Separator design parameters

The choice of the most suitable membrane module type for a particular membrane separation must balance several factors. The principal module design parameters that enter into the decision are summarised in Table 16.3. 

Some examples of calculated pressure gradients are shown in Figure 5.12 in which solids concentration is a parameter. Experimental points are given, with separate designations for each concentration band. The difference between experimental and predicted value does not generally exceed about 15 per cent. 

Vertical-Tube Coalescer This is the equipment finally selected to meet the design parameters listed in Table 2. The vertical-tube coalescer (VTC) unit equals the performance of a skimmer in less space or offers improved performance in the same space. The VTC tube packs provide up to five times more coalescing surface than a plate pack. The extra surface gives oil globules more area for coalescence Also, the vertical orientation of the tubes contributes to a more efficient separation. In a plate pack, the rising oil droplets must move perpendicular to the flow of influent. In a VTC pack, the oil droplets arc free to travel upward and to collect on the top surface of the tube bundles. 

Off-gas emissions from the modified baseline process MPF will pass through a separately fired afterburner maintained at a temperature of 2,000°F. The committee was told that the afterburner design is patterned after the successful afterburner operations at JACADS and TOCDF (Webster, 2000). The key design parameter for the afterburner is to have a one-second residence time at 2,000°F (CR E, 2000). Off-gas emissions then pass through the PAS, which includes high-efficiency particulate air (HEPA) and carbon filtration. Metal parts emerging from the MPF will be disposed of as scrap metal. 

In this table, we provide solubility parameters for some liquid solvents that can be used as modifiers in supercritical fluid extraction and chromatography. The solubility parameters (in MPa1/2) were obtained from reference 3, and those in cal1/2cm 3/2 were obtained by application of Equation 4.1 for consistency. It should be noted that other tabulations exist in which these values are slightly different, since they were calculated from different measured data or models. Therefore, the reader is cautioned that these numbers are for trend analysis and separation design only. For other applications of cohesive parameter calculations, it may be more advisable to consult a specific compilation. This table should be used along with the table on modifier decomposition, since many of these liquids show chemical instability, especially in contact with active surfaces. 

Various adsorbents have been examined for their potential to increase in situ product separation in plant cell culture. Suspended solid adsorbents were popular, and the use of immobilized adsorbent has been investigated recently [17-20]. The advantages of immobilized adsorbent are that it is easy to use in a bioreactor operation and that it allows adsorbents to be easily separated from culture broth for the repeated use of cells and adsorbents [21, 22]. The design and optimization of in situ separation process for phytochemicals using immobilized adsorbent required a detailed mathematical model. It was difficult to achieve an optimal design based on purely empirical correlations, because the effects of various design parameters and process variables were coupled. 

The proposed mathematical model for encapsulated adsorbents can describe various diffusion characteristics in addition to the intrinsic binding characteristics of the encapsulated adsorbents. The performance of encapsulated adsorbent in an in situ product separation process can be evaluated using the proposed model for the adsorption rate of a target product, berberine. The performance of the encapsulated adsorbents is influenced by design parameters such as the adsorbent content in the capsule (Ns), the capsule size ( R ), the number of capsules (n), the membrane thickness ( Rm), and the ratio of the single capsule volume to the total capsule volume (Nc). 

Having design parameters fixed in the outer problem and with a specific choice of D° (discussed in section 7.2) the inner loop optimisation can be partitioned into M independent sequences (one for each mixture) of NTm dynamic optimisation problems. This will result to a total of ND = 2 NTm problems. In each (one for each task) problem the control vector m for each task is optimised. This can be clearly explained with reference to Figure 7.3 which shows separation of M (=2) mixtures (mixture 1 = ternary and mixture 2 = binary) and number of tasks involved in each separation duty (3 tasks for mixture 1 and 2 tasks for mixture 2). Therefore, there are 5 (= ND) independent inner loop optimal control problems. In each task a parameterisation of the time varying control vector into a number of control intervals (typically 1-4) is used, so that a finite number of parameters is obtained to represent the control functions. Mujtaba and Macchietto (1996) used a piecewise constant approximation to the reflux ratio profile, yielding two optimisation parameters (a control level and interval length) for each control interval. For any task i in operation m the inner loop optimisation problem (problem Pl-i) can be stated as ... 

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