Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 2610.26050

Fractal forcing of turbulence by settling particles

Simone Tandurella·Alessandro Chiarini·Marco Edoardo Rosti
View original source ↗Read source document ↗Export metadata ↓

Abstract

The settling of particles in a fluid medium can trigger complex collective dynamics, dramatically affecting the distribution of energy across flow scales. In this work we present the first fully-resolved observations of the turbulence induced by large particle structures, also known as cluster-induced-turbulence (CIT), obtained through particle-resolved direct numerical simulations at high volume fractions and density ratios in large domains. We find that particles arrange in macroscopic fractal structures, exciting turbulent fluctuations at scales much larger than the individual constituents. By virtue of their fractal nature, these clusters force the continuous-phase in a multiscale, self-similar way. We further show that these cluster-driven, vertically decorrelated fluctuations at large scales coexist with, but are fundamentally distinct from, the established particle-driven high-wavenumber scaling. Beyond unveiling a different form of clustering in particle-settling, these results highlight a naturally arising, self-assembling path to fractal-generated turbulence.

Explore related subjects

physics.flu-dynnlin.AO

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Simone Tandurella, Alessandro Chiarini, Marco Edoardo Rosti. 2026-10-19. Fractal forcing of turbulence by settling particles. https://arxiv.org/abs/2610.26050

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

CuAD: Source-to-Source Automatic Differentiation of CUDA Kernels for Discrete Adjoints in Computational Fluid Dynamics

Discrete adjoint methods give the sensitivities that aerodynamic design and data assimilation require, but they remain hard to obtain for flow solvers that run on graphics processors. This paper presents CuAD, a source-to-source automatic differentiation tool that reads CUDA kernels and writes their tangent and adjoint versions as ordinary CUDA source. Its reverse mode is organised around the GPU thread. It adopts the convention of CUDA kernels that inputs and outputs do not alias, recomputes intermediate values instead of storing them, differentiates pure accumulations without a tape and keeps any remaining tape in a fixed thread-local array. We evaluate CuAD on four kernels from simple flow models and on a two-dimensional Euler solver. All generated derivatives pass dot-product tests to round-off, and the adjoint kernels cost two to six times the primal kernels. On a Biot-Savart summation compiled by one compiler, the CuAD adjoint costs about four times the primal at every size, as does Enzyme when the source declares the absence of aliasing with __restrict__. On the unchanged source Enzyme caches the loop in the device heap and costs 9 to 240 times the primal, while the heap tape of Clad costs 60 to 4400 times the primal and fails beyond 8192 vortices. Exact Jacobians assembled from the generated tangents also matter for accuracy. In single precision, the adjoint gradient of a finite-difference Jacobian reaches errors of 45 to 75 per cent on a stiff Burgers problem and of $5\times10^{-4}$ to $4\times10^{-2}$ on a transonic airfoil, whereas the generated Jacobian keeps them below $5\times10^{-5}$ and $3\times10^{-6}$. The applications include the shape sensitivities of lift and drag of a transonic NACA 0012, for which the residual, the boundary conditions and the wall force are differentiated by CuAD and the adjoint agrees with the tangent to $10^{-13}$.

physics.flu-dyn↗
arXiv2026

Predicting trigger in streak breakdown via Picard-Chebyshev approach in plane-Poiseuille flow

The evolution of finite-amplitude disturbances is critical in the prediction of laminar-to-turbulent transition. To analyze the transient growth of disturbances, Pralits et al. (J. Fluid Mechanics, 2015) proposed a weakly nonlinear optimal perturbation (WNLOP) analysis that accounts for the effect of mean-flow distortion on the fundamental wave. The present study formulates a WNLOP analysis via Picard--Chebyshev iteration for compressible parallel flows to predict streak breakdown. The formulation incorporates the non-modal amplification of disturbances and their nonlinear interactions for polychromatic waves, considering all the possible nonlinear interactions starting from a finite set of initial wavenumber components. The nonlinear interaction is tracked as a monotonically increasing set of wavenumber components; specifically, the first-order approximation recovers the linear disturbance equation, the third-order approximation corresponds to the amplitude equation of weakly nonlinear theory, and further iterations systematically approach DNS results in the weakly nonlinear regime. By applying the proposed formulation to a subcritical plane Poiseuille flow at Mach number $\mathrm{M}=0.3$ and Reynolds number $\mathrm{Re}=3000$, the proposed formulation demonstrates high predictive accuracy in comparison with DNS calculations and succeeds in identifying the optimal perturbation restricted to a planar wave that causes streak breakdown in full nonlinear simulation. The proposed method predicts the nonlinear interaction between the streak and the planar wave, which generates an oblique wave and subsequent harmonic waves characterized by an alternating streamwise vortex structure, whose amplitude determines whether further nonlinear interactions are induced to trigger the turbulent transition.

physics.flu-dyn↗
arXiv2026

IRENE: a fluId layeR finitE-elemeNt softwarE

We present a finite-element software library, IRENE, which allows to solve numerically the dynamics of a viscous fluid layer embedded in three-dimensional space. Unlike finite-element libraries present in the literature, IRENE can handle two-dimensional open surfaces with a wide range of boundary conditions, and inter-surface obstacles with any shapes, and is built upon the user-friendly and versatile finite element computational software (FEniCS). Also, the library can describe a wide range of physical regimes--both low-Reynolds-number and inertia-dominated ones--capturing the complex coupling between in-plane flows, out-of-plane deformations, surface tension, and elastic response. We validate IRENE against known analytical and numerical results, and demonstrate its capabilities through physical examples. Overall, IRENE provides a versatile and efficient tool for understanding fluid-layer dynamics on multiple physical scales, from flows of lipidic membranes on a microscopic level, to fluid flows on a macroscopic scale, to atmospheric air flows on a planetary level.

physics.flu-dyn↗