Análise de sensibilidade topológica de segunda ordem

• Autor(a) principal: Faria, Jairo Rocha de
• Data de Publicação: 2007
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações do LNCC
• Texto Completo: https://tede.lncc.br/handle/tede/72
• topic: Análise de sensibilidade topológica; Derivada topológica; Derivada topológica de segunda ordem; Análise assintótica; Topological sensitivity analysis; Topological rerivative; Second order topological derivative; Asymptotic analysis; CNPQ::CIENCIAS EXATAS E DA TERRA::MATEMATICA::ANALISE::EQUACOES DIFERENCIAIS PARCIAIS

The topological derivative provides the sensitivity of a given shape functional with respect to an infinitesimal non-smooth domain pertubation (insertion of hole or inclusion, for instance). Classically, this derivative comes from the second term of the topological asymptotic expansion, dealing only with inifinitesimal pertubations. However, for pratical applications, we need to insert pertubations of finite sizes.Therefore, we consider other terms in the expansion, leading to the concept of higher-order topological derivatives. In a particular, we observe that the topological-shape sensitivity method can be naturally extended to calculate these new terms, resulting in a systematic methodology to obtain higher-order topological derivatives. In order to present these ideas, initially we apply this technique in some problems with exact solution, where the topological asymptotic expansion is obtained until third order. Later, we calculate first as well as second order topological derivative for the total potential energy associated to the Laplace equation in two-dimensional domain pertubed with the insertion of a hole, considering homogeneous Neumann or Dirichlet boundary conditions, or an inclusion with thermal conductivity coefficient value different from the bulk material. With these results, we present some numerical experiments showing the influence of the second order topological derivative in the topological asymptotic expansion, which has two main features:it allows us to deal with pertubations of finite sizes and provides a better descent direction in optimization and reconstruction algorithms.