DocumentCode :
599708
Title :
Forecasting parameter of Kailashtilla gas processing plant using Neural Network
Author :
Kundu, Sandipan ; Hasan, Aftab ; Sowgath, M.T.
Author_Institution :
Dept. of Chem. Eng., Bangladesh Univ. of Eng. & Technol., Dhaka, Bangladesh
fYear :
2012
fDate :
20-22 Dec. 2012
Firstpage :
486
Lastpage :
489
Abstract :
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.
Keywords :
flow simulation; heat transfer; industrial plants; learning (artificial intelligence); natural gas technology; neural nets; petrochemicals; pressure; production engineering computing; HYSYS simulator; HYSYS software; Kailashtilla gas processing plant; NN based correlation; control activity; design activity; forecasting parameter; input heat flow; modeling activity; neural network; optimization activity; pressure; raw gas flow rate; sales gas flow rate; Artificial neural networks; Biological neural networks; Correlation; Feeds; Heating; Neurons; Training; HYSYS; Kailashtilla Gas Processing plant; Neural Network (NN);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical & Computer Engineering (ICECE), 2012 7th International Conference on
Conference_Location :
Dhaka
Print_ISBN :
978-1-4673-1434-3
Type :
conf
DOI :
10.1109/ICECE.2012.6471593
Filename :
6471593
Link To Document :
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