On Topological Derivatives for Elastic Solids with Uncertain Input Data

I. Hlaváček (), A. A. Novotny (), J. Sokołowski () and A. Żochowski ()
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I. Hlaváček: Academy of Sciences of the Czech Republic
A. A. Novotny: Laboratório Nacional de Computação Científica LNCC/MCT
J. Sokołowski: Université Henri Poincaré Nancy I
A. Żochowski: Polish Academy of Sciences

Journal of Optimization Theory and Applications, 2009, vol. 141, issue 3, No 6, 569-595

Abstract: Abstract In this paper, a new approach to the derivation of the worst scenario and the maximum range scenario methods is proposed. The derivation is based on the topological derivative concept for the boundary-value problems of elasticity in two and three spatial dimensions. It is shown that the topological derivatives can be applied to the shape and topology optimization problems within a certain range of input data including the Lamé coefficients and the boundary tractions. In other words, the topological derivatives are stable functions and the concept of topological sensitivity is robust with respect to the imperfections caused by uncertain data. Two classes of integral shape functionals are considered, the first for the displacement field and the second for the stresses. For such classes, the form of the topological derivatives is given and, for the second class, some restrictions on the shape functionals are introduced in order to assure the existence of topological derivatives. The results on topological derivatives are used for the mathematical analysis of the worst scenario and the maximum range scenario methods. The presented results can be extended to more realistic methods for some uncertain material parameters and with the optimality criteria including the shape and topological derivatives for a broad class of shape functionals.

Keywords: Topological derivative; Elasticity system; Uncertain input data; Asymptotic analysis (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10957-008-9490-3

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