Direct simultaneous reconstruction for temperature and concentration profiles of soot and metal-oxide nanoparticles in nanofluid fuel flames by a CCD camera

A reconstruction model based on inverse radiation analysis is presented to determine the temperature and concentration distributions of soot and metal-oxide nanoparticles in nanofluid fuel sooting flames using radiative intensities received by a CCD camera. The combined method consisting of the least-square QR decomposition (LSQR) algorithm and one dimensional searching was adopted to solve the inverse problem. Influences of ray number, wavelength combination, measurement error and metal-oxide nanoparticle concentration on the reconstruction accuracy were studied in details. The reconstructed results illustrated that the temperature distribution and soot concentration fields can be accurately retrieved, even with the measurement signal to noise ratio (SNR) as low as 39 dB, whereas the metal-oxide nanoparticle concentration field estimation process was more easily influenced by the measurement error and the practical metal-oxide nanoparticle concentrations. The proposed reconstruction method here is effective and robust for simultaneously retrieving the temperature distribution and concentration fields of soot and metal-oxide nanoparticles, even with noisy data.