Membrane and Water Treatment

  • 제2권2호
  • /
  • Pages.105-119
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  • 2011
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  • 2005-8624(pISSN)
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  • 2092-7037(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Multi-Dimension Scaling as an exploratory tool in the analysis of an immersed membrane bioreactor

  • Bick, A. (Department of Industrial Engineering and Management, Jerusalem College of Technology) ;
  • Yang, F. (J. Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev) ;
  • Shandalov, S. (J. Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev) ;
  • Raveh, A. (The school of business administration, The Hebrew University) ;
  • Oron, G. (J. Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev)
  • 투고 : 2009.12.21
  • 심사 : 2010.10.15
  • 발행 : 2011.04.25
⟨ 이전 논문 다음 논문 ⟩

초록

This study presents the tests of an Immersed Membrane BioReactor (IMBR) equipped with a draft tube and focuses on the influence of hydrodynamic conditions on membrane fouling in a pilot-scale using a hollow fiber membrane module of ZW-10 under ambient conditions. In this system, the cross-flow velocities across the membrane surface were induced by a cylindrical draft-tube. The relationship between cross-flow velocity and aeration strength and the influence of the cross-flow on fouling rate (under various hydrodynamic conditions) were investigated using Multi-Dimension Scaling (MDS) analysis. MDS technique is especially suitable for samples with many variables and has relatively few observations, as the data about Membrane Bio-Reactor (MBR) often is. Observations and variables are analyzed simultaneously. According to the results, a specialized form of MDS, CoPlot enables presentation of the results in a two dimensional space and when plotting variables ratio (output/input) rather than original data the efficient units can be visualized clearly. The results indicate that: (i) aeration plays an important role in IMBR performance; (ii) implementing the MDS approach with reference to the variables ratio is consequently useful to characterize performance changes for data classification.

키워드

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