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231225s2021 xx |||||o 00| ||eng c |
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|a 10.1080/09593330.2020.1733673
|2 doi
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|a pubmed25n1022.xml
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|a (NLM)32085686
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|a DE-627
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Cui, Fenghao
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Pseudo-analytical solutions for multi-species biofilm model of aerobic granular sludge
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|c 2021
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|a Text
|b txt
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|a ƒaComputermedien
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|a Date Completed 31.08.2021
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|a Date Revised 31.08.2021
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a This paper demonstrates modelling of the aerobic granular sludge (AGS) process with the pseudo-analytical solutions (PAS) of a biofilm model. A MATLAB programmed graphical user interface platform was developed to facilitate the model calculation and access. Model calibration and validation were carried out through using experimental data collected from a granular sludge sequencing batch reactor operation. The experimental and modelling results identified the distribution of heterotrophs and nitrifiers on the AGS and its contribution to the performance of wastewater treatment. The model could describe multi-species biofilms according to the distinguishing features among the three levels of PAS models. The models demonstrated increasing degrees of interaction (no interaction, competition for nitrogen and layering and protection) between heterotrophs and nitrifiers. Modelling the AGS process using PAS increases the accessibility of the simulation of multiple species in both biofilm and suspended biomass
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|a Journal Article
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|a Aerobic granular sludge
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|a SBR
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|a biofilm
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|a modelling
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|a pseudo-analytical solutions
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|a Sewage
|2 NLM
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|a Nitrogen
|2 NLM
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|a N762921K75
|2 NLM
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| 700 |
1 |
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|a Kim, Minkyung
|e verfasserin
|4 aut
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1 |
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|a Lee, Wonbae
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Park, Chul
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Kim, Moonil
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Environmental technology
|d 1993
|g 42(2021), 22 vom: 01. Sept., Seite 3421-3431
|w (DE-627)NLM098202545
|x 1479-487X
|7 nnas
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|g volume:42
|g year:2021
|g number:22
|g day:01
|g month:09
|g pages:3421-3431
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|u http://dx.doi.org/10.1080/09593330.2020.1733673
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