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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Water Researcharrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Water Research
Article . 2004 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
Water Research
Article . 2004
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Modeling the development of biofilm density including active bacteria, inert biomass, and extracellular polymeric substances

Authors: Bruce E. Rittmann; Chrysi Laspidou;

Modeling the development of biofilm density including active bacteria, inert biomass, and extracellular polymeric substances

Abstract

We present the unified multi-component cellular automaton (UMCCA) model, which predicts quantitatively the development of the biofilm's composite density for three biofilm components: active bacteria, inert or dead biomass, and extracellular polymeric substances. The model also describes the concentrations of three soluble organic components (soluble substrate and two types of soluble microbial products) and oxygen. The UMCCA model is a hybrid discrete-differential mathematical model and introduces the novel feature of biofilm consolidation. Our hypothesis is that the fluid over the biofilm creates pressures and vibrations that cause the biofilm to consolidate, or pack itself to a higher density over time. Each biofilm compartment in the model output consolidates to a different degree that depends on the age of its biomass. The UMCCA model also adds a cellular automaton algorithm that identifies the path of least resistance and directly moves excess biomass along that path, thereby ensuring that the excess biomass is distributed efficiently. A companion paper illustrates the trends that the UMCCA model is able to represent and shows a comparison with experimental results.

Related Organizations
Keywords

Bacterial Physiological Phenomena, Models, Biological, Waste Disposal, Fluid, Water Purification, Automation, Biopolymers, Bioreactors, Biofilms, Biomass, Algorithms, Forecasting

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    139
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
139
Top 10%
Top 10%
Top 10%