An extension of shape sensitivity analysis to an immersed boundary method based on Cartesian grids

[EN] Gradient-based shape optimization processes of mechanical components require the gradients (sensitivity) of the magnitudes of interest to be calculated with sufficient accuracy. The aim of this study was to develop algorithms for the calculation of shape sensitivities considering geometric repr...

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Detalles Bibliográficos
Autores: Marco, Onofre, Ródenas, Juan José|||0000-0003-2195-7920, Fuenmayor Fernández, Francisco-Javier|||0000-0003-3594-9593, Tur Valiente, Manuel|||0000-0001-7683-4771
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/133375
Acceso en línea:https://riunet.upv.es/handle/10251/133375
Access Level:acceso abierto
Palabra clave:Cartesian grid-FEM
Sensitivity analysis
Velocity field
NURB
INGENIERIA MECANICA
Descripción
Sumario:[EN] Gradient-based shape optimization processes of mechanical components require the gradients (sensitivity) of the magnitudes of interest to be calculated with sufficient accuracy. The aim of this study was to develop algorithms for the calculation of shape sensitivities considering geometric representation by parametric surfaces (i.e. NURBS or T-splines) using 3D Cartesian h-adapted meshes independent of geometry. A formulation of shape sensitivities was developed for an environment based on Cartesian meshes independent of geometry, which implies, for instance, the need to take into account the special treatment of boundary conditions imposed in non body-fitted meshes. The immersed boundary framework required to implement new methods of velocity field generation, which have a primary role in the integration of both the theoretical concepts and the discretization tools in shape design optimization. Examples of elastic problems with three-dimensional components are given to demonstrate the efficiency of the algorithms.