Abstract
The study of the frosting behavior of CO2 in the binary CH4-CO2 is very important for energy minimization and for the smooth operation of the cryogenic purification process for natural gas due to its extensive cooling requirements. The present study focuses on the solid region of the phase envelope and the development of a predictive model using the artificial neural network (ANN) technique. It validates the model using available experimental data. The model points out the outlying data points. The ANN prediction method developed in this work can be successfully used for the vapor-solid (V-S) and vapor-liquid-solid (V-L-S) equilibrium of a CH4-CO2 binary mixture for CO2 concentration of 1 to 54.2% and a temperature range of −50°C to −200°C. The use of the model for the liquid-solid (L-S) region in its current form is not recommended because the model was not validated due to lack of experimental data in this region.
Original language | English |
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Pages (from-to) | 67-78 |
Number of pages | 12 |
Journal | Greenhouse Gases: Science and Technology |
Volume | 9 |
Issue number | 1 |
DOIs | |
Publication status | Published - Feb 1 2019 |
Keywords
- CO freezing prediction
- CO-CH phase equilibria
- artificial neural network
- cryogenic CO separation
- solid CO formation
ASJC Scopus subject areas
- Environmental Engineering
- Environmental Chemistry