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dc.contributor.authorBarello, M.*
dc.contributor.authorManca, D.*
dc.contributor.authorMujtaba, Iqbal M.*
dc.date.accessioned2016-03-18T14:50:37Z
dc.date.available2016-03-18T14:50:37Z
dc.date.issued2014-07-15
dc.identifier.citationBarello M, Manca D, Patel R and Mujtaba IM (2014) Neural network based correlation for estimating water permeability constant in RO desalination process under fouling. Desalination. 345: 101-111.en_US
dc.identifier.urihttp://hdl.handle.net/10454/7942
dc.descriptionYesen_US
dc.description.abstractThe water permeability constant, (Kw) is one of many important parameters that affect optimal design and operation of RO processes. In model based studies, e.g.within the RO process model, estimation of Kw is therefore important. There are only two available literature correlations for calculating the dynamic Kw values. However, each of them are only applicable for a given membrane type, given feed salinity over a certain operating pressure range. In this work, we develop a time dependent neural network (NN) based correlation to predict Kw in RO desalination processes under fouling conditions. It is found that the NN based correlation can predict the Kw values very closely to those obtained by the existing correlations for the same membrane type, operating pressure range and feed salinity. However, the novel feature of this correlation is that it is able to predict Kw values for any of the two membrane types and for any operating pressure and any feed salinity within a wide range. In addition, for the first time the effect of feed salinity on Kw values at low pressure operation is reported. While developing the correlation, the effect of numbers of hidden layers and neurons in each layer and the transfer functions is also investigated.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttp://dx.doi.org/10.1016/j.desal.2014.04.016en_US
dc.rights© 2014 Elsevier B.V. Full-text reproduced in accordance with the publisher’s self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.subjectReverse Osmosis, Physical property models; Fouling; Water permeability elevation; Neural networks modellingen_US
dc.titleNeural network based correlation for estimating water permeability constant in RO desalination process under foulingen_US
dc.status.refereedYesen_US
dc.date.Accepted2014-04-12
dc.typeArticleen_US
dc.type.versionAccepted Manuscripten_US
refterms.dateFOA2018-07-25T14:51:35Z


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