A cubic equation of state based on saturated vapor modeling and the application of model-based design of experiments for its validation
For simulation of chemical processes, a sufficiently accurate mathematical description of phase equilibria is essential. In order to achieve this, high-quality measured data and model equations are indispensable. A new gamma-function as a replacement for the common alpha-function in cubic equations...
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| Main Authors: | , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
22 April 2010
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| In: |
Chemical engineering science
Year: 2010, Volume: 65, Issue: 14, Pages: 4194-4207 |
| ISSN: | 1873-4405 |
| DOI: | 10.1016/j.ces.2010.04.025 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.ces.2010.04.025 Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S0009250910002642 
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| Author Notes: | Alexander Kud, Stefan Körkel, Stefan Maixner |
| Summary: | For simulation of chemical processes, a sufficiently accurate mathematical description of phase equilibria is essential. In order to achieve this, high-quality measured data and model equations are indispensable. A new gamma-function as a replacement for the common alpha-function in cubic equations of state is proposed here for polar compounds with an existing vapor phase. The equation parameters of the gamma-function are fitted to state data on the dew line instead of, as usual, on the vaporization curve. The quality of the description is compared to the customary equations of state using statistical parameters. A further validation used for the description is the prediction of caloric parameters and the comparison thereof with measured data. By means of model-based experimental design, the gamma-function and the equation of state based thereon are validated. Multiple setpoint optimization allows a uniform experimental design for validation of a vapor pressure equation and of a vapor density equation to be calculated for polar compounds. The experiments calculated optimally in this way reduce large test series to a few experiments which are significant for the specific model equation. |
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| Item Description: | Gesehen am 07.03.2023 |
| Physical Description: | Online Resource |
| ISSN: | 1873-4405 |
| DOI: | 10.1016/j.ces.2010.04.025 |