A Model for Attrition in Fluidized Beds

Carbon attrition during the fluidized combustion of a coal

“…Attention, however, has been mainly devoted to the attrition behavior of coal ashes and of limestones and dolomites (Merrick and Highley, 1974;Vaux, 1978, Franceschi et al, 1980Chen et al, 1980) in relation to problems of atmospheric pollution control and better utilization of sorbents. Studies on the mechanism of carbon particle combustion in fluidized beds have generally been carried out on the assumption that the fraction of feed carbon leaving the combustor as attrited fines is negligible (Avedesian and M)01-1541-83-64%-004040-$2 00 0 The American Institute of Chemical Engineers, 1983 Davidson, 1973;Chakraborty and Howard, 1980).…”

A Model of Attrition in the Jetting Region of Fluidised Beds

“…A hydrodynamic model may be used to obtain the dependence of W 5 , and uP on the orifice gas velocity. This can be done by power-law correlations [12]: (4) (5) Ghadiri et al [12] proposed that the attrition rate in the jetting region is linearly related to the single particle impact attrition and the solids entrainment rate.…”

“…(4) into Eq. (3), and multiplying by the solids entrainment rate, W 5 , the attrition rate in a single jet may be given as: (6) In this way, a descriptive and predictive model is established, which incorporates the single particle attrition characteristics. The results of this approach will be presented in section 4.…”

“…Focusing on two main design and operation parameters, the orifice size, d 0 ro and the gas velocity, u, the correlations are generally written in the form of a power law: (1) where u can be the orifice gas velocity (u 0 ), or the superficial (u 5 ) or excess gas velocity (u 5 -umf), with values of n ranging from 0.66 to 5.8 and of h from 0 to 1.11, as reported by different authors. The exponential correlation of Lin et al [6] appears to be an exception to this general form, but replotting their data shows that there is no need for an exponential correlation, and that a good fit is also achieved with a linear regression.…”