Flux decline along the flow channel in tubular ultrafiltration modules

Nordin, Anna-Karin; Jönsson, Ann‐Sofi

doi:10.1016/j.cherd.2009.04.002

Cited by 8 publications

(4 citation statements)

References 49 publications

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“…Finally, Figure 3c shows the effect of the flow (2.01, 5.31, and 7.38 L/min) on the J vs. ∆P T curves with the membrane with a 2 mm d h (temperature fixed at 60 • C and a concentration factor of 1.5). As expected, the increase in temperature and flow has a positive effect on the J L , but the concentration factor has a negative effect on this parameter [26,35]. Therefore, the J L can be modified by manipulating the hydrodynamic conditions, such as flow or CFV, and the system physico−chemical properties, i.e., concentration factor and temperature [13].…”

Section: Flux Versus ∆P T Curves: Effect Of the Processing Conditionssupporting

confidence: 52%

Prediction of the Limiting Flux and Its Correlation with the Reynolds Number during the Microfiltration of Skim Milk Using an Improved Model

Astudillo‐Castro

Córdova

Oyanedel-Craver

et al. 2020

Foods

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Limiting flux (JL) determination is a critical issue for membrane processing. This work presents a modified exponential model for JL calculation, based on a previously published version. Our research focused on skim milk microfiltrations. The processing variables studied were the crossflow velocity (CFV), membrane hydraulic diameter (dh), temperature, and concentration factor, totaling 62 experimental runs. Results showed that, by adding a new parameter called minimum transmembrane pressure, the modified model not only improved the fit of the experimental data compared to the former version (R2 > 97.00%), but also revealed the existence of a minimum transmembrane pressure required to obtain flux (J). This result is observed as a small shift to the right on J versus transmembrane pressure curves, and this shift increases with the flow velocity. This fact was reported in other investigations, but so far has gone uninvestigated. The JL predicted values were correlated with the Reynolds number (Re) for each dh tested. Results showed that for a same Re; JL increased as dh decreased; in a wide range of Re within the turbulent regime. Finally, from dimensionless correlations; a unique expression JL = f (Re, dh) was obtained; predicting satisfactorily JL (R2 = 84.11%) for the whole set of experiments

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Section: Flux Versus ∆P T Curves: Effect Of the Processing Conditionssupporting

confidence: 52%

Prediction of the Limiting Flux and Its Correlation with the Reynolds Number during the Microfiltration of Skim Milk Using an Improved Model

Astudillo‐Castro

Córdova

Oyanedel-Craver

et al. 2020

Foods

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show abstract

“…As expected, when the cross-flow velocity was increased, an increase in the limiting flux was observed. 14,47 Another effect of this parameter on the curves can be observed: when the crossflow velocity is increased, the limiting transmembrane pressure increased significantly from 0.08 bar for 1.13 m/s to 1.05 bar for 4.29 m/s. That means that when a low cross-flow velocity is used for skim milk microfiltration, a low transmembrane pressure is needed to achieve a balance between the convection and erosion within the membrane−solution interface.…”

Section: Industrial and Engineering Chemistry Researchmentioning

confidence: 99%

Limiting Flux and Critical Transmembrane Pressure Determination Using an Exponential Model: The Effect of Concentration Factor, Temperature, and Cross-Flow Velocity during Casein Micelle Concentration by Microfiltration

Astudillo‐Castro

2014

Ind. Eng. Chem. Res.

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During microfiltration, limiting (J L ) and critical flux (J C ) are essential. Using these concepts, the operational zones, have been established for flux (J) versus transmembrane pressure (ΔP T ). However, the resistance model cannot be used for an accurate description of these operational zones. The aim of this work was to evaluate the application of an equation for process parameters' determination during skim milk microfiltration. The exponential model, J = J L (1 − exp(−ΔP T /(ΔP T ) C ), allowed a direct determination of J L and the critical ΔP T ((ΔP T ) C ) and allowed the calculation of J C and the limiting ΔP T ((ΔP T ) L ). The effect of temperature, concentration factor, and cross-flow velocity over J L and (ΔP T ) C were evaluated. For J L and (ΔP T ) C , a good fitting was obtained (R adj 2 = 98.12%; R adj 2 = 97.83%, respectively). These results allow to predict the limiting and critical points for given values of the concentration factor, cross-flow velocity and temperature. Moreover, determination of the operational zones could be established.

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“…The main reason is that turbulent flow may consume the TMP of the system, causing a decline in the permeate flux. A recent study 60 showed that an optimal CFV depends on the frictional pressure drop, which is the function of solution viscosity and module configuration. In a normal flow channel a high tangential flow increases turbulence close to the membrane surface, which mitigates the formation of concentration−polarization.…”

Section: ■ Effects Of Process Parametersmentioning

confidence: 99%

Recent Developments in Membrane Treatment of Spent Cutting-Oils: A Review

Milić

Muric

Petrinić

et al. 2013

Ind. Eng. Chem. Res.

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Throughout the metal-working industry, cutting-oil emulsions are used as lubricants and coolants. However, they have to be discarded after a certain time due to losing their functional properties. Hence, they need to be treated in order to separate any oil before disposal. Conventional methods have their advantages, but none are effective enough. Therefore, membrane technology appears to be a promising alternative. The aim of this work was to study the membrane treatment of spent metal-working fluids. The main drawback of membranes is flux decline due to fouling and concentration–polarization. The complexes of cutting-oils containing membrane filtration systems demand complementary studies on issues relating to fouling control and its reduction and membrane cleaning after fouling. Important conclusions were therefore formed about achievements in the field of fouling control and membrane cleaning.

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Flux decline along the flow channel in tubular ultrafiltration modules

Cited by 8 publications

References 49 publications

Prediction of the Limiting Flux and Its Correlation with the Reynolds Number during the Microfiltration of Skim Milk Using an Improved Model

Prediction of the Limiting Flux and Its Correlation with the Reynolds Number during the Microfiltration of Skim Milk Using an Improved Model

Limiting Flux and Critical Transmembrane Pressure Determination Using an Exponential Model: The Effect of Concentration Factor, Temperature, and Cross-Flow Velocity during Casein Micelle Concentration by Microfiltration

Recent Developments in Membrane Treatment of Spent Cutting-Oils: A Review

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