Use of Artificial Neural Network for the Correlation of Vapour-Liquid Equilibrium Data for Hydrocarbon Ternary System (Ethane-n-Butane-n-Pentane)

Daniyan, I.A and Adeodu, A.O and Omitola, O.O and Daniyan, O.L and Yusuff, A.S (2013) Use of Artificial Neural Network for the Correlation of Vapour-Liquid Equilibrium Data for Hydrocarbon Ternary System (Ethane-n-Butane-n-Pentane). Use of Artificial Neural Network for the Correlation of Vapour-Liquid Equilibrium Data for Hydrocarbon Ternary System (Ethane-n-Butane-n-Pentane), 4 (8). ISSN 2229-5518

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Abstract

In this study, existing experimental vapour-liquid equilibrium (VLE) data covering a wide range of temperature, phase composition and pressure for ethane-n-butane-n-pentane was correlated using MATLAB (Matrix Laboratory) software. To increase the reliability of correlations, neural network was trained using existing vapour-liquid equilibrium data with the aid of Levenberg Marquardt algorithm. Network parameters are fine-tuned until the output generated by simulation are checked and observed to match with pre-determined experimental V L E data. It was found that there is high degree of coherence between the chosen targets from experimental data and predicted values. This confirms that correlations and predictions of V L E data using neural network is efficient and significant.

Item Type: Article
Uncontrolled Keywords: Correlation, Levenberg Marquardt algorithm, MATLAB, Network parameters, Neural network, Simulation, Vapour-liquid equilibrium (VLE)
Subjects: T Technology > TH Building construction
Divisions: Faculty of Engineering, Science and Mathematics > School of Chemistry
Depositing User: Mr Tayo Okunlola
Date Deposited: 21 Nov 2017 13:38
Last Modified: 21 Nov 2017 13:38
URI: http://eprints.abuad.edu.ng/id/eprint/289

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