Predicción de la concentración de cloroformo en el proceso de destilación de una mezcla metanol-cloroformo mediante ARN
DOI:
https://doi.org/10.23857/dc.v8i3.2817Palabras clave:
ARN, DWSIM, cloroformo, destilaciónResumen
En este trabajo se realiza la simulación mediante el software de código abierto DWSIM de un sistema de destilación por oscilación de presión de la mezcla azeotrópica metanol-cloroformo para posteriormente predecir por redes neuronales artificiales (ARN) la concentración de cloroformo. El modelo de predicción desarrollado utiliza una capa oculta con 100 neuronas. La temperatura y la fracción molar de cloroformo en la alimentación, la relación de reflujo y temperatura de reboiler en la columna de baja y alta presión se han seleccionado como variables de entrada y la fracción molar de cloroformo y velocidad de flujo en el destilado y residuo de las columnas como variables de salida. El coeficiente de correlación de Pearson de 0.999, el error cuadrótico medio de 1.52 e-14 y el anólisis ANOVA (P-value > 0.05) confirman que no existe una diferencia estadísticamente significativa entre los datos experimentales y los valore predichos por la ARN, lo cual indica que la capacidad de predicción de la ARN es satisfactoria y que puede ser empleada para la predicción de la concentración cloroformo en el sistema.
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