Numerical prediction of ash deposit growth burning pure coal and its blends with woody biomass in a 1.5 MWTH combustor. (April 2023) - Fakourian, Seyedhassan; Roberts, Matt; Dai, Jinze
Highlights: A comprehensive model incorporating alkali vapor-ash interaction is established to predict ash deposit growth. The condensation of alkali vapor is found to create a sticky layer that accelerates ash deposition. The model is validated with the experimental data from 1.5 MW coal combustion along with its blends of biomass. Inertial impaction is the dominant mechanism of ash deposit formation. Abstract: The present work applies an original ash deposition model to a 1.5 MWTH combustor burning pure coal and its blends with woody biomasses (15 wt% biomass and 85 wt% coal). Previously, this model was validated with eleven (11) different solid fuels burning at a 100 kW down fired combustor, and this is the first scale-up study under industrially relevant conditions at 1.5 MWTH . The model does not require CFD modeling but considers four essential deposition mechanisms: inertial impaction, thermophoresis, condensation, and eddy impaction. The model employs the melt fraction stickiness model (MFSM), which includes a novel approach to determine sticking efficiency. The thermodynamic package of FactSage calculates the equilibrium composition of vapor species and the melt fraction of ash deposit and fly ash particles. Burning the fuels of this research produces NaCl and KCl, which are the main alkali vapor species for ash deposit formation on the clean surface of a heat exchanger. Condensation of such alkali vapor species expedites the ash deposit growth. The model suggests that cofiring woody biomass with coal makes slight changes at ash deposit growth at the locations farther to the burner. However, the predicted ash deposit growth for coal versus its blends at the closer location to the burner is significant. The present work substantiates that a numerical non-CFD model can be used for different scales of combustors and a wide range of solid fuels. Based on a novel approach in predicting ash deposit growth, the modeling results are consistent with the experimental data from a 1.5 MWTH combustor, paving the way for its commercial application.