Simulation research on simultaneous reconstruction of temperature and soot volume fraction distributions in axisymmetric hydrocarbon flames by a GN-HGA coupled method

In inverse radiation analysis, flame temperature and soot volume fraction distributions are critical state parameters that characterize the combustion process. They effectively reflect the operational status of the combustion system and provide a basis for optimizing the control strategy to improve combustion efficiency and reduce harmful emissions. To reconstruct the temperature and soot volume fraction distributions, this study proposes a coupled method (GN-HGA) that integrates the Gauss-Newton (GN) method and the hybrid genetic algorithm (HGA). The simultaneous reconstruction of these parameters in an axisymmetric hydrocarbon flame is simulated, and the results are compared with those from the GN method and the GN-HGA coupled method. Simulation results demonstrate that, under a 5 % measurement error, the GN-HGA coupled method achieves an average relative error below 1 % for both parameters. Compared to the GN method, the GN-HGA coupled method provides higher reconstruction accuracy. This study highlights the advantages of combining local and global optimization strategies for inverse radiation problems and provides a promising framework for advanced combustion diagnostics and industrial applications requiring precise monitoring of flame characteristics.