Construction of GPT-Vanishing Structures Using Shape Derivative
Abstract
The Generalized Polarization Tensors (GPT) are a series of tensors which contain information on the shape of a domain and its material parameters. The aim of this paper is to provide a method of constructing GPT-vanishing structures using shape derivative for two-dimensional conductivity or anti-plane elasticity problem. We assume a multi-coating geometry as a candidate of GPT-vanishing structure. We define a cost functional to minimize GPT and compute the shape derivative of this functional deriving an asymptotic expansion of the perturbations of the GPTs due to a small deformation of interfaces of the structure. We present some numerical examples of GPT-vanishing structures for several different shaped inclusions.
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How to Cite
Construction of GPT-Vanishing Structures Using Shape Derivative. (2018). Journal of Computational Mathematics, 35(5), 569-585. https://doi.org/10.4208/jcm.1605-m2016-0540