No abstract

No abstract

No abstract

A measurement-based closed-loop control system using in-process ATR-FTIR spectroscopy coupled with a multivariate chemometric PLS calibration model is developed, validated, and applied to the monitoring and control of supersaturation in a 250- L industrial pilot-plant crystalliser. Supersaturation control experiments are carried out on seeded batch cooling crystallisation of β-l-glutamic acid from aqueous solutions using two methods of seeding involving addition of seeds to the solution and generation of seeds within the solution. The generic applicability of the approach is demonstrated through this challenging system reflecting this molecule’s weak chromophore for infrared and relatively low solubility compared with previous solute−solvent systems. Based on the laboratory experiments, the system was fully tested and optimised prior to a series of trials carried out in an industrial pilot plant at Syngenta, Münchwillen, Switzerland. Good control of the supersaturation is achieved at three levels, 1.1, 1.2, and 1.3, within a prescribed range of ±0.025. The average product crystal size is found to decrease with increasing supersaturation. Comparison between product crystals produced at the 20- and 250-L scales indicates that secondary nucleation is more prevalent at the smaller-scale size. For the same level of supersaturation, the rate of depletion of solute is faster at the 20-L scale size than at 250-L scale, and hence a higher cooling rate is required to maintain the desired supersaturation. However, for a given crystalliser scale size, as expected, the mean cooling rate required to maintain a constant supersaturation is found to increase with increasing supersaturation level.

No abstract

This paper develops a new simulation model for crystal size distribution dynamics in industrial batch crystallization. The work is motivated by the necessity of accurate prediction models for online monitoring purposes. The proposed numerical scheme is able to handle growth, nucleation, and agglomeration kinetics by means of the population balance equation and the method of characteristics. The former offers a detailed description of the solid phase evolution, while the latter provides an accurate and efficient numerical solution. In particular, the accuracy of the prediction of the agglomeration kinetics, which cannot be ignored in industrial crystallization, has been assessed by comparing it with solutions in the literature. The efficiency of the solution has been tested on a simulation of a seeded flash cooling batch process. Since the proposed numerical scheme can accurately simulate the system behavior more than hundred times faster than the batch duration, it is suitable for online applications such as process monitoring tools based on state estimators.

No abstract

No abstract