Characterising complex reaction mechanisms using machine learning clustering techniques
|Title||Characterising complex reaction mechanisms using machine learning clustering techniques|
An example is given of the use of machine learning clustering to detect phases within a continuous process. Specifically, the example involves data from the numerical modeling (from the numeric integrator of Fabian Maus, Combustion Physics Dept. Technical University Lund) of counterflow combustion flames (two jets of gases pointed at each other, one with a hydrocarbon fuel and the other with oxygen). The example not only shows the use of clustering, but the multiple pre- and post- processing steps needed to derive the final result. The example shows how all these varied manipulations are automatically handeled within the ANALYSIS++/REACTION framework.