Revista: | Brazilian journal of chemical engineering |
Base de datos: | PERIÓDICA |
Número de sistema: | 000308766 |
ISSN: | 0104-6632 |
Autores: | Guardani, R1 Onimaru, R.S Crespo, F.C.A |
Instituciones: | 1Universidade de Sao Paulo, Departamento de Engenharia Quimica, Sao Paulo. Brasil |
Año: | 2001 |
Periodo: | Sep |
Volumen: | 18 |
Número: | 3 |
Paginación: | 267-275 |
País: | Brasil |
Idioma: | Inglés |
Tipo de documento: | Artículo |
Enfoque: | Experimental, aplicado |
Resumen en inglés | This paper presents the results of the application of a recently developed technique, based on Neural Networks (NN), in the recognition of angular distribution patterns of light scattered by particles in suspension, for the purpose of estimating concentration and crystal size distribution (CSD) in a precipitation process based on the addition of antisolvent (a model system consisting of sodium chloride, water and ethanol). In the first step, in NN model was fitted, using particles with different size distributions and concentrations. Then the model was used to monitor the process, thus enabling a fast and reliable estimation of supersaturation and CSD. Such information, which is difficult to obtain by any other means, can be used in the study of fundamental aspects of crystallization and precipitation processes |
Disciplinas: | Química |
Palabras clave: | Ingeniería química, Cristalización, Distribución por tamaño de partícula, Difracción láser, Redes neuronales, Modelación |
Keyword: | Chemistry, Chemical engineering, Crystallization, Particle size distribution, Laser diffraction, Neural networks, Modeling |
Texto completo: | Texto completo (Ver HTML) |