A novel hybrid ant colony optimization and particle swarm optimization algorithm for inverse problems of coupled radiative and conductive 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 one-dimensional coupled radiative and conductive heat transfer. To overcome the slow convergence of the ant colony optimization algorithm for con...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
VINCA Institute of Nuclear Sciences
2016-01-01
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| Series: | Thermal Science |
| Subjects: | |
| Online Access: | http://www.doiserbia.nb.rs/img/doi/0354-9836/2016/0354-98361400023Z.pdf |
| Summary: | 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. |
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| ISSN: | 0354-9836 2334-7163 |