Biomass viability: An experimental study and the development of an empirical mathematical model for submerged membrane bioreactor

Zuthi, M.F.R.; Ngo, Huu Hao; Guo, Wenshan; Nghiem, Long D.; Hai, Faisal I.; Xia, Siqing; Zhang, Z.Q.; Li, J.X.

doi:10.1016/j.biortech.2015.04.104

Cited by 8 publications

(2 citation statements)

References 21 publications

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“…Deng et al (2014) noted that the added sponge can prevent cake formation and pore blockage in a submerged MBR that are mainly contributed by soluble microbial products in activated sludge. Zuthi et al (2015) developed a mathematical model for a sponge submerged membrane bioreactor considering the biomass viability and extra-cellular polymeric substances redundancy. The model was validated by experimental data and was used for making process performance prediction.…”

Section: External Additivesmentioning

confidence: 99%

Membrane bioreactor: A mini review on recent R&D works

Huang

Lee

2015

Bioresource Technology

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Section: External Additivesmentioning

confidence: 99%

Membrane bioreactor: A mini review on recent R&D works

Huang

Lee

2015

Bioresource Technology

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“…The existing MBR models are derived from activated sludge model (ASM) with a physical membrane filtration process (Ng and Kim 2007). Biomass kinetic models and membrane fouling models are major components to describe the MBR process (Diez et al 2014;Zuthi et al 2015). Development of MBER models will need to synergistically integrate MFC models with MBR models.…”

Section: Responsible Editor: Marcus Schulzmentioning

confidence: 99%

Development of a dynamic mathematical model for membrane bioelectrochemical reactors with different configurations

2015

Environ Sci Pollut Res

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Membrane bioelectrochemical reactors (MBERs) integrate membrane filtration into bioelectrochemical systems for sustainable wastewater treatment and recovery of bioenergy and other resource. Mathematical models for MBERs will advance the understanding of this technology towards further development. In the present study, a mathematical model was implemented for predicting current generation, membrane fouling, and organic removal within MBERs. The relative root-mean-square error was used to examine the model fit to the experimental data. It was found that a constant to determine how fast the internal resistance responds to the change of the anodophillic microorganism concentration could have a dominant impact on current generation. Hydraulic cross-flow exhibited a minor effect on membrane fouling unless it was reduced below 0.5 m s −1 . This MBER model encourages further optimization and eventually can be used to guide MBER development.

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