Theoretical and practical experiences with molasses exhaustion in Nordzucker

摘要

The cooling crystallization process is complicated by many important and inter-connected variables. This makes accurate prediction of molasses exhaustion difficult. This is important when optimizing cooling crystallizer systems, especially where investment decisions are needed. To find the best predictive model a robust set of factory data measurements (n = 39) were evaluated. The crystal growth model that gave the best estimate of the data used a two-step crystal growth equation involving the coefficients for mass transfer by diffusion and reaction integration and an effective concentration difference, Ac ,,, which accounted erf' for the influences of nonsugar/water ratio, temperature and variations in raffinose and invert sugar contents on the crystallization end point. The model was validated by giving a good estimate of the purity drop (+0.1 unit) measured over a newly upgraded cooling crystallizer system at a factory during the 2012 campaign. The ability to more accurately predict molasses exhaustion makes it possible to better evaluate investment decisions to increase sugar yield.