| Abstract: |
| Scale-by-scale scalar statistics are investigated from first principles in non-equilibrium multicomponent flows, with particular emphasis on higher-order moments as signatures of rare and extreme events. The analysis focuses on how small-scale scalar fluctuations are shaped by large-scale gradients, advection, waves, coherent structures, and component coupling in systems where a single effective Reynolds number is insufficient to characterize the dynamics. The framework is illustrated primarily for quantum turbulence described by the Hall-Vinen-Bekharevich-Khalatnikov (HVBK) model, including temperature effects. A second case pertains to atmospheric flows simulated using the Weather Research and Forecasting (WRF) model in Large Eddy Simulation configuration, with application to heat-wave conditions over France. Although physically distinct, both systems exhibit strong mixing, variable thermodynamic properties, and a marked dependence of small-scale statistics on large-scale forcing. This parallel highlights common multiscale mechanisms governing intermittency and extreme events in non-equilibrium flows.
1. Polanco, J. I., Roche, P. E., Danaila, L., and Leveque, E. (2025). Disentangling temperature and Reynolds-number effects in quantum turbulence. Proceedings of the National Academy of Sciences, 122.
2. Zhang, Z., Danaila, L., Leveque, E., and Danaila, I. (2023). Higher-order statistics and intermittency in two-fluid quantum turbulence. Journal of Fluid Mechanics, 960, A6. |
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