Modelling of an anaerobic plug-flow reactor. Process analysis and evaluation approaches with non-ideal mixing considerations

[Display omitted] •Two models for considering non-ideal mixing in an anaerobic PFR were implemented.•Calibration and validation were carried out with data from a pilot scale reactor.•Parameter estimation for AD of cow manure in continuous operation was performed.•Changes in mixing parameters did not...

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Veröffentlicht in:Bioresource technology 2018-07, Vol.260, p.95-104
Hauptverfasser: Donoso-Bravo, Andrés, Sadino-Riquelme, Constanza, Gómez, Daniel, Segura, Camilo, Valdebenito, Emky, Hansen, Felipe
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Sprache:eng
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Zusammenfassung:[Display omitted] •Two models for considering non-ideal mixing in an anaerobic PFR were implemented.•Calibration and validation were carried out with data from a pilot scale reactor.•Parameter estimation for AD of cow manure in continuous operation was performed.•Changes in mixing parameters did not cause significant changes in biogas production.•The PF conventional model slightly outperformed the non-ideal mixing approaches. This study shows the implementation of the Anaerobic Digestion Model (ADM1) in an anaerobic plug-flow reactor (PFR) with two approaches based on the use of consecutive continuous stirred tank reactors (CSTR) connected in serie for considering non-ideal mixing. The two-region (TR) model splits each CSTR into two regions, while the particulate retention (PR) model adds a retention parameter. The models were calibrated and validated based on experimental data from a bench-scale reactor treating cow manure. The PFR conventional model slightly outperformed the non-ideal mixing approaches. However, the PR model showed an increase in biomass retention time treating high solid content substrate. Biogas production was not sensitive to variations of the mixing parameters. The liquid fraction content was better represented by the PR model than the PFR and TR models. The study shows how reactor modelling is useful for monitoring and supervising biogas plants.
ISSN:0960-8524
1873-2976
DOI:10.1016/j.biortech.2018.03.082