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ISSN 2753-3239
ISSN 2753-3239
CCC: 8
PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY
PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY
Edited by: P. Iványi, J. Kruis and B.H.V. Topping
Paper 2.2
Parallel Enclosed Hole Detection for Introducing Manufacturing Constraints in Topology Optimization
D. Herrero-Pérez
Department of Structures, Construction and Graphic Expression, Technical University of Cartagena, Cartagena, Spain
Full Bibliographic Reference for this paper
D. Herrero-Pérez, "Parallel Enclosed Hole Detection for Introducing Manufacturing Constraints in Topology Optimization", in P. Iványi, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Twelfth International Conference on
Engineering Computational Technology", Civil-Comp Press, Edinburgh, UK,
Online volume: CCC 8, Paper 2.2, 2024, doi:10.4203/ccc.8.2.2
Keywords: connectivity, topology optimization, enclosed holes, high-performance computing, additive manufacturing, computational effort.
Abstract
This work presents a distributed approach based on Graph Theory for detecting enclosed holes in
density-based topology optimization using the traditional material penalization scheme. The
distributed topology optimization framework divides the domain into several subdomains to exploit
parallel computing resources. The proposal generates a set of graphs from the empty elements of the
meshes of such subdomains, detecting the empty regions and classifying them. Then, it generates a
hierarchical distributed graph between the subdomains to obtain a coherent representation of the
connectivity design, minimizing inter-node communications in the classification of the empty regions.
We use such information to introduce manufacturing constraints preventing enclosed holes in the final
designs, which is especially useful in diverse additive manufacturing techniques because such holes can
induce failures in the manufacturing process. We validate the proposal using a classical two-dimensional
cantilever problem with asymmetric simplifications and parallel computing.
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