Large-scale circulation reversals explained by pendulum correspondence
arXiv:2307.13148 · doi:10.1017/jfm.2024.584
Abstract
We introduce a low-order dynamical system to describe thermal convection in an annular domain. The model derives systematically from a Fourier-Laurent truncation of the governing Navier-Stokes Boussinesq equations and accounts for spatial dependence of the flow and temperature fields. Comparison with fully-resolved direct numerical simulations (DNS) shows that the model captures parameter bifurcations and reversals of the large-scale circulation (LSC), including states of (i) steady circulating flow, (ii) chaotic LSC reversals, and (iii) periodic LSC reversals. Casting the system in terms of the fluid's angular momentum and center of mass (CoM) reveals equivalence to a damped pendulum with forcing that raises the CoM above the fulcrum. This formulation offers a transparent mechanism for LSC reversals, namely the inertial overshoot of a forced pendulum, and it yields an explicit formula for the frequency of regular LSC reversals in the high Rayleigh-number limit. This formula is shown to be in excellent agreement with DNS and produces the scaling law .
References in corpus (11)
- Large scale dynamics in turbulent Rayleigh-Benard convection
- Computing Nearly Singular Solutions Using Pseudo-Spectral Methods
- Flow reversals in thermally driven turbulence
- Switchbacks in the near-Sun magnetic field: long memory and impact on the turbulence cascade
- Orientation changes of the large-scale circulation in turbulent Rayleigh-Benard convection
- Wind reversals in turbulent Rayleigh-Benard convection
- Enhanced heat transport by turbulent two-phase Rayleigh-Bénard convection
- Tristable flow states and reversal of the large-scale circulation in two-dimensional circular convection cells
- A stable and accurate scheme for solving the Stefan problem coupled with natural convection using the Immersed Boundary Smooth Extension method
- Morphological attractors in natural convective dissolution
- Predicting flow reversals in chaotic natural convection using data assimilation