Ambiguous phase assignment of discretized 3D geometries in topology optimization

• Published in: arXiv.org
• Main Authors: Barrera, Jorge L, Maute, Kurt
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 20.02.2020
• Subjects: Algorithms; Ambiguity; Computer Science - Computational Engineering, Finance, and Science; Configurations; Design optimization; Discretization; Finite element method; Mathematics - Optimization and Control; Optimization; Phase assignment; Topology optimization
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2002.10255

Level set-based immersed boundary techniques operate on nonconforming meshes while providing a crisp definition of interface and external boundaries. In such techniques, an isocontour of a level set field interpolated from nodal level set values defines a problem's geometry. If the interface is explicitly tracked, the intersected elements are typically divided into sub-elements to which a phase needs to be assigned. Due to loss of information in the discretization of the level set field, certain geometrical configurations allow for ambiguous phase assignment of sub-elements, and thus ambiguous definition of the interface. The study presented here focuses on analyzing these topological ambiguities in embedded geometries constructed from discretized level set fields on hexahedral meshes. The analysis is performed on three-dimensional problems where several intersection configurations can significantly affect the problem's topology. This is in contrast to two-dimensional problems where ambiguous topological features exist only in one intersection configuration and identifying and resolving them is straightforward. A set of rules that resolve these ambiguities for two-phase problems is proposed, and algorithms for their implementations are provided. The influence of these rules on the evolution of the geometry in the optimization process is investigated with linear elastic topology optimization problems. These problems are solved by an explicit level set topology optimization framework that uses the extended finite element method to predict physical responses. This study shows that the choice of a rule to resolve topological features can result in drastically different final geometries. However, for the problems studied in this paper, the performances of the optimized design do not differ.