Dean Ilievski

Supersaturation and temperature dependency of gibbsite growth in laminar and turbulent flows

Abstract The temperature and supersaturation dependencies of gibbsite crystal growth rates in caustic aluminate solutions were experimentally investigated in both the laminar (Taylor–Couette precipitator) and turbulent (stirred tank) mixing regimes. The gibbsite precipitation experiments were conducted batchwise in a temperature range from 55°C to 90°C, but all with the same initial liquor composition and seed type. At low supersaturation it was found that gibbsite crystal growth could be described satisfactorily by a screw dislocation growth mechanism over the complete temperature range, irrespective of the flow regime. At higher supersaturation and lower temperatures, i.e. 55°C and 60°C, it is proposed that two-dimensional polynuclear growth is the dominant growth mechanism in turbulent flows. Any differences observed in the measured growth rate estimates from the laminar and turbulent systems were explained by error analysis.

Modelling non-stationary precipitation systems : sources of error and their propagation

A laboratory well-mixed, constant supersaturation, semi-batch gibbsite precipitator, with clear liquor advance, was modelled using a discretized population balance (DPB). This experimental configuration is inherently non-stationary (i.e. does not reach steady state). The model predictions of the transient crystal size distribution (CSD) were found to give good agreement to the experimental CSDs initially but deviated apart with time. The cause of this deviation was identified as error propagated in the computation of the DPB model. The source of the propagated error was investigated. The error contributions from the growth and agglomeration term discretizations were found to be small compared to the magnitude of the observed deviation. Monte Carlo simulation demonstrated that the main contribution to the observed error is from uncertainty in the estimates of the agglomeration kernel and growth rate parameters, which are estimated from experimental data and used in the simulation. The findings highlight the need for more precise kinetics estimation procedures and advocate care when simulating the CSD of non-stationary precipitators over longer time scales, which may have implications for precipitator start-up simulations.

Modelling a Constant Supersaturation Precipitator

A population balance model of a semi-batch gibbsite precipitator, operating at constant supersaturation, was developed and compared with corresponding experimental gibbsite precipitation data. The experimental data were generated under controlled laboratory conditions where crystal agglomeration and growth were the dominant size enlargement mechanisms, and nucleation was negligible. The Hounslow discretization method was used to solve the resulting integro-partial differential equations. The agglomeration and growth rates used in this work were determined in two ways: (1) from correlation models in the literature, and (2) by matching moments of the crystal size distribution (CSD). The model predictions of the CSD and the total crystal numbers were found to give good agreement to the experimental precipitation data when agglomeration and growth kinetics estimated from moments matching were used; poor agreement was observed when the literature correlations were used. A 3-term discretized growth term was found to result in better CSD predictions than a 2-term growth discretization. Error propagation was identified as a potential problem in precipitator modelling using the discretized population balance.

Micromixing of solids and fluid in an aggregating precipitator

A lab-scale precipitator of alumina trihydroxide (gibbsite) is simulated for three extreme cases of micromixing, these being: the familiar cases of Maximum Mixedness and Complete Segregation, and a third case in which the fluid is mixed but the solids are segregated. Through this novel third case, the effect of segregated fluid on the particle size distribution is distinguished from the effect of segregated solids. It is found that these two effects are sometimes in opposition to each other, and the latter is dominant in a system undergoing aggregation but not nucleation. Few other simulations have considered this. Conclusions are drawn on the relevance of micromixing to simulating crystallisation, especially when aggregation is significant.