Identification of Thermal Diffusion Coefficients for Transient Heat Conduction Problems With Heat Sources

ZHOU Huanlin; YAN Jun; YU Bo; CHEN Haolong

doi:10.21656/1000-0887.380199

Volume 39 Issue 2

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Article Navigation > Applied Mathematics and Mechanics > 2018 > 39(2): 160-169

ZHOU Huanlin, YAN Jun, YU Bo, CHEN Haolong. Identification of Thermal Diffusion Coefficients for Transient Heat Conduction Problems With Heat Sources[J]. Applied Mathematics and Mechanics, 2018, 39(2): 160-169. doi: 10.21656/1000-0887.380199

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Identification of Thermal Diffusion Coefficients for Transient Heat Conduction Problems With Heat Sources

doi: 10.21656/1000-0887.380199

¹School of Civil Engineering, Hefei University of Technology, Hefei 230009, P.R.China;²Steel Structure Construction Co. Ltd., China Tiesiju Civil Engineering Group, Hefei 230088, P.R.China

Funds: The National Natural Science Foundation of China(11672098;11502063)

Received Date: 2017-07-19
Rev Recd Date: 2017-12-18
Publish Date: 2018-02-15

Abstract

Abstract

An improved cuckoo search (ICS) algorithm was developed to identify the thermal diffusion coefficients for inverse transient heat conduction problems with heat sources. The heat conduction problem with heat source was transformed into one without heat source. The direct problem was solved with the boundary element method. The thermal diffusion coefficient was treated as the optimization variable, and the difference between the calculated temperature and the measured temperature was taken as the objective function. The thermal diffusion coefficient was optimized through minimization of the objective function with the ICS algorithm. Comparison between the results of the conjugate gradient method (CGM), the cuckoo search (CS) algorithm and the ICS algorithm indicates that the ICS algorithm is less sensitive to iterative initialization than the CGM, and the ICS algorithm has higher efficient convergence than the CS algorithm. The numerical examples were devoted to the influences of the measured point number, the nest number and the measured noise. The result accuracy decreases with the measured point number, and the iteration number decreases with the nest number. Moreover, the higher the measured noise goes, the lower the result accuracy will be. The results show that the ICS algorithm is accurate and efficient for the identification of thermal diffusion coefficients.
- heat conduction,
- inverse problem,
- thermal diffusion coefficient,
- improved cuckoo search algorithm,
- boundary element method

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References(17)

References

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