Fouling determine pressure drop

Table I shows the flexibility of the computational system. Six types of frequently encountered problems are classified according to their respective boundary conditions. In each classification, one or more run options can be selected. For example, Class 1 are typical simulation problems where the reactor outlet pressure and feed conversion are specified and the inlet pressure and radiant temperature are calculated. Alternatively, the effect of fouling can be determined by calculating a coking factor from a known pressure drop. The following examples illustrate applications of the system in problems under Classes 1, 5 and 6 respectively.

And so forth. When running a projection for an existing system, the projected and actual pressure drop data should be contrasted and used to determine whether fouling or scaling may be occurring. 

As an alternative to direct heat transfer measurements it is possible to use changes in pressure drop brought about by the presence of the deposit. The pressure drop is increased for a given flow rate by virtue of the reduced flow area in the fouled condition and the rough character of the deposit. The shape of the curve relating pressure drop with time will in general, follow an asymptotic shape so that the time to reach the asymptotic fouling resistance may be determined. The method is often combined with the direct measurement of thickness of the deposit layer. 

Equation 8.16 is a simplified equation which is based upon equipment with a certain amount of fouling present on the shell side. Consequently, it may predict values of pressure drop higher than actually present for certain applications. A more rigorous method for calculating pressure drop across banks of tubes is presented here. The pressure drop for fluids flowing across the tube banks may be determined by calculating the following components ... 

Membrane fouling and the subsequent permeate flux decline is one of the major drawbacks. A number of theories about concentration polarization, cake formation and flux decline have been developed to predict membrane fouling. Generally those models are based on an assumed behavior and validated by experimental determinations. Nevertheless, typical experimental measurements are focused on macroscopic parameters, such as permeate flux, pressure drop and solute rejection, which provide little information about microscopic phenomena and, thus, are not able to validate mechanistic models. 

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