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A methodology for adaptive mesh refinement in optimum shape design problems
Affiliation:1. University of Liège, Department of Architecture, Geology, Environment and Constructions, Mechanics of Solids and Structures, Chemin des Chevreuils, 1, B52/3, 4000 Liège, Belgium;2. University of Liège, Department of Architecture, Geology, Environment and Constructions, Structural Engineering Division, Chemin des Chevreuils, 1, B52/3, 4000 Liège, Belgium;1. Composite Construction Laboratory (CCLab), Ecole Polytechnique Fédérale de Lausanne (EPFL), Station 16, Bâtiment BP, CH-1015 Lausanne, Switzerland;2. Timber and Composite Construction, Bern University of Applied Sciences, Solothurnstrasse 102, Biel, Switzerland;1. Instituto Universitario de Arquitectura y Ciencias de la Construcción, Escuela Técnica Superior de Arquitectura, Universidad de Sevilla, Avenida Reina Mercedes, n 2, 41012 Sevilla, Spain;2. Department of Structures, Laboratório Nacional de Engenharia Civil, Avenida do Brasil, 101, 1700-066 Lisboa, Portugal
Abstract:This work presents a methodology based on the use of adaptive mesh refinement (AMR) techniques in the context of shape optimization problems analyzed by the Finite Element Method (FEM). A suitable and very general technique for the parametrization of the optimization problem using B-splines to define the boundary is first presented. Then, mesh generation using the advancing front method, the error estimation and the mesh refinement criteria are dealt with in the context of a shape optimization problems. In particular, the sensitivities of the different ingredients ruling the problem (B-splines, finite element mesh, design behaviour, and error estimator) are studied in detail. The sensitivities of the finite element mesh coordinates and the error estimator allow their projection from one design to the next, giving an “a priori knowledge” of the error distribution on the new design. This allows to build up a finite element mesh for the new design with a specified and controlled level of error. The robustness and reliability of the proposed methodology is checked out with some 2D examples.
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