Murphree vapor efficiency prediction in SCC columns by computational fluid dynamics analysis
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Mortaza Zivdar
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Nasim Shahrouei
Abstract
The spinning cone columns (SCC) are one of the distillation columns with increasing applications in food industries. The geometrical complexity and different flow regimes, besides the presence of moving parts, make the design and analysis of these columns challenging. Computational fluid dynamics analysis of SCC columns has shown promising results in analyzing the performance of these towers. The majority of previous works were pertinent to the air/water systems. Therefore, the application of these results to real systems is not very clear. In this study, the liquid film thickness, mass transfer coefficients, HETP, and Murphree vapor efficiency for the water/ethanol system have been predicted in a pilot-scale column. The results show that by increasing the radial distance from the axis, the thickness of the liquid film gradually decreases. This finding is also in consistent with the experimental results. The maximum thickness of the liquid film is <1 mm and is near the axis. Mass transfer coefficients in the liquid phase and in the gas phase increase slightly with increasing flow velocity and remain almost unchanged. The average values of these coefficients in the liquid and gas phases are 0.023 (s−1) and 1.21 (s−1), respectively. HETP increased with increasing gas velocity, the range of which varies between 0.092 and 0.375 m. Also, Murphree vapor efficiency at three rotational speeds of 550, 750, and 1000 rpm are predicted and compared with the experimental data. The results show that the efficiency has been decreased by increasing the strip ratio and increased by increasing the rotational speed. Minimum and maximum efficiencies obtained are 3.48 and 24.56% corresponding to strip ratio = 27.1% and RPM = 550 plus strip ratio = 9.15% and RPM = 1000, respectively. The predicted efficiencies are in a reasonable agreement (within 10.3%) with experimental data.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
Appendix: Sample calculation of Murphree vapour efficiency
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© 2021 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Viscosity prediction of hydrocarbon binary mixture using an artificial neural network-group contribution method
- Design of an environmentally friendly fuel based on a synthetic composite nano-catalyst through parameter estimation and process modeling
- Numerical study of coupled natural convection to surface radiation in an open cavity submitted to lateral or corner heating
- A comparative study of thermodynamic models to describe the VLE of the ternary electrolytic mixture H2O–NH3–CO2
- Murphree vapor efficiency prediction in SCC columns by computational fluid dynamics analysis
- Retrofitting recycled stripping gas in a glycol dehydration regeneration unit
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Viscosity prediction of hydrocarbon binary mixture using an artificial neural network-group contribution method
- Design of an environmentally friendly fuel based on a synthetic composite nano-catalyst through parameter estimation and process modeling
- Numerical study of coupled natural convection to surface radiation in an open cavity submitted to lateral or corner heating
- A comparative study of thermodynamic models to describe the VLE of the ternary electrolytic mixture H2O–NH3–CO2
- Murphree vapor efficiency prediction in SCC columns by computational fluid dynamics analysis
- Retrofitting recycled stripping gas in a glycol dehydration regeneration unit
