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Journal of Information Science and Engineering, Vol. 28 No. 1, pp. 67-82 (January 2012)

Estimation of Unknown Inlet Temperature Profile Using an Improved Gbest-PSO*

College of Storage and Transportation and Architectural Engineering
China University of Petroleu, Hua Dong
Qing Dao, ShanDong, 266555, P.R. China
+State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources
North China Electric Power University
Beijing 102206, P.R. China

In this study, an improved gbest-PSO is proposed to overcome the shortcoming of earlier convergence of classical gbest-PSO. Then the improved gbest-PSO is used to identify the unknown inlet temperature profile in a plate channel flow. The effects of measurement position and measurement error on the accuracy of prediction are studied thoroughly. Analysis of computational results of two test problems shows that the improved gbest-PSO proposed in this paper has an excellent smooth convergence characteristic. The local refine mechanism introduced in the improved gbest-PSO increases the opportunity of finding the global optimum greatly especially for high dimensional multimodal optimization problems. Accurate results are obtained even when the measurements contain a 10% noise. Consequently, the inverse convection heat transfer problem is successfully solved by the improved gbest-PSO.

Keywords: particle swarm optimization, inverse convection heat transfer, channel flow, global optimization, evolutionary computation

Full Text () Retrieve PDF document (201201_05.pdf)

Received February 22, 2011; revised August 4, 2011; accepted August 31, 2011.
Communicated by I-Chen Wu.
* This work was supported by the National Natural Science Foundation of China, Young Scientists Fund (Grant No. 51006121); also partially supported by Young Scientists Fund of NSF of China (51106049).