Literature DB >> 20347471

Mixing characterisation of full-scale membrane bioreactors: CFD modelling with experimental validation.

M Brannock1, Y Wang, G Leslie.   

Abstract

Membrane Bioreactors (MBRs) have been successfully used in aerobic biological wastewater treatment to solve the perennial problem of effective solids-liquid separation. The optimisation of MBRs requires knowledge of the membrane fouling, biokinetics and mixing. However, research has mainly concentrated on the fouling and biokinetics (Ng and Kim, 2007). Current methods of design for a desired flow regime within MBRs are largely based on assumptions (e.g. complete mixing of tanks) and empirical techniques (e.g. specific mixing energy). However, it is difficult to predict how sludge rheology and vessel design in full-scale installations affects hydrodynamics, hence overall performance. Computational Fluid Dynamics (CFD) provides a method for prediction of how vessel features and mixing energy usage affect the hydrodynamics. In this study, a CFD model was developed which accounts for aeration, sludge rheology and geometry (i.e. bioreactor and membrane module). This MBR CFD model was then applied to two full-scale MBRs and was successfully validated against experimental results. The effect of sludge settling and rheology was found to have a minimal impact on the bulk mixing (i.e. the residence time distribution).

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Year:  2010        PMID: 20347471     DOI: 10.1016/j.watres.2010.02.029

Source DB:  PubMed          Journal:  Water Res        ISSN: 0043-1354            Impact factor:   11.236


  2 in total

1.  Computational fluid dynamics simulation as a tool for optimizing the hydrodynamic performance of membrane bioreactors.

Authors:  Yan Jin; Cheng-Lin Liu; Xing-Fu Song; Jian-Guo Yu
Journal:  RSC Adv       Date:  2019-10-09       Impact factor: 3.361

2.  Hydrodynamics of an electrochemical membrane bioreactor.

Authors:  Ya-Zhou Wang; Yun-Kun Wang; Chuan-Shu He; Hou-Yun Yang; Guo-Ping Sheng; Jin-You Shen; Yang Mu; Han-Qing Yu
Journal:  Sci Rep       Date:  2015-05-22       Impact factor: 4.379

  2 in total

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