Control of combustion systems is of considerable importance to the improvement of system performance and is currently an active field of research. An understanding of combustion system dynamics is crucial to the development of effective control systems. Combustion dynamics and control combine the different aspects of combustion research such as theoretical analysis of the governing equations and phenomena, computational simulation, modeling, and measurement using advanced sensors.
Investigation of the use of proper orthogonal decomposition to analyze combustion product fields and their associated dynamics is presented. Proper orthogonal decomposition is applied to CO2 number density and vorticity magnitude data from reacting rectangular jet simulations. The resulting eigenfunctions are used to develop physical insight of the vortex formations and dynamics of these jets and their related mixing and spreading characteristics. It is seen that different vortex structures are captured in the eigenfunctions and that CO2 and vorticity eigenfunctions are very similar indicating that vortex-driven mixing dominates in these jets. Using subsets of eigenfunctions with high information content, CO2 and vorticity magnitude distributions can be represented with relatively few eigenfunctions.
Results of research to develop and apply multiple line-of-sight absorption and emission tomography for the study of combustion and as a sensor for monitoring and control of combustion systems are reported. Absorption tomography can provide data on the state of macro-mixing in combustion systems that can influence system performance, e.g. efficiency, radiation signature, and pollutant emissions. The development of an IR laser absorption facility for rapid scanning tomography and the performance of the tomographic reconstruction technique, Adaptive Finite Domain Direct Inversion, are discussed. The development of a sensor system for use in a practical combustion device is also addressed. Computational simulation of a combustor sector rig provided operating state conditions such as excited state population and temperature distributions. Emission tomography measurements were simulated using numerical line-of-sight integration of simulated excited state number densities of water for two emission transitions. Tomographic reconstruction was performed using Tomographic Reconstruction via a Karhunen-Loeve Basis to evaluate nine line-of sight measurement configurations and an optimal measurement configuration was selected. Operating state identification for control applications was investigated using the TRKB reconstructions.