Performance of predictive models in phase equilibria of complex associating systems: PC-SAFT and CEOS/GE
Cubic equations of state combined with excess Gibbs energy predictive models (like UNIFAC) and equations of state based on applied statistical mechanics are among the main alternatives for phase equilibria prediction involving polar substances in wide temperature and pressure ranges. In this work, the predictive performances of the PC-SAFT with association contribution and Peng-Robinson (PR) combined with UNIFAC (Do) through mixing rules are compared. Binary and multi-component systems involving polar and non-polar substances were analyzed. Results were also compared to experimental data available in the literature. Results show a similar predictive performance for PC-SAFT with association and cubic equations combined with UNIFAC (Do) through mixing rules. Although PC-SAFT with association requires less parameters, it is more complex and requires more computation time.
| Main Authors: | , , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Brazilian Society of Chemical Engineering
2013
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| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322013000100009 |
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| Summary: | Cubic equations of state combined with excess Gibbs energy predictive models (like UNIFAC) and equations of state based on applied statistical mechanics are among the main alternatives for phase equilibria prediction involving polar substances in wide temperature and pressure ranges. In this work, the predictive performances of the PC-SAFT with association contribution and Peng-Robinson (PR) combined with UNIFAC (Do) through mixing rules are compared. Binary and multi-component systems involving polar and non-polar substances were analyzed. Results were also compared to experimental data available in the literature. Results show a similar predictive performance for PC-SAFT with association and cubic equations combined with UNIFAC (Do) through mixing rules. Although PC-SAFT with association requires less parameters, it is more complex and requires more computation time. |
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