Data-driven reduced modelling of turbulent Rayleigh–Bénard convection using DMD-enhanced fluctuation–dissipation theorem

DOI10.1017/jfm.2018.586zbMath1415.76314arXiv1805.10577OpenAlexW2804138598MaRDI QIDQ4585936

Pedram Hassanzadeh, M. A. Khodkar

Publication date: 11 September 2018

Published in: Journal of Fluid Mechanics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1805.10577

zbMATH Keywords

nonlinear dynamical systemlow-dimensional modelturbulent convection

Mathematics Subject Classification ID

Dynamical systems in fluid mechanics, oceanography and meteorology (37N10) Convective turbulence (76F35)

Related Items (5)

A data-driven, physics-informed framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings ⋮ Generative Stochastic Modeling of Strongly Nonlinear Flows with Non-Gaussian Statistics ⋮ Adaptive sparse interpolation for accelerating nonlinear stochastic reduced-order modeling with time-dependent bases ⋮ A preconditioned multiple shooting shadowing algorithm for the sensitivity analysis of chaotic systems ⋮ Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms

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