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Factorial Experiment Design in the Front Velocity Modeling Approach Applied to Chromatographic Separation of Glucose and Fructose

A. Prieto-Moreno1, L.D.Tavares Câmara2, O. Llanes-Santiago1, A. J. Silva Neto2

CUJAE, Marianao, La Habana, Cuba.
IPRJ-UERJ, Nova Friburgo, RJ, Brazil.

Computer Modeling in Engineering & Sciences 2015, 106(6), 441-462. https://doi.org/10.3970/cmes.2015.106.441

Abstract

This work deals with a statistical approach to the uncertainty propagation analysis when estimating the kinetic mass transfer parameters used to model a chromatographic column in the Simulated Moving Bed. The chromatographic column modeling was performed using the new front velocity approach. The uncertainty propagation analysis of operational factors intervening in the chromatographic process to estimated parameters was made using the response surface methodology. The application of the factorial experimental design allowed us to establish those operational factors showing a greater influence on continuous chromatography. Besides, the chromatographic regions, where factors cause a greater output variation as well as their respective patterns, were determined. The analysis was applied to the separation of glucose and fructose.

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APA Style
Prieto-Moreno, A., Câmara, L., Llanes-Santiago, O., Neto, A.J.S. (2015). Factorial experiment design in the front velocity modeling approach applied to chromatographic separation of glucose and fructose. Computer Modeling in Engineering & Sciences, 106(6), 441-462. https://doi.org/10.3970/cmes.2015.106.441
Vancouver Style
Prieto-Moreno A, Câmara L, Llanes-Santiago O, Neto AJS. Factorial experiment design in the front velocity modeling approach applied to chromatographic separation of glucose and fructose. Comput Model Eng Sci. 2015;106(6):441-462 https://doi.org/10.3970/cmes.2015.106.441
IEEE Style
A. Prieto-Moreno, L. Câmara, O. Llanes-Santiago, and A.J.S. Neto "Factorial Experiment Design in the Front Velocity Modeling Approach Applied to Chromatographic Separation of Glucose and Fructose," Comput. Model. Eng. Sci., vol. 106, no. 6, pp. 441-462. 2015. https://doi.org/10.3970/cmes.2015.106.441



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