Operating and Design Parameters

The chromatographic process contains many design and operating parameters. Hence, the optimization of all parameters requires a great amount of resources 

Dimensionless formulation of model equations for a chromatographic column can be found in Chapter 6. For clarity, the dimensionless parameters and the phenomena described by them will also be mentioned here  

2) Mass transfer and convection modified Stanton number 

3) Adsorption for linear chromatography, adsorption behavior is determined by the dimensionless Henry coefficient H  

In most cases (nonlinear chromatography), however, the feed concentration plays a major role in the adsorption. 

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The equilibrium stage calculations discussed earlier can easily be applied to distillation in order to find the required operating and design parameters. Consider the following problem specification. 

An important part of this chapter will be devoted to robustness. The design will ensure that feasibility is preserved when operation and design parameters change or are uncertain. Thus, we will take into account the fact that alkylation plants are often built as onstream units, being required to deal with large changes of the butene feed stream. In addition, we will be aware of large errors of the kinetic data. 

Using the materials of construction and mechanical design procedures which are typical of the late 1970 s, a conventional high temperature steam reformer would have operating and design parameters approximately as given in Table 2 for a 10 million scf/day hydrogen plant. 

No formal optimization of the parameters was attempted. Instead, individual feed, operating, and design parameters were perturbed around a standard set to assess their influence on the computed performance parameters. 

A review of the cost contributions in chromatography is presented in this section [73. These results emphasize the importance of optimizing the operating and design parameters in chromatography to minimize cost as well as the importance of solvent... 

Fig. 7.3. Hffect of operating and design parameters on the column ID. (a) Linear velocity (A) and optimum r/p/L ( ) and plate count (c) versus column ID. (b) Loading (mg prtxluct/g packing) (A) and yield ( ) versus column ID. (c) Column length (A) and cycle time ( ) versus column ID. (d) Total cost ( /g) ( ) and production rate ( ) versus column ID.

Verify operating and design parameters needed for start of detailed design. 

Objective functions - such as yield, productivity or total cost - provide an evaluation of efficiency and quality of preparative chromatographic separations. Since values of the objective functions can be changed by altering operating and design parameters, they are dependent variables for any optimization problem. The definitions of each objective function are identical for every chromatographic process (e.g. batch or SMB) but different parameters must be applied for its calculation. 

An analogous procedure can also be applied to SMB processes (Tab. 7.5). The following compares the axial concentration profile of several 8-column SMB processes with different operating and design parameters but identical number of stages and dimensionless flow rate in each SMB section (m,) (Tab. 7.6). For this purpose we use... 

Table 7.6 Different operating and design parameters for SMB plant.

Dimensionless Representation of Operating and Design Parameters 318 7.1.3 Scaling Up and Down 322... 

In the last part of this book, we apply the different models discussed earlier, particularly the ideal model and the equilibrium-dispersive model, to the investigation of the properties of simulated moving bed chromatography (Chapter 17) and we discuss the optimization of the batch processes used in preparative chromatography (Chapter 18). Of central importance is the optimization of the column operating and design parameters for maximum production rate, minimum solvent use, or minimum production cost. Also critical is the comparison between the performance of the different modes of chromatography. 

Because the liquid phase process is predominantly used for new EB plants, the critical operating and design parameters for liquid phase benzene alkylation are discussed below. 

Using the supposedly efficient numerical algorithm, the model equations with the operating and design parameters of the industrial unit are solved and the output is compared with the output of the industrial unit. It is not unusual even with the utmost care in model formulation, choice of the physico-chemical parameters and the use of an accurate solution algorithm, that the predictions of the model differ from the industrial data. Blind empirical fitting using one or more adjustable parameters will make the model lose almost all its... 

Table 7 Operational and design parameters used in the experimental design and their levels.

They depend on the operating and design parameters of a plant. Hereby, they are potential variables for any optimization problem and the basis for the formulation of objective functions. The definitions of objective functions are often identical for diverse chromatographic processes (e.g., batch or SMB), but different operating and design parameters must be applied for their calculation. 

Temperature explicit functions for inactivation parameters considering substrate and product modulation and a two-stage series mechanism were also determined and validated as already presented in Table 5.2. Temperature optimization of CPBR was then accomplished by replacing these temperature-explicit functions in Eqs. 5.76 and 5.79. A battery of staggered reactors was considered to absorb output flow fluctuations due to enzyme inactivation (see Eqs. 5.82 and 5.83). Elow-rate was considered constant during each time interval (see Eq. 5.84) so that variation in substrate conversion was below 1%. Conditions of operation and design parameters used in the simulation of an industrial CPBR for the hydrolysis of whey permeate with immobilized p-galactosidase are summarized in Table 5.4. 

P. Boutikosa, V. Nikolakisb, A simulation study of the effect of operating and design parameters on the performance of a water gas shift membrane reactor, J. Membr. Sci. 350 (2010) 378-386. 

Ironically, the drawbacks of the CFD approach stem from its great versatility it is difficult to resist temptation to take into account all imaginable processes, and CFD model usually includes several tens of kinetic, transport, operational and design parameters. In real systems, however, many of these parameters are poorly known. In this situation, the numerical model gives a qualitative rather than an exact picture. While they are valuable tools for understanding 3D effects, CFD models still fail to predict performance and local characteristics of cells in a wide range of operating conditions. 

Currently used mathematical models of gas purification formed on simplified theoretical concepts of gas flow. They are not sufficiently taken into account the operational and design parameters of gas cleaning devices, as well as aero-hydrodynamic properties of gas-dispersed flows. These models cannot be used to search for the best options of integrated gas cleaning systems, as they show the properties of objects in a narrow range of parameters. We need more complete and appropriate mathematical models based on the study of the aerodynamics of gas and taking place in these events. 

Using previously obtained correlations between the dust collection efficiency and pressure drop with regime - the design parameters of design procedure. The technique allows to select the unit with operational and design parameters under which it would provide the required process parameters at a minimum cost of cleaning. 

In the frame of the experimental investigations a broad range of different operating and design parameters were taken into account, e.g. steady state and transient, core power, asymmetric DHR by DHX, type of DHX, reduced fluid level, operation of air dampers and environmental Influences. 

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