Modelo anfis para la obtención de carbonato de glicerol: desarrollo y validación
Date
2019
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Abstract
El crecimiento en la producción de biodiesel genera grandes cantidades de glicerol. A partir de esta
materia prima renovable se puede obtener carbonato de glicerol, utilizando catálisis heterogénea. El
objetivo del trabajo es comprobar la capacidad de generalización de un modelo matemático desarrollado
mediante ANFIS, que caracterice la relación entre la conversión del reactivo glicerol y la masa del
carbonato de glicerol producido, empleando catalizadores heterogéneos con porcentajes variables de Cs
incorporado. Se desarrolló un modelo ANFIS con tres funciones de membresía de tipo campana
generalizada, considerando el porcentaje de conversión del reactivo glicerol, como entrada y la masa
del producto carbonato de glicerol, como salida de la reacción catalizada por óxidos mixtos adicionados
con 25% de Cs. Éste fue capaz de reproducir la relación entre los resultados de la reacción evaluados,
demostrando además, aptitud para representar dicha correspondencia al emplearse un catalizador sólido
con 10% de Cs adicionado. El desarrollo de estos modelos es de interés, dada su incidencia en la
proyección del proceso a mayores escalas.
The growth in the production of biodiesel generates large amounts of glycerol. From this renewable raw material, glycerol carbonate can be obtained by heterogeneous catalysis. The aim of this work is to verify the generality ability of a mathematical model based on artificial neural networks, which characterizes the relationship between the glycerol conversion and the mass of the glycerol carbonate produced. Mixed oxides of Mg and Al, derived from layered double hydroxides, with variable percentages of Cs incorporated were used. An ANFIS model was developed considering the conversion percentage of the reagent (glycerol) as input and the mass of the product (glycerol carbonate) as an output of the reaction catalyzed by mixed oxides with 25% content of Cs. The model proposed was also able to reproduce the relationship between the reaction parameters evaluated, demonstrating the aptitude to represent the process when a solid catalyst with 10% content of Cs was used. The development of these models is of interest, agreed with their impact on the projection of the process at highest scales.
The growth in the production of biodiesel generates large amounts of glycerol. From this renewable raw material, glycerol carbonate can be obtained by heterogeneous catalysis. The aim of this work is to verify the generality ability of a mathematical model based on artificial neural networks, which characterizes the relationship between the glycerol conversion and the mass of the glycerol carbonate produced. Mixed oxides of Mg and Al, derived from layered double hydroxides, with variable percentages of Cs incorporated were used. An ANFIS model was developed considering the conversion percentage of the reagent (glycerol) as input and the mass of the product (glycerol carbonate) as an output of the reaction catalyzed by mixed oxides with 25% content of Cs. The model proposed was also able to reproduce the relationship between the reaction parameters evaluated, demonstrating the aptitude to represent the process when a solid catalyst with 10% content of Cs was used. The development of these models is of interest, agreed with their impact on the projection of the process at highest scales.
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Keywords
Modelo, ANFIS, Carbonato de glicerol, Óxidos mixtos, Cesio
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