Neural Network Based Correlations for Estimating the First and Second Dissociation Constant of Carbonic Acid in Seawater

摘要

Neural Network (NN) can be used successfully in modelling, simulation andrnoptimisation of desalination processes. In this paper, three NN based correlations arerndeveloped for predicting the first dissociation constant (K1) and the second dissociationrnconstant (K2) of carbonic acid in seawater as function of temperature and salinity. Theserncorrelations are developed from different sources of the experimental data from thernliterature. It is found that the NN based correlation can predict K1 and K2 very close tornthe experimental data. These correlations are currently being implemented in the fullrnMSF (Multi-Stage Flash) desalination process model for performance evaluation of thernprocess which will be reported elsewhere.