Search arXiv⌕ Search

arXiv · 2109.11183

Ascending-descending and direct-inverse cascades of Reynolds stresses in turbulent Couette flow

Abstract

The interaction between small- and large-scale structures, and the coexisting bottom-up and top-down processes are studied in a turbulent plane Couette flow, where space-filling longitudinal rolls appear at relatively low values of the Reynolds number $Re$. A DNS database at $Re_τ=101$ is built to replicate the highest $Re$ considered in a recent experimental work by Kawata and Alfredsson (Phys. Rev. Lett., vol.120, 2018, 244501). Our study is based on the exact budget equations for the second-order structure function tensor $\langle δu_i δu_j \rangle$, i.e. the Anisotropic Generalized Kolmogorov Equations (AGKE). The AGKE study production, redistribution, transport and dissipation of every Reynolds stress tensor component, considering simultaneously the physical space and the space of scales, and properly define the concept of scale in the inhomogeneous wall-normal direction. We show how the large-scale energy-containing motions are involved in the production and redistribution of the turbulent fluctuations. Both bottom-up and top-down interactions occur, and the same is true for direct and inverse cascading. The wall-parallel components $\langle δu δu \rangle$ and $\langle δw δw \rangle$ show that the both small and large near-wall scales feed the large scales away from the wall. The wall-normal component $\langle δv δv \rangle$ is different, and shows a dominant top-down dynamics, being produced via pressure-strain redistribution away from the wall and transferred towards near-wall larger scales via an inverse cascade. The off-diagonal component shows a top-down interaction, with both direct and inverse cascade, albeit the latter takes place within a limited range of scales.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Alessandro Chiarini, Mariadebora Mauriello, Davide Gatti, Maurizio Quadrio. 2021-09-23. Ascending-descending and direct-inverse cascades of Reynolds stresses in turbulent Couette flow. https://doi.org/10.1017/jfm.2021.886

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

KEEP EXPLORING

Related papers

Reynolds-number regimes of corrugation-induced lift enhancement in two-dimensional dragonfly-like wings

Corrugated wing structures commonly observed in insect wings can enhance aerodynamic performance at low Reynolds numbers ($Re \simeq O(10^3)$). However, their effectiveness strongly depends on the Reynolds number, and the corresponding operating range remains unclear. Direct numerical simulations of an impulsively started corrugated wing are performed over a wide range of Reynolds numbers ($100 \leq Re \leq 4000$) to identify the conditions under which corrugation is beneficial. Three Reynolds-number regimes are identified within the examined parameter sets. No characteristic lift-enhancement mechanism is observed for $100 \leq Re < 1000$. For $1000 \leq Re \leq 4000$, lift enhancement is associated with alternating vortices formed within the V-shaped region of the corrugated wing, which generate low-pressure regions near the wing surface. Above $Re=2000$, the collapse and confinement of a secondary vortex within the V-shaped region emerge as an additional dominant mechanism, further enhancing the lift. An analysis based on a local Reynolds number organizes the onset conditions of these mechanisms and provides a useful local measure for characterizing the onset of vortex detachment from the corrugation. Furthermore, long-time simulations confirm that the observed vortex dynamics persist well beyond the initial transient response following an impulsive start. These results elucidate Reynolds-number-dependent lift-enhancement mechanisms and define aerodynamic conditions under which corrugated wings provide an advantage.

physics.flu-dyn↗

PhysMiner: An Agentic AI Framework for Automated Flow Component Analysis

Uncovering the physical mechanisms of turbulent flows remains a fundamental challenge in fluid mechanics. In particular, conventional velocity-gradient analysis methods suffer from shear contamination, which hinders accurate identification of the dominant physical mechanisms. This study presents PhysMiner, an automated framework integrating the triple decomposition method of the velocity gradient tensor with large language model-driven reasoning for turbulence-physics discovery. The triple decomposition module automatically decomposes flow fields into rigid rotation, pure shearing, and normal straining components, enabling statistical analysis, contour visualization, vortex-line extraction, and threshold-insensitive vortex identification while eliminating shear contamination. These automated capabilities are validated across five benchmarks, ranging from canonical configurations to complex engineering flows. A discover-physics agent combines flow statistics, spatial structures, and literature-derived knowledge to perform pattern recognition and physical inference, while a review Agent iteratively validates physical consistency to ensure reliable conclusions. A continuously evolving Triple Decomposition Library accumulates statistical knowledge from successfully analyzed flows, enabling cross-case comparison and progressive enhancement of inductive capability. The complete PhysMiner pipeline is validated end-to-end on the periodic hill flow, where the framework autonomously generates turbulence modeling recommendations and derives an improved subgrid-scale model with superior Reynolds-stress predictions. PhysMiner is open to the public and establishes a foundation for long-term collaborative advancement in automated turbulence-physics discovery.

physics.flu-dyn↗

Lattice Boltzmann Methods for Navier-Stokes Equations in General Orthogonal Coordinates for Efficient Flow Simulations using Nonuniform Clustered Grids

Resolving multiscale fluid flows or boundary layers effectively requires the use of nonuniform meshes with local grid clustering. The standard lattice Boltzmann method (LBM), a kinetic theory-based approach for computational fluid dynamics, however, is restricted to the use of uniform Cartesian grids. We present new and improved formulations of the LBM that accommodate continuously varying spatial grids via coordinate transformations to simulate the Navier-Stokes equations (NSE) in the general orthogonal coordinates (GOC). They are constructed using a Chapman-Enskog analysis to specify the equilibrium moments of the distribution functions and the geometric force terms used in the collision step to be dependent on the local metric factors and their spatial derivatives, along with the density, momentum and their fluxes, and some correction terms related to the normal velocity gradients so as to accurately represent the NSE in the GOC. The resulting GOC-LBM importantly maintains the simplicity of the collide-and-stream approach and is Galilean invariant that is free of the cubic velocity artifacts. Our GOC-LBM is general and modular in that it can be used with any collision model with appropriate modifications to the equilibria and forcing terms. We present its implementation details for a variety of collision models while the central moments-based model using multiple relaxation times was found to be the most robust in practical implementations. We validate the GOC-LBM through numerical simulations for various benchmark flow problems. Moreover, we demonstrate significant computational advantages of our approach for a case study on simulating boundary layer flows efficiently that involves coupling the GOC-LBM for the NSE with a new GOC-LB scheme for solving the magnetic induction equation for magnetohydrodynamics (MHD), and for another case study involving orthogonal curvilinear grids.

physics.flu-dyn↗