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Authordc.contributor.authorMuñoz Pérez, J. 
Authordc.contributor.authorLeyton, P. 
Authordc.contributor.authorPaipa, C. 
Authordc.contributor.authorSoto, J. P. 
Authordc.contributor.authorBrunet, J. 
Authordc.contributor.authorGómez Jeria, Juan 
Authordc.contributor.authorCampos Vallette, Marcelo 
Cita de ítemdc.identifier.citationJournal of Molecular Structure 1122 (2016) 198e204es_ES
Abstractdc.description.abstractAccurate characterization of two phase bubbly flows is crucial in many industrial processes such as fluidized reactors, ore froth flotation, etc. The bubble size determines the rate at which components present in the gas phase are transferred to the surroundings and vice versa while bubble rate defines the appropriate bubbly flow regime occurring in the heterogeneous system. This research work employs deep neural networks (DNNs) to predict bubble size and bubble rate using data obtained from validated computational fluid dynamics (CFD) computations. Pure water and slurry (in conditions similar to those employed in mineral froth flotation) case studies are evaluated. It is found that the DNN can predict the CFD results accurately when using four hidden layers, describing discontinuities in the bubbly flow regime. The relative errors computed between the CFD data and the prediction obtained by the DNN is as low as 8.8% and 1.8% for bubble size and bubble rate, respectively. These results confirm that the DNN can be applied to sophisticated fluid dynamics systems and allow developing better control process strategies since once the DNN is trained critical variables can be computed very efficiently. The slurry case study, although restricted to the application of mineral froth flotation, can also be generalized to other industrial operations keeping the exact same procedure. (C) 2016 Elsevier Ltd. All rights reserved.es_ES
Patrocinadordc.description.sponsorshipCONICYT-Chile PIA ACT 1120es_ES
Type of licensedc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile*
Link to Licensedc.rights.uri*
Sourcedc.sourceJournal of Molecular Structurees_ES
Keywordsdc.subjectConstant flow conditionses_ES
Títulodc.titleRaman and surface enhanced Raman scattering study of the orientation of cruciform 9,10-anthracene thiophene and furan derivatives deposited on a gold colloidal surfacees_ES
Document typedc.typeArtículo de revistaes_ES
Indexationuchile.indexArtículo de publicación ISIes_ES

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Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Chile