Predicting flow reversals in chaotic natural convection using data assimilation
نویسندگان
چکیده
A simplified model of natural convection, similar to the Lorenz system, is compared to computational fluid dynamics simulations of a thermosyphon in order to test data assimilation (DA) methods and better understand the dynamics of convection. The thermosyphon is represented by a long time flow simulation, which serves as a reference ‘truth’. Forecasts are then made using the Lorenz-like model and synchronised to noisy and limited observations of the truth using DA. The resulting analysis is observed to infer dynamics absent from the model when using short assimilation windows. Furthermore, chaotic flow reversal occurrence and residency times in each rotational state are forecast using analysis data. Flow reversals have been successfully forecast in the related Lorenz system, as part of a perfect model experiment, but never in the presence of significant model error or unobserved variables. Finally, we provide new details concerning the fluid dynamical processes present in the thermosyphon during these flow reversals.
منابع مشابه
Supporting Information Predicting flow reversals in chaotic natural convection using data assimilation
Following the derivations of Gorman et al. (1986) and Ehrhard and Müller (1990), we consider the forces acting upon a control volume of incompressible fluid in the loop. All fluid properties are cross-sectionally averaged, and the radial components of velocity and heat conduction within the fluid are neglected. The fluid velocity u = u(t) is assumed to be constant at all points. Applying Newton...
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