A novel hybrid ant colony optimization and particle swarm optimization algorithm for inverse problems of coupled radiative and conductive heat transfer

摘要

In this study, a continuous ant colony optimization algorithm on the basis of probability density function was applied to the inverse problems of one-dimensional coupled radiative and conductive heat transfer. To overcome the slow convergence of the ant colony optimization algorithm for continuous domain problems, a novel hybrid ant colony optimization and particle swarm optimization algorithm was proposed. To illustrate the performances of these algorithms, the thermal conductivity, absorption coefficient and scattering coefficient of the one-dimensional homogeneous semi-transparent medium were retrieved for several test cases. The temperature and radiative heat flux simulated by the finite volume method were served as inputs for the inverse analysis. Through function estimation and parameter estimation, the HAPO algorithm was proved to be effective and robust.