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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 108
PROCEEDINGS OF THE FIFTEENTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING
Edited by: J. Kruis, Y. Tsompanakis and B.H.V. Topping
Paper 233

The Scaled-Boundary Finite Element Solution Method for Inverse Heat Conduction Problems

F. Kowsari1, T. Sokhansefat2, M. Moradi2 and S. Mohasseb3

1School of Mechanical Engineering, University of Tehran, Iran
2Faculty of New Sciences and Technologies, University of Tehran, Iran
3Smteam GmbH, Meilen, Switzerland

Full Bibliographic Reference for this paper
F. Kowsari, T. Sokhansefat, M. Moradi, S. Mohasseb, "The Scaled-Boundary Finite Element Solution Method for Inverse Heat Conduction Problems", in J. Kruis, Y. Tsompanakis, B.H.V. Topping, (Editors), "Proceedings of the Fifteenth International Conference on Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Stirlingshire, UK, Paper 233, 2015. doi:10.4203/ccp.108.233
Keywords: inverse heat conduction, scaled boundary finite element method, genetic algorithm, inverse heat conduction problems.

Summary
The scaled boundary finite element method is a semi analytical fundamental solution-less boundary-element method which links to both finite elements and boundary elements. In this paper coupling of scaled boundary finite element method (SBFEM) and genetic algorithm (GA) is used to solve inverse heat conduction problems (IHCP) for a square plate in a two dimensional steady state. Inverse heat conduction methods can be used to determine heat flux and temperatures on an inaccessible surface of a wall by measuring the temperature on an accessible boundary. Herein, the unknown heat flux at the boundary is estimated using an IHCP. Temperature differences between the calculated and exact values at the middle of the plate is considered as the objective function. The validation of the SBFEM results is proved by comparing temperature distributions which are determined using the finite element method. The accuracy of the SBFEM and the low computational cost demonstrates an efficient method for IHCPs.

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