OPTIMAL CAKE THICKNESS

As the cake thickness of a product varies, filtration rates and capacity will also change. Equation 4 shows that rates increase as the cake (W/A)mass decreases thus, thin cakes yield higher filtration rates. This is particularly the case with amorphous materials or materials with high specific cake resistance. As a increases, maximizing dV/dO requires W/A to decrease. 

In continuous operations this can be done easily. In batch operations however, often filtration equipment cannot efficiently operate with extremely thin cakes. The long discharge times required to remove residual product in preparation for the next cycle, etc., make operation at a product s optimal 

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Figure 8. Optimal cake thickness curve. (Courtesy of Heinkel Filtering Systems, Inc.)...

Of course, if equipment is presently in operation at the plant on the particular product, invaluable data can be obtained. Optimization of the filter should be done, perhaps with the vendor s help, to be sure that over-sizing of the next piece of equipment does not occur. Variance of precoat, cake thickness, wash, etc., if not already done on the process, will enable fine-tuning of the process as well as confirm the data for the next system s design. 

It is recommended that optimization be carried out by developing three different cake thicknesses. From this, a capacity versus cake thickness curve can be developed. Additional parameters that have to be evaluated are vacuum level, wash requirements, slurry concentration, and slurry temperature. If cake cracking occurs, the wash should be introduced earlier to avoid channeling. 

Optimal filter cake thickness in a batch filter, for which the rate of filtration is balanced against the cost of removing the cake. 

These results iadicate that as the fiherahility of the material reduces, so does the optimum cycle time. Practical e q>eiieiice [Bosley, 1986] suggests that difficuh-to-fiher materials, e.g. alum sludge or hi protdn containing materials require thin cake filtration conditions, with cake thicknesses 1.5-2.0 cm Read% filtered materials are generally produced optimally as thicker cakes, iq) to 7.0 cm in thickness. This e qieiience points to the usefiihiess of the models discussed here, in process calculations and plant q>edfications. 

The amount of body feed is subject to optimization which has to be based on experiments but can be modelled mathematicallyThe criterion for the optimization depends on the purpose of the filtration. Maximum yield of filtrate per unit mass of filter aid, as depicted in Figure 1.2, is probably the most common but least cake resistance" longest cycle, fastest flow, or maximum utilization of cake space are other criteria which each require a different rate of body feed addition. The tests to be carried out for such optimization normally use laboratory or pilot scale filters and have to include variation of the filtration parameters such as pressure or cake thickness in the optimization. 

Nowadays, ultrafiltration (UF) or microfiltration (MF) membrane processes are widely used because of their ability to remove particles, colloidal species and microorganisms from different liquids feeds. However a limitation inherent in the process is membrane fouling due to the deposition of suspended matter during filtration. Therefore the understanding of formation and transport properties of particle deposits responsible for membrane fouling is a necessary step to optimize membrane processes. Thus it is necessary to obtain local information in order to analyze and model the basic mechanisms involved in deposit formation and then to further predict the process operation. Besides, it is also useful to control the deposit formation and to plan preventive or curative actions with a controlled efficiency. Nonetheless, local parameters such as cake thickness and porosity are hardly reachable with conventional techniques. 

Several leaf tests should be performed for repeatability. Data collected will permit scaleup to plant scale operations. Significant data will be pounds of dry cake per square foot per hour, gallons of filtrate per square foot per hour, filtrate clarity, wash ratios, (pounds of solids/gallon of wash), residual moistures, filtermedia selection, knife advance time, precoat thickness, solids penetration into precoat, and submergence level should also be evaluated. For the optimization equation, refer to Peters and Timmerhaus, and Tiller and Crump. 

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