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Resistance to filtration

Comparing (5) and (8), it appears that an rph to meet the filtering requirements is 68.3/17.94 = 3.8 times that for washing and is the controlling speed. [Pg.313]

19) could be written in terms of a from Eq. (11.17) and would then have the same form as Eq. (11.2), but with only Rf as a parameter to be found from a single run at constant pressure. In Example 11.1, the mean resistivity is found from the simpler equation [Pg.313]

Analysis of the filtration of a compressible material is treated in Example 11.4. [Pg.313]

The four unknown parameters are ao, k, n, and Rf. The left-hand side should vary linearly with V/A. Data obtained with at least three different pressures are needed for evaluation of the parameters, but the solution is not direct because the first three parameters are involved nonlinearly in the coefficient of V/A. The analysis of constant rate data likewise is not simple. [Pg.337]

The mean resistivity at a particular pressure difference can be evaluated from a constant pressure run. From three such runs— APi, AP2, and AT3—three values of the mean resistivity—ai, d.2, and CI3—can be determined with Eq. (11.2) and used to find the three constants of the expression for an overall mean value, [Pg.337]


Minimum resistance to filtrate flow (i.e., high produc tion rate) Resistance to chemical attack... [Pg.1706]

Filter cake resistance (Rq) is the resistance to filtrate flow per unit area of filtration. R increases with increasing cake thickness during filtration. At any instant, Rc depends on the mass of solids deposited on the filter plate as a result of the passage of V (m ) filtrate. Rf may be assumed a constant. To determine the relationship between volume and residence time t. Equation 5 must be integrated, which means that Rc must be expressed in terms of V. [Pg.163]

Essentially equivalent information can be obtained during the formation of the filter cake, without the need for a second filtration. During filtration, particles are deposited as a layer of increasing thickness, so that the resistance to filtration increases. The resistance, R(m-1), is inversely related to permeability and is defined in terms of the volume flow rate ... [Pg.447]

An alternative method of reducing the resistance to filtration is to recirculate the slurry and thereby maintain a high velocity of flow parallel to the surface of the filter medium. Typical recirculation rates may be 10-20 times the filtration rate. By this means the cake is prevented from forming during the early stages of filtration. This can be particularly beneficial when the slurry is flocculated and exhibits shear-thinning non-Newtonian properties. This method of operation is discussed by Mackley and Sherman(21) and by Holdich, Cumming and Ismail(22). [Pg.386]

Biomass morphology also impacts on sludge treatability. Ng and Hermanowitz [41] showed that MBR sludge was more difficult to dewater than that from CAS operated under the same conditions. Values of the sludge resistance to filtration (SRF) in the MBR were, in fact, in order of magnimde higher than in the CAS (typically 1 x lO m kg ). [Pg.1016]

Ng HY and Hermanowicz SW. Specific resistance to filtration of biomass from membrane bioreactor reactor and activated sludge Effects of exocellular polymeric substances and dispersed microorganisms. Water Environ Res. 2005 77 187-192. [Pg.1022]

It is beyond the scope of this entry to review the basic principles governing filtration. However, it is interesting to note that filtration produces a more concentrated and dewatered cell sludge (20-35% w/v) or cell solids (>40% w/v) than settling. A variety of filter media, membranes, and equipment are commercially available. In the case where the deposited cake is compressible with low permeability and thereby adds more resistance to filtration, filter aids or precoats often alleviate the problem. Two of the most widely used filter aids are diatomaceous earth and perlite. [Pg.224]

Figure 9-15 Effect of crystal size on filtration rate for Example 9.3, Option 3. The data indicate that the smaller the particle, the higher the cake resistance to filtration. Figure 9-15 Effect of crystal size on filtration rate for Example 9.3, Option 3. The data indicate that the smaller the particle, the higher the cake resistance to filtration.
As discussed in the theory section of this chapter, the filter medium is an insignificant resistance to flow, in comparison to the cake. However, if the filter medium retains a high amount of fines, the subsequent cake that builds up becomes more resistant to filtration, thus the degree of clarity required in the filtrate can be a trade-off to capacity. [Pg.249]

Specific Resistance to Filtration. Specific resistance to filtration (SRF) is a standard method (34) for determination of the industrial amenability of a material to dewatering by filtration methods. Modifications of this method are useful empirical tools for evaluating interparticle interactions in concentrated suspensions. Figure 24 shows a schematic diagram of the apparatus in which the water released during filtration under standard conditions can be measured. Figure 25 shows data collected on oil sands mature fine tailings as a function of pH. As with the other methods, these data indicate that material is most difficult to handle at basic pHs. [Pg.88]

Figure 24. A schematic of the apparatus used to measure the specific resistance to filtration. This is a useful empirical method for comparing suspensions. With a defined pressure for filtration, coupled with the quantification of the filtrate produced as a function of time, suspension characteristics can he compared. Figure 24. A schematic of the apparatus used to measure the specific resistance to filtration. This is a useful empirical method for comparing suspensions. With a defined pressure for filtration, coupled with the quantification of the filtrate produced as a function of time, suspension characteristics can he compared.
Figure 25. The specific resistance to filtration of oil sands sludge as a function of pH. This behavior correlates to the behavior of G and ESA as a function of pH (Figure 23). The lowest resistance to filtration occurred at a pH where G and ESA indicated the most dispersed suspension. Figure 25. The specific resistance to filtration of oil sands sludge as a function of pH. This behavior correlates to the behavior of G and ESA as a function of pH (Figure 23). The lowest resistance to filtration occurred at a pH where G and ESA indicated the most dispersed suspension.
Figure 27. Low speed centrifugation of oil sands fine tailings as a function of pH. This correlates with the behavior observed in specific resistance to filtration, G and ESA in Figures 23 and 25. Figure 27. Low speed centrifugation of oil sands fine tailings as a function of pH. This correlates with the behavior observed in specific resistance to filtration, G and ESA in Figures 23 and 25.
Figure 29. Specific resistance to filtration ofMFT as a function of pH. The greatest resistance to filtration is also near pH 8.5, analogous to the behavior shown in Figures 27 and 28, illustrating the importance of water chemistry in determining MFT behavior. Figure 29. Specific resistance to filtration ofMFT as a function of pH. The greatest resistance to filtration is also near pH 8.5, analogous to the behavior shown in Figures 27 and 28, illustrating the importance of water chemistry in determining MFT behavior.

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See also in sourсe #XX -- [ Pg.277 , Pg.286 , Pg.288 , Pg.302 , Pg.389 ]




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