Abstract

Methanation is a promising technology to transform carbonaceous materials into high-value fuels, yet the relationship between multi-scale structures and reactor performance is still not well understood. Accordingly, the methanation process in a bubbling fluidized bed (BFB) reactor is investigated via the computational fluid dynamics-discrete element method (CFD-DEM) featuring thermochemical sub-models. A novel algorithm is developed for bubble identification and related information statistics. The effects of crucial operating parameters on bubble behaviours are quantified. Moreover, the underlying mechanism of mesoscale bubble behaviours is illuminated by linking with microscale particle dimensionless number and macroscale reactor performance. The results show that the bubble dynamics can be well captured by the novel bubble identification algorithm. Particle Reynolds number (Rep) and Nusselt number (Nup) have the highest values in the bubble phase and the lowest values in the emulsion phase. Decreasing inlet gas velocity, increasing particle size, and lowering operating temperature causes smaller volume ratios of the bubble phase to emulsion phase, thereby enhancing interphase heat and mass transfer and promoting methane concentration in the gas products.

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