| Autor: |
Vanessa Villazón-León, Adrián Bonilla-Petriciolet, Juan Carlos Tapia-Picazo |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
International Journal of Chemical Engineering, Vol 2022 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1687-8078 |
| DOI: |
10.1155/2022/5943833 |
| Popis: |
The thermodynamic properties of pure compounds are relevant data for process systems engineering. Different first-order group contribution models have been reported in the literature to calculate these properties and they are also widely employed in commercial process simulators. However, they may have some limitations and, consequently, a reliable comparison of these models is required to analyze their performance and to determine the best alternative for the calculation of pure compound properties. This paper reports the implementation and evaluation of several first-order group contribution models to calculate the normal boiling point and critical properties (temperature, pressure, and volume) of pure compounds. The performance of these models was characterized and compared for several compound families using a standardized approach to determine their group contributions and parameters. An artificial neural network model was also applied and assessed to improve the estimations obtained with the best group contribution models. Results showed that the calculation of critical temperature was challenging for several compound families where AARD values ranged from 0.05 to 56.28%, while the group contribution models were more accurate to estimate the critical volume with AARD values ranging from 0.48 to 35.99%. This study allows us to identify the limitations and gaps of this type of thermodynamic models with the objective of improving its performance for the calculation of pure compound thermodynamic properties. The findings of this study can help to enhance the capabilities of thermodynamic models for the calculation of the normal boiling point and critical properties of pure compounds, which are relevant for the process systems engineering of new operations and products. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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