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A segregated feed model linked to the population balance, which includes micromixing and mesomixing effects together with crystallization and agglomeration kinetics, is proposed for scaling up reactive precipitation processes. The model is solved using kinetic parameters extracted from laboratory-scale experiments together with local mixing parameters obtained from a computational fluid dynamics simulation. Predicted particle size characteristics are compared with experimental data collected on three different scales of operation (range 0.3-25 L) using the aqueous calcium oxalate system. The hybrid precipitation-mixing model accurately predicts mixing effects observed during the continuous mode of operation, including a maximum in the mean particle size and coefficient of variation with increasing power input on each of the three different scales. The influence of mixing on the mean particle size in semibatch operation is found to be more pronounced owing to the direct mixing of the feed solution with the other component already present in the reactor, and is also correctly predicted by the hybrid model.

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