INVESTIGADORES
AMADEO Norma Elvira
artículos
Título:
..?Approximation by neural network of the effectiveness factor in a catalyst with deactivation?.
Autor/es:
D PARISI; M CHOCRON; N AMADEO; M LABORDE
Revista:
CHEMICAL ENGINNERING TECHNOLOGY
Editorial:
WILEY-V C H VERLAG GMBH
Referencias:
Lugar: Weinheim; Año: 2002 vol. 25 p. 1183 - 1186
ISSN:
0930-7516
Resumen:
AbstractA method for estimating the effectiveness factor in a catalytic pellet submitted to deactivation using neural networks is proposed. When a catalyst is deactivated by poisoning, the function η = η (t, Φ) presents a minimum when strong diffusional resistances exist. In this particular case, the few methods published in the literature are not able to calculate η. A feedforward neural network trained with the back-propagation algorithm was used to estimate the effectiveness factor. This methodology is especially useful when the function η = η (t, Φ) presents a minimum. The predicted values using the neural network successfully fit those obtained solving the differential equation system. An extrapolation using temperatures outside the training range can be satisfactorily performed.
