Modelación de un tratamiento avanzado de aguas residuales, provenientes de una planta de envasado, usando las metodologías de análisis de superficie de respuesta (ASR) y de redes neuronales (RNA)
DOI:
https://doi.org/10.29105/qh3.2-97Keywords:
Coagulación, floculación, ósmosis inversa (OI), análisis de superficie de respuesta (ASR) y redes neuronales artificiales (RNA)Abstract
El agua residual estudiada fue obtenida de una planta productora de latas, localizada en el centro de la República Mexicana. Esta agua residual fue caracterizada y tratada a nivel laboratorio y planta piloto usando procesos de coagulación y floculación. Tres coagulantes y dos floculantes fueron usados en seis combinaciones y un diseño factorial, así como un análisis de superficie de respuesta (ASR) fueron llevados a cabo para explorar los efectos de pH, concentraciones de coagulante y floculante y velocidad de agitación. Del mismo modo pruebas de sedimentación en columna fueron llevadas a cabo, a las mejores condiciones de operación, para determinar el tiempo de detención para la planta piloto. Estas condiciones fueron utilizadas para construir una planta piloto para tratar 15.14 L/min, la cual incluye una membrana de ósmosis inversa (0I). En la prueba de jarras, las mejores condiciones de remoción UNT con cero turbidez fueron alcanzadas por la combinación de Al2(SO4)3-NALCO 9907, a 100 min-1 y pH ácido. En la planta piloto fue requerido un tiempo de detención de 2 horas para remover el 100 % de los sólidos suspendidos en el tanque de sedimentación. La unidad de OI permitió el incremento de remoción de los sólidos totales disueltos a 96.1 % permitiendo una recuperación máxima de agua residual de casi 72 %. Los datos de la unidad de OI fueron exitosamente modelados mediante redes neuronales artificiales (ANN). Una red de cuatro capas alimentada hacia adelante con un algoritmo de propagación hacia atrás fue usada para entrenar todos los modelos de RNA. Los datos esperados y experimentales fueron bien correlacionados y fue alcanzado un coeficiente de determinación de 0.99.
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Copyright (c) 2013 A. Salgado, E. Soto, R. Gómez, F. J. Cerino, R. B. García, M. T. Garza, J. A. Loredo , M. M. Alcalá
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