چهارشنبه 08 بهمن 1399
News > Experimental data, thermodynamic and neural network modeling of CO2 absorption capacity for 2-amino...


  Print        Send to Friend

2020

Experimental data, thermodynamic and neural network modeling of CO2 absorption capacity for 2-amino...

Experimental data, thermodynamic and neural network modeling of CO2 absorption capacity for 2-amino-2-methyl-1-propanol (AMP) + Methanol (MeOH) + H2O system

 

Authors Peyman Pakzad, Masoud Mofarahi, Amir Abbas Izadpanah, Morteza Afkhamipour
Publication Date 2020/1/1
Journal Journal of Natural Gas Science and Engineering
Volume 73
Pages 103060
Publisher Elsevier

ABSTRACT

In this study, new experimental data were reported for CO2 solubility in H2O + 2-amino-2-methyl-1-propanol (AMP) + methanol (MeOH) system by using a static-synthetic apparatus. The experiments were done in the temperature range of 313.15–353.15 K and the CO2 partial pressure range of 1.08–303.7 kPa. The concentrations (wt. %) of mixed AMP + MeOH were 8.2 + 41.2, 16.5 + 32.2, 22.3 + 27.7 and 30.6 + 19.4. Also, the density of the hybrid solvent was measured using a pycnometer similar to concentration and temperature ranges. To correlate the experimental CO2 solubility data, three different models namely modified Kent-Eisenberg, Deshmukh-Mather, and artificial neural network (ANN) were used. The density data were correlated by Redlich-Kister equation. The results showed that the ANN modeling with an average absolute relative deviation (AARD%) and a correlation coefficient (R2) of 1.95 and 0.9981, respectively, were in good agreement with the experimental CO2 loading data in comparison with other models.


15:03 - 14/12/2020    /    Number : 3568    /    Show Count : 10



Close