Decision tree and first-principles model-based approach for reactor runaway analysis and forecasting

Decision trees (DTs) are effective in extracting linguistically interpretable models from data. This paper shows that DTs can also be used to extract information from process models, e.g. they can be used to represent homogenous operating regions of complex process. To illustrate the usefulness of this novel approach a detailed case study is shown where DTs are used for forecasting the development of runaway in an industrial, fixed bed, tube reactor. Based on first-principles knowledge and historical process data the steady-state simulator of the tube reactor has been identified and validated. The runaway criterion based on Ljapunov's indirect stability analysis has been applied to generate a data base used for DT induction. Finally, the logical rules extracted from the DTs are used in an operator support system (OSS), since they are proven to be useful to describe the safe operating regions. A simulation study based on the dynamical model of the process is also presented. The results confirm that by the synergistic combination of a DT based on expert system and the dynamic simulator a powerful tool for runaway forecasting and analysis is achieved and it can be used to work safe operating strategies out.