémi Zamansky , Aymeric Vié , Marc Massot

Discrete multiplicative turbulent cascades are described using a formalism involving infinitely divisible random measures. This permits to consider the continuous limit of a cascade developed on a continuum of scales, and to provide the…

Statistical Mechanics · Physics 2015-06-24 F. Schmitt , D. Marsan

The concept of stochastic Lagrangian and its use in statistical dynamics is illustrated theoretically, and with some examples. Dynamical variables undergoing stochastic differential equations are stochastic processes themselves, and their…

Statistical Mechanics · Physics 2020-03-18 Massimo Materassi

We study the local regularity and multifractal nature of the sample paths of jump diffusion processes, which are solutions to a class of stochastic differential equations with jumps. This article extends the recent work of Barral {\it et…

Probability · Mathematics 2017-09-06 Xiaochuan Yang

We present a dynamical log-stable process for the spatio-temporal evolution of the energy-dissipation field in fully developed turbulence. The process is constructed from multifractal scaling relations required for two-point correlators of…

Statistical Mechanics · Physics 2007-05-23 J. Schmiegel , M. Greiner

Motivated by systems in which droplets grow and shrink in a turbulence-driven supersaturation field, we investigate the problem of turbulent condensation in a general manner. Using direct numerical simulations we show that the turbulent…

Fluid Dynamics · Physics 2016-12-06 Christoph Siewert , Jeremie Bec , Giorgio Krstulovic

Obtaining accurate field statistics continues to be one of the major challenges in turbulence theory and modeling. From the various existing modeling approaches, multifractal models have been successful in capturing intermittency in…

Log-normal continuous random cascades form a class of multifractal processes that has already been successfully used in various fields. Several statistical issues related to this model are studied. We first make a quick but extensive review…

Statistical Finance · Quantitative Finance 2008-12-02 E. Bacry , A. Kozhemyak , J. -F. Muzy

We develop a stochastic model for Lagrangian velocity as it is observed in experimental and numerical fully developed turbulent flows. We define it as the unique statistically stationary solution of a causal dynamics, given by a stochastic…

Multifractal systems usually have singularity spectra defined on bounded sets of H\"older exponents. As a consequence, their associated multifractal scaling exponents are expected to depend linearly upon statistical moment orders at high…

Fluid Dynamics · Physics 2021-06-30 L. Moriconi

We develop a stochastic model for the velocity gradients dynamics along a Lagrangian trajectory. Comparing with different attempts proposed in the literature, the present model, at the cost of introducing a free parameter known in…

Fluid Dynamics · Physics 2018-02-23 Rodrigo M. Pereira , Luca Moriconi , Laurent Chevillard

Velocity increments over a distance r and turbulent energy dissipation on a box of size r are well described by the multifractal models of fully developed turbulence. These quantities and models however, do not involve time-correlations and…

chao-dyn · Physics 2008-02-03 R. Lima , R. Vilela Mendes

We use the multifractal formalism to describe the effects of dissipation on Lagrangian velocity statistics in turbulent flows. We analyze high Reynolds number experiments and direct numerical simulation (DNS) data. We show that this…

Statistical Mechanics · Physics 2007-05-23 L. Chevillard , S. G. Roux , E. Leveque , N. Mordant , J. -F. Pinton , A. Arneodo

This study makes the first attempt to use the 2/3-order fractional Laplacian modeling of enhanced diffusing movements of random turbulent particle resulting from nonlinear inertial interactions. A combined effect of the inertial…

Chaotic Dynamics · Physics 2007-05-23 Wen Chen

A computationally efficient model is introduced to account for the sub-grid scale velocities of tracer particles dispersed in statistically homogeneous and isotropic turbulent flows. The model embeds the multi-scale nature of turbulent…

Fluid Dynamics · Physics 2015-06-18 I. M. Mazzitelli , F. Toschi , A. S. Lanotte
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