Modeling of bubble surface area flux in an industrial rougher column using artificial neural network and statistical techniques / M. Massinaei in Minerals engineering, Vol. 23 N° 2 (Janvier 2010)  

Public ISBD [article]  inMinerals engineering > Vol. 23 N° 2 (Janvier 2010) . - pp. 83-90 Titre : Modeling of bubble surface area flux in an industrial rougher column using artificial neural network and statistical techniques Type de document : texte imprimé Auteurs : M. Massinaei, Auteur ; R. Doostmohammadi, Auteur Article en page(s) : pp. 83-90 Note générale : Génie Minier Métallurgie Langues : Anglais (eng) Mots-clés : Froth flotation Flotation machines Modeling Neural networks Index. décimale : 622 Industrie minière Résumé : Previous studies in mechanical and column flotation cells have shown that bubble surface area flux (Sb) is an appropriate indicator of gas dispersion in a flotation cell which has a relatively strong correlation with flotation rate constant. In the present investigation, based on extensive tests conducted in an industrial Metso Minerals CISA flotation column (4 m in diameter and 12 m in height) in a rougher circuit, Sb as a function of the most significant operating variables which affect gas dispersion in a flotation column (i.e. superficial gas velocity, slurry density (solids%) and frother dosage/type) was modeled using artificial neural network (ANN) and statistical (non-linear regression) techniques. The models were developed taking into consideration a data set consisting of 82 experimental tests conducted in an industrial rougher column (at a copper concentrator in Iran) operating under a variety of experimental conditions. This paper outlines the development of the models and validation using a number of randomly selected datasets. Limitations of the present models are discussed and comments and recommendations on further investigations are given. DEWEY : 622 ISSN : 0892-6875 En ligne : http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6VDR-4XDKC9K-1&_user=6 [...] [article] Modeling of bubble surface area flux in an industrial rougher column using artificial neural network and statistical techniques [texte imprimé] / M. Massinaei, Auteur ; R. Doostmohammadi, Auteur . - pp. 83-90. Génie Minier Métallurgie Langues : Anglais (eng) in Minerals engineering > Vol. 23 N° 2 (Janvier 2010) . - pp. 83-90 Mots-clés : Froth flotation Flotation machines Modeling Neural networks Index. décimale : 622 Industrie minière Résumé : Previous studies in mechanical and column flotation cells have shown that bubble surface area flux (Sb) is an appropriate indicator of gas dispersion in a flotation cell which has a relatively strong correlation with flotation rate constant. In the present investigation, based on extensive tests conducted in an industrial Metso Minerals CISA flotation column (4 m in diameter and 12 m in height) in a rougher circuit, Sb as a function of the most significant operating variables which affect gas dispersion in a flotation column (i.e. superficial gas velocity, slurry density (solids%) and frother dosage/type) was modeled using artificial neural network (ANN) and statistical (non-linear regression) techniques. The models were developed taking into consideration a data set consisting of 82 experimental tests conducted in an industrial rougher column (at a copper concentrator in Iran) operating under a variety of experimental conditions. This paper outlines the development of the models and validation using a number of randomly selected datasets. Limitations of the present models are discussed and comments and recommendations on further investigations are given. DEWEY : 622 ISSN : 0892-6875 En ligne : http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6VDR-4XDKC9K-1&_user=6 [...]

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