Quantifying differences between chaotic Rayleigh-Bénard convection experiments and simulations using plumes detected by persistent homology 10.1.3

Persistent homology is a data analysis technique that can be used to quantify the topological information of image data. In the spatio-temporally chaotic flow known as spiral defect chaos in Rayleigh-Benard convection, we explore the difference between convective plume statistics, detected using persistent homology, over long time-series of convection experiments and simulations of the Boussinesq equations with constant temperature boundary conditions.   We find that such simulations produce plume statistics that are different from experiments.  We describe a model of the thermal conduction in the experimental cell that produces temperature boundary conditions that are constant in time but vary in space while accounting for the finite thickness and thermal conductivity of the heating and cooling plates in experiments.  We demonstrate that simulations that employ these improved boundary conditions produce total plume statistics that are more similar to experiments.  However, we demonstrate that in order to account for a discrepancy in cold and hot experimental plume rates, simulations that include non-Boussinesq effects are necessary.

 

10.1.3