Simulation and Experimental Study of Inverse Heat Conduction Problem

Abstract:

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.

• Periodical: Advanced Materials Research (Volumes 233-235)
• Pages: 2820-2823
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.233-235.2820
• Online since: May 2011
• Authors: Ley Chen, S Askarian, M Mohammadzaheri, F Samadi

References

[1] Beck, J. V.,Blackwell, B. and Clair, C. R. S. (1985). Inverse Heat Conduction: Ill-posed Problems. NY, Wiley Intersciences.

[2] Tikhonov , A. N. and Arsenin, V. Y. (1977). Solution of Ill- Posed Problems. Washington D.C., V. H. Winston and Sons.

[3] Özicik, M. N. and Orlande, R. B. (2000). Inverse Heat Transfer's Fundamentals & Applications. London, Taylor and Francis.

[4] Kowsary, F.,Behbahaninia, A. and Pourshaghaghy, A. (2006). Transient Heat Flux Function Estimation Utilizing the Variable Metric Method, International Communications in Heat and Mass Transfer.

DOI: 10.1016/j.icheatmasstransfer.2006.02.008

[5] Behbahaninia, A. and Kowsary, F. (2004), A dual reciprocity BE-based sequential function specification method for inverse heat conduction problem, International Journal of Heat and Mass Transfer, 47(2), pp.1247-1255.

DOI: 10.1016/j.ijheatmasstransfer.2003.09.023

[6] Deng , S. and Hwang, Y. (2006). Applying neural networks to the solution of forward and inverse heat conduction problems, International Journal of Heat and Mass Transfer 49, pp:4732–4750.

DOI: 10.1016/j.ijheatmasstransfer.2006.06.009

[7] Morteza Mohammadzaheri and Lei Chen, (2010), Intelligent predictive control of a model helicopter's yaw angle, Asian Journal of Control, Vol.12, No.6, pp.1-13.

DOI: 10.1002/asjc.243