Simulation and Experimental Study of Inverse Heat Conduction Problem

Abstract:

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In this paper, a neural network method is proposed to solve a one dimensional inverse heat conduction problem (IHCP). The method relies on input/output data of an unknown system to create an intelligent neural network model. Multi layer perceptrons with recurrent properties are utilised in the model. Prepared input/output data are used to train the neural network. Reliable checking processes are also offered to justify the robustness of the method. A numerical sequential function specification (SFS) method is used as another technique to solve the IHCP. The numerical result is compared with that of the proposed method and good agreement is shown between the two methods. However, the numerical method can be only used to solve the IHCP off-line due to the high computation requirement. The proposed neural network method can be used in real-time situations as shown in the experimental tests.

Info:

Periodical:

Advanced Materials Research (Volumes 233-235)

Edited by:

Zhong Cao, Lixian Sun, Xueqiang Cao, Yinghe He

Pages:

2820-2823

DOI:

10.4028/www.scientific.net/AMR.233-235.2820

Citation:

L. Chen et al., "Simulation and Experimental Study of Inverse Heat Conduction Problem", Advanced Materials Research, Vols. 233-235, pp. 2820-2823, 2011

Online since:

May 2011

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Price:

$35.00

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