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Autor(en) / Beteiligte
Titel
A new hydrodynamic analogy model for the determination of transport phenomena in random packings
Ist Teil von
  • Chemical engineering science, 2021-04, Vol.233, p.116246, Article 116246
Ort / Verlag
Elsevier Ltd
Erscheinungsjahr
2021
Link zum Volltext
Quelle
Elsevier ScienceDirect Journals Complete
Beschreibungen/Notizen
  • •A new model was proposed for the description of separation processes in random packings.•Fluid dynamics in random packings was captured by simplified flow pattern.•Absorption measurements of CO2 into aqueous sodium hydroxide solution .•The model was successfully validated against experimental data. A new model for absorption processes in columns equipped with random packings based on the hydrodynamic analogy approach is presented. The packed bed is represented by a bundle of cylindrical channels with the same diameter equal to the hydraulic diameter of the bed. The liquid flow in the real packing is captured by a combination of film, jet and drop flow which are assumed to be the dominating flow patterns in the bed. The film flow is considered as attached to the inner surface of the channels, while jets and drops are falling through the channel center. Each of the flow patterns is modelled independently of one another, in a separate channel type with counter-current gas flow. After certain packing specific lengths of undisturbed flow, each phase is mixed to govern the redirection of the flow and the transition from film to jet and drop flow and vice versa as well as the mixing of gas flows from neighboring packing elements. The fluid dynamics as well as heat and mass transfer are described by the respective rigorous conservation equations. Both phases are related by conjugate boundary conditions at the phase interface. The reactive CO2 absorption into aqueous sodium hydroxide solution is investigated experimentally for two random packings of type 50 mm Pall-Ring and ENVIPAC 2 in an industrial-scale column. The model is validated against the experimentally obtained data.
Sprache
Englisch
Identifikatoren
ISSN: 0009-2509
eISSN: 1873-4405
DOI: 10.1016/j.ces.2020.116246
Titel-ID: cdi_crossref_primary_10_1016_j_ces_2020_116246

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