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Modeling ash deposit growth rates for a wide range of solid fuels in a 100 kW combustor.

Authors :
Fakourian, Seyedhassan
McAllister, Zachary
Fry, Andrew
Wang, Yueming
Li, Xiaolong
Wendt, Jost O.L.
Dai, Jinze
Source :
Fuel Processing Technology. Jun2021, Vol. 217, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

This work details a model for evaluating the relative ash deposition propensity of various solid fuels without the complicated spatial considerations included in CFD modeling. Four deposition mechanisms are included, namely: inertial impaction, thermophoresis, condensation, and eddy impaction. This model has been validated and shown to effectively predict ash deposit rates for a wide range of solid fuels including coal, biomass, and their blends, burned in a 100 kW rated downflow combustor. Specifically, this work presents and compares two separate models for the sticking efficiency of impacting ash particles on a coupon surface: the melt fraction stickiness model (MFSM), which is developed here and includes a novel approach to determine sticking efficiency, and the kinetic energy stickiness model (KESM), an existing model used for comparison. To apply the MFSM model, the equilibrium composition of vapor species are calculated by thermodynamic modeling using FactSage. By comparing the root-mean-square-errors of the MFSM and KESM over the wide variety of fuels, it is shown that the MFSM is more accurate than the KESM in predicting the ash deposit rate. This shows that NaCl and KCl are expected to be the main alkali vapor species in the flue gas, for the fuels evaluated. • The model helps the operators of utility boilers predict the relative deposition rate. • The condensation creates a sticky layer that enhances the sticking efficiency. • Performace of the MFSM model is much better than the KESM model. • The model is validated with the experimental data of a wide range of solid fuels. • Inertial impaction is the dominant mechanism of ash deposit formation in Ө = 0. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03783820
Volume :
217
Database :
Academic Search Index
Journal :
Fuel Processing Technology
Publication Type :
Academic Journal
Accession number :
149944018
Full Text :
https://doi.org/10.1016/j.fuproc.2021.106777