Visual exploration of circulation rolls in convective heat flows

We present techniques to improve the understanding of pattern forming processes in Rayleigh-Bénard-type convective heat transport, through visually guided exploration of convection features in timeaveraged turbulent flows. To enable the exploration of roll-like heat transfer pathways and pattern-forming anomalies, we combine feature extraction with interactive visualization of particle trajectories. To robustly determine boundaries between circulation rolls, we propose ridge extraction in a z-averaged temperature field, and in the extracted ridge network we automatically classify topological point defects hinting at pattern forming instabilities. An importance measure based on the circular movement of particles is employed to automatically control the density of 3D trajectories and, thus, enable insights into the heat flow in the interior of rolls. A quantitative analysis of the heat transport within and across cell boundaries, as well as investigations of pattern instabilities in the vicinity of defects, is supported by interactive particle visualization including instant computations of particle density maps. We demonstrate the use of the proposed techniques to explore direct numerical simulations of the 3D Boussinesq equations of convection, giving novel insights into Rayleigh-Bénard-type convective heat transport.