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MODELING OF CO2 SOLUBILITY IN METHYLDIETHANOLAMINE + PIPERAZINE AQUEOUS SOLUTIONS USING NEURAL NETWORK MODEL

NASERI, AHMAD NAJDAN (2012) MODELING OF CO2 SOLUBILITY IN METHYLDIETHANOLAMINE + PIPERAZINE AQUEOUS SOLUTIONS USING NEURAL NETWORK MODEL. UNIVERSITI TEKNOLOGI PETRONAS, UNIVERSITI TEKNOLOGI PETRONAS. (Unpublished)

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Abstract

Acid gas removal processing from natural gas, synthesis gas and refinery gas stream is very important in plant industry to prevent corrosion in the subsequent piping and as per required by users. Generally, the gaseous feedstock stream is contacted with alkanolamine aqueous solution countercurrently in the acid gas absorber tower. The acid gas will partly be converted to non-volatile ionic species by the basic amine and partly be dissolved physically in the liquid solution. Acid gas removal unit is very important in petrochemical processing plant. There had been great numbers of studies on the solubility of CO2 in methyldiethanolamine (MDEA) aqueous solutions. M. Vahidi used extended Debye- Huckle model to explain on the solubility data of CO2 absorption in MDEA and Piperazine (PZ) at certain concentration, temperature and pressure. The average absolute relative deviation percent (AAD %) reported were 8.11%. Model of solubility of CO2 in MDEA aqueous solution using neural network model is presented. In this work, neural network was used to determine solubility of CO2 in MDEA + PZ solutions based on 3 experimental research data, M. Vahidi (Mehdi Vahidi, 2009), H. B. Liu (Hua-Bing Liu, 1999) and B. Si Ali (B. Si. Ali, 2004). Data prediction was conducted at different temperature and partial pressure and for various solution concentrations. The model developed has an absolute relative deviation of 3.047% compared to other papers; M. Vahidi with 8.11% deviation, B. Lemoine of 7.84% and H. B. Liu with 11.6% error deviation. The model also not capable to extrapolate prediction of CO2 loading on zero promoter system due to the experimental data at zero promoter is not included in the training process.

Item Type: Final Year Project
Academic Subject : Academic Department - Chemical Engineering - Advance Process Control
Subject: T Technology > TP Chemical technology
Divisions: Engineering > Chemical
Depositing User: Sharifah Fahimah Saiyed Yoep
Date Deposited: 01 Apr 2013 09:12
Last Modified: 25 Jan 2017 09:40
URI: http://utpedia.utp.edu.my/id/eprint/6098

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