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Dynamic multiscaling in stochastically forced Burgers turbulence

De, S and Mitra, D and Pandit, R (2023) Dynamic multiscaling in stochastically forced Burgers turbulence. In: Scientific Reports, 13 (1).

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Official URL: https://doi.org/10.1038/s41598-023-29056-3


We carry out a detailed study of dynamic multiscaling in the turbulent nonequilibrium, but statistically steady, state of the stochastically forced one-dimensional Burgers equation. We introduce the concept of interval collapse time, which we define as the time taken for a spatial interval, demarcated by a pair of Lagrangian tracers, to collapse at a shock. By calculating the dynamic scaling exponents of the moments of various orders of these interval collapse times, we show that (a) there is not one but an infinity of characteristic time scales and (b) the probability distribution function of the interval collapse times is non-Gaussian and has a power-law tail. Our study is based on (a) a theoretical framework that allows us to obtain dynamic-multiscaling exponents analytically, (b) extensive direct numerical simulations, and (c) a careful comparison of the results of (a) and (b). We discuss possible generalizations of our work to higher dimensions, for the stochastically forced Burgers equation, and to other compressible flows that exhibit turbulence with shocks.

Item Type: Journal Article
Publication: Scientific Reports
Publisher: Nature Research
Additional Information: The copyright for this article belongs to the Authors.
Department/Centre: Division of Physical & Mathematical Sciences > Physics
Date Deposited: 15 Jun 2023 05:38
Last Modified: 15 Jun 2023 05:38
URI: https://eprints.iisc.ac.in/id/eprint/81926

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