Comparison of Two-Phase Porosity Models for High Capacity Random Packing
High capacity random packing is used in absorption applications where a large throughput of gas is required while simultaneously maintaining as low a pressure loss as possible. Utilising computational fluid dynamics to capture the internal flow patterns and transients when designing packed bed tower...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN FR |
| Publicado: |
EDP Sciences
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/0455d1d9d11e4ae1abead51f35df088e |
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| Sumario: | High capacity random packing is used in absorption applications where a large throughput of gas is required while simultaneously maintaining as low a pressure loss as possible. Utilising computational fluid dynamics to capture the internal flow patterns and transients when designing packed bed towers can be advantageous in respect to expected performance and cost optimisation. However, capturing the direct interaction between gas, liquid and packing is not computationally feasible and therefore the packed bed is modelled as a porous media. In this work four different porosity model are calibrated with idealised equations to data for the high capacity packing IMTP or I-Ring. The different models are evaluated based on their ability to predict pressure loss and liquid holdup in the packed bed. An Eulerian two-phase model with a porous zone representing the packed bed is setup in a cylindrical tower. The CFD results are compared to the predictions of the best performing porosity model. It was found that the best performing model had an absolute mean error of 6.7% when calibrated with the idealised equations. This error increased to 10.5% when the porosity model was implemented into the CFD model. |
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