Control of supersaturation in a 1-L continuous cooling KCI crystallizer was investigated. The supersaturation was determined from on-line measurements of the density and temperature of clear liquor samples. A cascade control scheme was used to control the supersaturation through the manipulation of the co-saturated feed temperature set-point while maintaining the crystallizer temperature at 303.2 K. Experimental results showed that due to the suppression of spontaneous nuclearion, a decrease in the measured supersaturation resulted in a 23 % increase in the mean crystal sue and a 12% decrease in the amount of NaCl impurity in the KCI crystals.. On a 6tudi6 le contr6le de la sursaturation dans un cristalliseur de KCI h refroidissement continu de 1 L. La sursaturation a 6tt5 d6terminb 21 partir de mesures continues de la masse volumique et de la temp6rature des kchantillons de liqueur Claire. On a utilis6 un schkma de contr8le en cascade pour rkguler la sursaturation par la manipulation du point de consigne de temp6rature d'alimentation cosaturk, tandis que la temp6rature du cristalliseur 6tait maintenue A 303,Z K. Les fisultats exp6rimentaux montrent que, du fait de la suppression de la nuclbtion spontade, une diminution de la sursaturation mesurk entraine une diminution de 23% de la taille moyenne des cristaux et une diminution de 12% de l'impuret6 du NaCl dans les cristaux de KCI. rystallization is an important separation process in the C chemical industry, with widespreaduse in the production and purification of bulk chemicals, fermizers, pharmaoeuticals, etc. Despite the varied applications of crystallization, the successful design and operation of industrial crystallizers are based largely on experience as opposed to being based on theoretical principles. Previous work on the on-line control of crystal product quality has primarily dealt with control of the crystal size distribution (CSD). Feedback control of the nuclei density (Rovang and Randolph, 1980; Randolph et al., 1981; Randolph and Low, 1982; Randolph et al., 1987), or of the lines suspension density (Rohani, 1986; Rohani and Lee, 1987; Rohani and Paine, 1991), and manipulation of the h e s dissolution rate have shown some success in the control of CSD in continuous crystallizers. Various control strategies used in industrial crystallizers are discussed by Rohani CrystallizationKineticsofPUassi~chloride'',Ind. Eng.Chem. Res. 28, 844-850 (1989).
A method is developed for the calculation of the saturation temperature of a KCI‐NaCI aqueous solution, based on the measurement of the density and temperature of a sample solution, and prior knowledge of the NaCl concentration. Experimental density and solubility data for solutions saturated with KCI in the temperature range of 299 to 321 K with concentrations of NaCl greater than 0.200 kg/kg H2O were used to develop the empirical correlation allowing the calculation of the solution saturation level. The method is applicable in the on‐line determination of the level of supersaturation in a KCI crystallizer in which the NaCl concentration is known. Knowledge of the prevailing supersaturation is necessary for the control of crystal purity and crystal size distribution in industrial potash crystallizers.
Particles and droplets are critical in the determination of product quality and process efficiency in the manufacture of a wide range of chemical, pharmaceutical, and biological products. Processes such as crystallization and precipitation, homogenization and emulsification, polymerization, and fermentation are based on the detailed understanding, optimization, and control of particles, droplets, and bubbles. This article distinguishes between in situ particle system characterization (PSC) and traditional off‐line particle size analysis (PSA), and explains how the broader view of PSC is better suited to optimization and control of complex multiphase processes. PSC goes beyond traditional off‐line PSA, to provide real‐time, in‐process measurements of the rate and degree of change in particles and particle structures as they exist in the actual process environment. In situ process analytical methods can also significantly reduce measurement errors associated with off‐line sampling and sample preparation. This facilitates improved process development through direct real‐time monitoring of the particles and droplets as they exist and change in process. Process‐analytical‐based understanding contributes to faster methods of optimization and results in more consistent scale‐up. Real‐time monitoring and control of the particle system in the manufacturing environment is also used as a tool to help assure product quality.
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