Characterisation of Cake Compressibility in Dead-End Microfiltration of Microbial Suspensions

McCarthy, A.A.; Gilboy, P.; Walsh, Padraig K.; Foley, Greg

doi:10.1080/00986449908912777

Cited by 24 publications

(21 citation statements)

References 11 publications

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“…2 shows plots of specific cake resistance, measured by the steady-state method, as a function of pressure, at various pHs. The magnitudes of the specific resistance values are in agreement with other workers [32] and [33], but higher than those of Nakanishi et al [3] and McCarthy et al [28]. This is probably due to variations in the types of dried yeast employed in each study as well as differences in the various cell washing regimens used.…”

Section: Filtration Behavioursupporting

confidence: 90%

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Dead-end filtration of yeast suspensions: Correlating specific resistance and flux data using artificial neural networks

Mhurchú

Foley

2006

Journal of Membrane Science

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The specific cake resistance in dead-end filtration is a complex function of suspension properties and operating conditions. In this study, the specific resistance of resuspended dried bakers yeast suspensions was measured in a series of 150 experiments covering a range of pressures, cell concentrations, pHs, ionic strengths and membrane resistances. The specific resistance was found to increase linearly with pressure and exhibited a complex dependence on pH and ionic strength. The specific resistance data were correlated using an artificial neural network containing a single hidden layer with nine neurons employing the sigmoidal activation function. The network was trained with 104 training points, 13 validation points and 33 test points. Excellent agreement was obtained between the neural network and the test data with average errors of less than 10%. In addition, a network was trained for prediction of the filtrate flux directly from the system inputs and this approach is easily extended to crossflow filtration by adding inputs such as the crossflow velocity and channel height. An attempt was made to interpret the network weights for both the specific resistance and flux networks. The effective contribution of each input to the system output was computed in each case and showed trends that were as expected. Although network weights, and consequently the computed effect of each parameter, is different each time a network is changed (depending on the initial weights used in the training process), the variation was low enough for information contained in the network to be interpreted in a meaningful way.Keywords: Dead-end filtration; Specific cake resistance; Artificial neural network; Bakers yeast

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Section: Filtration Behavioursupporting

confidence: 90%

“…(1). It should be noted that it is generally found that the specific resistance of a microbial cake at a given pressure is independent of whether or not the cake has been exposed previously to different pressures [28] and hence the approach of incrementing the pressures in the way described above is valid.…”

Section: Filtration Methodsmentioning

confidence: 99%

Dead-end filtration of yeast suspensions: Correlating specific resistance and flux data using artificial neural networks

Mhurchú

Foley

2006

Journal of Membrane Science

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“…(8), which is similar to previous results using other microorganisms such as yeast, Escherichia coli, Bacillus circulans, etc. [13,[25][26][27]37]. Additionally, the values of B. diminuta and S. marcescens cake specific resistances are in the same range as previously reported for other bacteria, e.g., [20,37,38].…”

Section: Constant Pressure Measurements Of Cake Propertiessupporting

confidence: 83%

“…Increasing stresses associated with higher pressures necessary to maintain a constant flux increases specific resistances in addition to the total resistance to water flow. For microbial suspensions, the specific resistance often increases in a straight line fashion with pressure [25][26][27];…”

Section: Theoreticalmentioning

confidence: 99%

Blocking laws analysis of dead-end constant flux microfiltration of compressible cakes

Chellam

2006

Journal of Colloid and Interface Science

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“…Consequently, at applied pressures below one atmosphere, increasing pressure neither increased the flow rate nor decreased the average cake porosity. McCarthy et al 28 found that for microbial suspensions, the specific cake resistance was a linear function of pressure. Cake compression was found to be reversible or weakly irreversible with respect to changes in pressure, ie the specific resistance measured at a given pressure was only weakly dependent on whether the filter cake had previously been exposed to higher pressures.…”

Section: Filtrationmentioning

confidence: 99%

Filtration of zinc ions utilising pretreated Streptomyces rimosus biomass

Addour¹,

Bakhti²,

Belhocine³

et al. 2003

J of Chemical Tech & Biotech

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The performance of biofiltration of zinc utilising pretreated Streptomyces rimosus was studied. Streptomyces rimosus biomass is able to bind zinc ions in batch mode. The biomass granules may be regenerated easily by using a biomass pretreatment which confers rigidity to biosolids, without decreasing the zinc uptake capacity, thus allowing collection of the biomass by filtration. Accordingly, biomass was pretreated with an anionic enzymatic tension active product (Extran AP41) and regeneration with a cleaning product (HCl) was successfully realised. It was shown that the optimum concentration of biomass and pressure range are found to be between 50 and 120 g dm −3 and 0.5 and 1 × 10 5 Pa, respectively. Complete regeneration was reached after three cycles under optimal experimental conditions when the biosorbent was saturated with synthetic ZnCl 2 solution. The filterability of biosolids was demonstrated. A combination of a batch reactor and a filtration process made it possible to increase the performance of the complete treatment process. The biosorption capacity of the biomass to bind Zn ions was slightly increased (from X = 14 mg g −1 in batch mode to X = 16.1 mg g −1 in a process combining batch reactor and pressure filtration) and the experimental contact time was considerably reduced. Integration of the filtration process produced a dewatering cake which considerably facilitated the regeneration operation.

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Characterisation of Cake Compressibility in Dead-End Microfiltration of Microbial Suspensions

Cited by 24 publications

References 11 publications

Dead-end filtration of yeast suspensions: Correlating specific resistance and flux data using artificial neural networks

Dead-end filtration of yeast suspensions: Correlating specific resistance and flux data using artificial neural networks

Blocking laws analysis of dead-end constant flux microfiltration of compressible cakes

Filtration of zinc ions utilising pretreated Streptomyces rimosus biomass

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