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dc.contributor.authorSatish, S.-
dc.contributor.authorSetty ., Y.P-
dc.date.accessioned2024-11-19T06:42:11Z-
dc.date.available2024-11-19T06:42:11Z-
dc.date.issued2005-
dc.identifier.citation10.1016/j.icheatmasstransfer.2004.06.005en_US
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/1535-
dc.descriptionNITWen_US
dc.description.abstractThe work involves experimentation on drying of solids in a continuous fluidized bed dryer covering different variables like bed temperature, gas flow rate, solids flow rate and initial moisture content of solids. The data are modeled using artificial neural networks. The results obtained from artificial neural networks are compared with those obtained using Tanks-in-series model. It was found that results obtained from ANN fit the experimental data more accurately compared to the RTD model with less percentage error. This indicates a better fit of artificial neural networks to experimental data compared to various mathematical modelsen_US
dc.language.isoenen_US
dc.publisherInternational Communications in Heat and Mass Transferen_US
dc.subjectFluidized bed dryingen_US
dc.subjectModelingen_US
dc.subjectArtificial neural networksen_US
dc.subjectResidence time distributionen_US
dc.titleModeling of a continuous fluidized bed dryer using artificial neural networksen_US
dc.typeArticleen_US
Appears in Collections:Chemical Engineering

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