Simulation and experimental study of inverse heat conduction problem

L. Chen, S. Askarian, M. Mohammadzaheri, F. Samadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationFundamental of Chemical Engineering
Pages2820-2823
Number of pages4
Volume233-235
DOIs
Publication statusPublished - 2011
Event2011 International Conference on Chemical Engineering and Advanced Materials, CEAM 2011 - Changsha, China
Duration: May 28 2011May 30 2011

Publication series

NameAdvanced Materials Research
Volume233-235
ISSN (Print)1022-6680

Other

Other2011 International Conference on Chemical Engineering and Advanced Materials, CEAM 2011
CountryChina
CityChangsha
Period5/28/115/30/11

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Keywords

  • ANSYS parametric design language
  • Artificial neural network
  • Inverse heat conduction problem
  • Sequential function specification

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Chen, L., Askarian, S., Mohammadzaheri, M., & Samadi, F. (2011). Simulation and experimental study of inverse heat conduction problem. In Fundamental of Chemical Engineering (Vol. 233-235, pp. 2820-2823). (Advanced Materials Research; Vol. 233-235). https://doi.org/10.4028/www.scientific.net/AMR.233-235.2820