The Motivation for Modeling

Extruder modeling can also be used to observe, control, and regulate processes online . The observer is an integral component of the model in this case. The observer calculates measurable or difficult-to-measure process values during an ongoing process. The observer can pre-calculate one or more values which can be measured in order to identify any discrepancies between reference and measured processes values, i. e., a shortcoming in the model. The corrector is another integral part of the model. It can use the observed discrepancies between the model and the measured data to improve the observer model or adjust model characteristics. 

While the observer model operates alongside the process, effectively tracking its progress, modeling can also be used for prediction purposes. A model component called the predictor can calculate the required control values for a process in order to achieve a desired operating status. This is, of course, subject to the bounds of what is physically possible. Naturally, this kind of modeling is subject to limitations because in many processes it is not possible to take all the influences into account in computational form. 

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The motives for modeling of performance at the single agglomerate level are, thus, multifold. There are few open reports on the effect of composition inside agglomerates on mass transport, electrochemical reactions, and catalyst utilization. It is poorly understood whether pores inside agglomerates should be hydrophobic or hydrophilic. Agglomerates are of vital importance in determining the true active area and the effectiveness of catalyst utilization. 

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