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RESEARCH PRODUCT
Real-time optimization of the key filtration parameters in an AnMBR: Urban wastewater mono-digestion vs. co-digestion with domestic food waste
María Victoria RuanoJosé FerrerGabriel Capson-tojoÁNgel RoblesAurora Secosubject
fouling[SDV]Life Sciences [q-bio]0208 environmental biotechnology02 engineering and technologyWastewater010501 environmental sciencesprocess control01 natural sciences7. Clean energyModellinganaerobic membrane bioreactor (AnMBR)law.inventionmodellingBioreactorsDigestion (alchemy)BiogaslawProcess controlurban wastewaterAnaerobiosisWaste Management and DisposalFiltrationTECNOLOGIA DEL MEDIO AMBIENTE0105 earth and related environmental sciencesFoulingAnaerobic membrane bioreactor (AnMBR)Food wasteUrban wastewaterMembranes ArtificialFoulingPulp and paper industry6. Clean water020801 environmental engineeringFood wasteWastewaterfood waste13. Climate actionBiofuels[SDE]Environmental SciencesEnvironmental scienceProcess controlCo digestionFiltrationdescription
[EN] This study describes a model-based method for real-time optimization of the key filtration parameters in a submerged anaerobic membrane bioreactor (AnMBR) treating urban wastewater (UWW) and UWW mixed with domestic food waste (FW). The method consists of an initial screening to find out adequate filtration conditions and a real-time optimizer applied to a periodically calibrated filtration model for minimizing the operating costs. The initial screening consists of two statistical analyses: (1) Morris screening method to identify the key filtration parameters; (2) Monte Carlo method to establish suitable initial control inputs values. The operating filtration cost after implementing the control methodology was (sic)0.047 per m(3) (59.6% corresponding to energy costs) when treating UWW and 0.067 per m(3) when adding FW due to higher fouling rates. However, FW increased the biogas productivities, reducing the total costs to (sic)0.035 per m(3). Average downtimes for reversible fouling removal of 0.4% and 1.6% were obtained, respectively. The results confirm the capability of the proposed control system for optimizing the AnMBR performance when treating both substrates. (C) 2018 Elsevier Ltd. All rights reserved.
year | journal | country | edition | language |
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2018-01-01 |