Abstract
A novel reconstruction model based on inverse radiation analysis was presented for simultaneous estimation of temperature and concentration fields of soot and multiple metal-oxide nanoparticles in nanofluid fuel flame from the knowledge of the flame emission radiation intensity obtained by a CCD camera. The self-absorption effect was considered in the reconstruction model and least-square QR decomposition (LSQR) algorithm combined with iterative method was introduced to solve the inverse radiation problem. The inverse reconstruction model was successfully applied in the flames containing two and three kinds of metal-oxide nanoparticles from simulation values as examples and can be extended to more kinds of metal-oxide nanoparticles containing system. The measured data were also simulated by adding random noise into the exact solution of the direct problem. The numerical results showed that all the unknown parameters fields can be estimated accurately, even with the noisy data.
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