Open Access

ARTICLE

The Detection of Super-elliptical Inclusions in Infrared Computerised Axial Tomography

by N.S.Mera¹, D.B.Ingham²

1 Centre for Computational Fluid Dynamics, University of Leeds, UK.
2 Department of Applied Mathematics, University of Leeds, UK.

Computer Modeling in Engineering & Sciences 2006, 15(2), 107-114. https://doi.org/10.3970/cmes.2006.015.107

Abstract

The purpose of this study is to investigate the efficiency, accuracy and rate of convergence of an evolutionary algorithm for detecting inclusions parametrised by superellipses in non-destructive evaluation and testing. The inverse problem investigated consists of identifying the geometry of discontinuities in a conductive material from Cauchy data measurements taken on the boundary. Temperature and heat flux are measured on the outside boundary of the domain and the position and the size of a super-elliptical inclusion are determined by minimising an objective functional using an evolution strategy. The super-elliptical form allows the parametric model to characterise a variety of shapes whilst at the same time regularizing the problem by the function specification method. The boundary element method is employed in order to solve the direct problem, i.e. to calculate the boundary data for a given geometric configuration. Numerical results are presented for several test examples for both exact and noisy boundary data. The algorithm developed by combining evolution strategies, the boundary element method and super-elliptical parametrisation is found to be a robust, fast and efficient method for detecting the size and location of subsurface inclusions.

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Keywords

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