Causal analysis of inner and outer motions in near-wall turbulent flow
arxiv(2024)
摘要
In this work, we study the causality of near-wall inner and outer turbulent
motions. Here we define the inner motions as the self-sustained near-wall cycle
and the outer motions as those living in the logarithmic layer exhibiting a
footprint on the near-wall region. We perform causal analysis using two
different methods: one is the transfer entropy, based on the information
theory, and the other one is the Liang–Kleeman information-flow theory. The
causal-analysis methods are applied to several scenarios, including a linear
and a non-linear problem, a low-dimensional model of the near-wall cycle of
turbulence, as well as the interaction between inner and outer turbulent
motions in a channel at a friction Reynolds number of Re_τ=1000. We find
that both methods can well predict the causal links in the linear problem, and
the information flow can identify more of the nonlinear problem. Despite richer
causalities revealed by the transfer entropy for turbulent-flow problems, both
methods can successfully identify the streak-vortex regeneration mechanism that
majorly sustains the near-wall turbulence. It is also indicated that both
bottom-up and top-down influences of inner and outer motions may coexist in
addition to the multiscale self-sustaining mechanism. Lastly, we mention that
the computation of the information flow is much more efficient than the
transfer entropy. The present study suggests that the information flow can have
great potential in causal inference for turbulent-flow problems besides the
transfer entropy.
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