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dc.creatorLaspidou, C. S.en
dc.date.accessioned2015-11-23T10:37:30Z
dc.date.available2015-11-23T10:37:30Z
dc.date.issued2014
dc.identifier10.1080/19443994.2013.822336
dc.identifier.issn1944-3994
dc.identifier.urihttp://hdl.handle.net/11615/30194
dc.description.abstractThis study presents the strengths and weaknesses of a biofilm erosion probability algorithm that can be used in cellular automaton and individual-based biofilm simulation models. The erosion probability is calculated using data on localized biofilm mechanical properties, expressed through the composite biofilm Young's modulus-a measure of biofilm strength that varies in time and space-and on fluid hydrodynamic shear stress. Analysis of trends shows that biofilm detachment is the process that results from the competition between biofilm strength and hydrodynamic shear stress exerted on it by the fluid, with hydrodynamics being more important when biofilm strength is low and vice versa. From the modeling sample analyzed in this study, it is evident that for biofilms with cluster and mushroom formations, erosion probabilities are lower in the crevices formed between two clusters-where substrate is depleted-and higher at the top of the clusters where there is fresh biomass growth. When compared to other detachment methodologies extensively used by biofilm modeling researchers, such as the detachment speed that is a function of the square of the distance to the solid substratum, it is proved that the probability of erosion algorithm would give similar results.en
dc.sourceDesalination and Water Treatmenten
dc.source.uri<Go to ISI>://WOS:000343665400009
dc.subjectUMCCAen
dc.subjectBiofilm detachmenten
dc.subjectBiofilm modelingen
dc.subjectProbability of detachmenten
dc.subjectBiofilm erosionen
dc.subjectBiofilm mechanical propertiesen
dc.subjectCellular automatonen
dc.subjectEXTRACELLULAR POLYMERIC SUBSTANCESen
dc.subjectUMCCA MODELen
dc.subjectCOMPRESSIONen
dc.subjectSHEARen
dc.subjectEngineering, Chemicalen
dc.subjectWater Resourcesen
dc.titleErosion probability for biofilm modeling: analysis of trendsen
dc.typejournalArticleen


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