화학공학소재연구정보센터
Chemical Engineering Journal, Vol.169, No.1-3, 299-312, 2011
Numerical study of the conversion time of single pyrolyzing biomass particles at high heating conditions
When designing industrial furnaces for combustion of biomass particles, it-is of technical importance to know the time of pyrolysis at high heating conditions. We numerically investigated pyrolysis of a single biomass particle using a one-dimensional model which assumes that the conversion process of a pyrolyzing particle takes place through three parallel reactions yielding light gases, tar and char. A novel idea that has been established in this paper is that the heat of pyrolysis in the energy conservation equation is calculated by accounting for the exothermicity of char formation and the endothermicity of volatiles generation in accordance with the correlations proposed in the literature. As the idea is to investigate biomass particle pyrolysis at high heating conditions, three different sets of experimental data conducted at high surrounding temperatures are selected for validation of the improved model. It is found that employing the correlations of Milosavljevic et al. and Mok and Antal to compute the heat of pyrolysis together with kinetic constants of Di Blasi and Branca in the model provides a good prediction of the final char yield and conversion time. In the next stage of the study, the pyrolysis model is utilized to investigate the effects of particle shape, size and initial density on conversion time and final char density of a biomass particle at high heating environments. Typical results are presented which are expected to enable a designer to estimate the pyrolysis time and final char density of a biomass particle undergoing thermochemical conversion at the conditions of industrial combustors. Finally, the homogeneity of the pyrolysis process inside small particles exposed to high reactor temperatures is investigated. It is found that adaption of such an assumption in a particle conversion model may result in undesired reduction of the accuracy of the model predictions. (C) 2011 Elsevier B.V. All rights reserved.