A NOVEL HYBRID ANT COLONY OPTIMIZATION AND PARTICLE SWARM OPTIMIZATION ALGORITHM FOR INVERSE PROBLEMS OF COUPLED RADIATIVE AND CONDUCTIVE HEAT TRANSFER

作者：Zhang, Biao; Qi, Hong^*; Sun, Shuang-Cheng; Ruan, Li-Ming^*; Tan, He-Ping

来源：Thermal Science, 2016, 20(2): 461-472.

DOI：10.2298/TSCI131124023Z

• inverse problem
• ant colony optimization
• particle swarm optimization
• coupled heat transfer

In this study, a continuous ant colony optimization algorithm on the basis of probability density function was applied to the inverse problems of 1-D 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 1-D 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 hybrid colony and particle swarm optimization algorithm was proved to be effective and robust.

• 出版日期2016
• 单位哈尔滨工业大学