期刊
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
卷 113, 期 -, 页码 116-129出版社
ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
DOI: 10.1016/j.ijthermalsci.2016.11.018
关键词
Simultaneous estimation of multi parameter; Stochastic particle swarm optimization; Chebyshev collocation spectral method; Coupled optical and thermal information; Graded-index media
资金
- National Natural Science Foundation of China [51476043]
- Major National Scientific Instruments and Equipment Development Special Foundation of China [51327803]
- Foundation for Innovative Research Groups of the National Natural Science Foundation of China [51421063]
An inverse conduction-radiation analysis is presented for estimating multi-parameter in semitransparent graded-index media from measured coupled optical and thermal information. The boundary radiative signals (optical information) and temperature distribution within the media (thermal information) are served as measurement data. The direct coupled conduction-radiation heat transfer problems are solved by the Chebyshev collocation spectral method. The stochastic particle swarm optimization (SPSO) was employed to estimate the multi-parameter including graded refractive index, absorption coefficient and conduction-radiation parameter. Only using the optical information is enough in estimation of graded refractive index and simultaneous estimation of graded refractive index and absorption coefficient when the conduction-radiation parameter is known. It was found that an increase of measurement noise significantly deteriorated the estimation accuracy of multi-parameter by using single optical or thermal information. To address this issue, coupled optical and thermal information was suggested to be adopted as input to estimate multi-parameter simultaneously. All the simulation results show that SPSO can estimate the multi-parameter of semitransparent graded-index media accurately based on coupled optical and thermal information even with noise. The results obtained show that the proposed methodology is a promising approach for accurate estimation of multi-parameter in semitransparent graded index media. (C) 2016 Elsevier Masson SAS. All rights reserved.
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