Abstract
No
Neural Network (NN) is widely used in all aspects of;
process engineering activities, such as modeling, design,;
optimization and control. In this paper work, in absence of real;
plant data, simulated data (such as sales gas flow rate, pressure,;
raw gases flow rates and input heat flow associated with a heater;
used after dehydration) from a detailed model of Kailashtilla gas;
processing plant (KGP) within HYSYS is used to develop NN;
based model. Thereafter NN based model is trained and;
validated from HYSYS simulator generated data and that;
framework can predict the output data (sales gas flow rate and;
pressure) very closely with the simulated HYSYS plant data.;
The preliminary results show that the NN based correlation is;
adequately able to model and generate workable profiles for the;
process.