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Indian Journal of Chemical Technology (IJCT) >
IJCT Vol.11 [2004] >
IJCT Vol.11(1) [January 2004] >
| Title: | Prediction of reverse osmosis performance using artificial neural network |
| Authors: | Murthy, Z V P
Vora, Mehul M |
| Issue Date: | Jan-2004 |
| Publisher: | CSIR |
| IPC Code: | B01D61/02 |
| Abstract: | Reverse osmosis (RO) has found extensive usage in the
fields of desalination and pollution control. In the present work, an attempt
is made to model the separation of sodium chloride-water system by reverse
osmosis using neural nets. Experimental data are used to train the network
developed for the said system. The training data included the feed
concentration range from 1000 to 30000 ppm, pressure range from 20 to 100 atm,
and feed rates from 300 to 1500 mL/min. The network thus developed has been
found to predict the system variables within the error range of ±1%, except for sudden deviations in process parameters, and initial
and final value of flow rates at low pressures. Nearly the same trend, that is,
maximum errors at lower pressures and higher flow rates, were observed in the
prediction of RO performance with
membrane transport models, reported earlier. The reasons for this may be the
unsteady state behaviour of the system, or system instability or error in experimentation.
Such deviations are not of much importance, because the predicted and
experimental values are within the satisfactory range. |
| Page(s): | 108-115 |
| ISSN: | 0975-0991 (Online); 0971-457X (Print) |
| Source: | IJCT Vol.11(1) [January 2004]
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