Sampled images in combustion experiments carry much information, both on flame morphology and, when collected in sequences, on flame statistics. Non-intrusive methods extract experimental basis function sets, and the statistical study of coefficients obtained by projection of the data set onto the basis allows various kinds of analysis. This work outlines possible applications, via proper data treatment and real-time processing, in order to identify critical conditions and to design control strategies to avoid them.

This presentation is part of Minisymposium “MS53 - Dimensionality Reduction Algorithms for Large-Scale Images (2 parts)”
organized by: Salvatore Cuomo (Dept. Mathematics and Applications "Renato Caccioppoli", University of Naples) , Costantinos Siettos (National Technical University of Athens ) , Lucia Russo (Consiglio Nazionale delle Ricerche, Istituto di Ricerche sulla Combustione) .

Authors:

Gaetano Continillo (University of Sannio, Benevento)

Keywords:

image representation, partial differential equation models, proper orthogonal decomposition