Quantitative evaluation of forward and backward scattering in isotropic turbulence via Hänggi–Klimontovich and Itô stochastic processes
Abstract
Abstract This work evaluates the magnitude of the turbulent energy cascade in terms of forward and backward scattering by modeling the “stretch and fold” mechanism through a drift-free Hänggi–Klimontovich stochastic process. Mapping this dynamics onto an equivalent Itô process provides a statistical justification for the uniform distribution of the Lagrangian Lyapunov exponent via the associated Fokker–Planck equation. This continuous distribution is shown to be driven by a Lagrangian bifurcation rate significantly higher than the Lyapunov exponents themselves, reflecting the high frequency with which trajectories encounter the singular surfaces of the velocity gradient. The resulting PDF corresponds to the simultaneous maximization of the information entropy and the Kolmogorov–Sinai entropy. This stochastic formulation, framed within the author’s Lyapunov–Liouville analysis, provides a non-diffusive analytical closure of the von Kármán–Howarth and Corrsin equations. While forward scattering emerges from trajectory instabilities and bifurcations, backscattering is linked to fluid incompressibility. These phenomena are quantified through the continuously distributed Lyapunov exponents, allowing for an estimation of canonical exponents and fundamental transport properties, such as eddy viscosity, eddy thermal diffusivity, and the turbulent Prandtl number. These parameters, traditionally associated with diffusive models, are shown to emerge naturally from non-diffusive Lagrangian dynamics and bifurcation-driven fluctuations. The analytical results demonstrate close agreement with numerical data available in the literature.
Fields of Study & Subjects
Fluid Dynamics and Turbulent Flows
stochastic dynamics and bifurcation
Advanced Thermodynamics and Statistical Mechanics
Publication details
- Journal / source
- Transport Phenomena
- Publisher
- Walter de Gruyter GmbH
- Volume
- 1
- Issue
- 2
- Publication date
- 1 June 2026
- Language
- EN