A new overhang constraint for topology optimization of self-supporting structures in additive manufacturing

This work falls within the scope of computer-aided optimal design, and aims to integrate the topology optimization procedures and recent additive manufacturing technologies (AM). The elimination of scaffold supports at the topology optimization stage has been recognized and pursued by many authors r...

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Bibliographic Details
Published in:Structural and multidisciplinary optimization 2018-11, Vol.58 (5), p.2003-2017
Main Authors: Garaigordobil, Alain, Ansola, Rubén, Santamaría, Javier, Fernández de Bustos, Igor
Format: Article
Language:English
Subjects:
Additive manufacturing
Algorithms
CAD
Computational Mathematics and Numerical Analysis
Computer aided design
Edge detection
Engineering
Engineering Design
Image analysis
Image detection
Inclination angle
Research Paper
Theoretical and Applied Mechanics
Topology optimization
Workflow
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Summary:This work falls within the scope of computer-aided optimal design, and aims to integrate the topology optimization procedures and recent additive manufacturing technologies (AM). The elimination of scaffold supports at the topology optimization stage has been recognized and pursued by many authors recently. The present paper focuses on implementing a novel and specific overhang constraint that is introduced inside the topology optimization problem formulation along with the regular volume constraint. The proposed procedure joins the design and manufacturing processes into a integrated workflow where any component can directly be manufactured with no requirement of any sacrificial support material right after the topology optimization process. The overhang constraint presented in this work is defined by the maximum allowable inclination angle, where the inclination of any member is computed by the Smallest Univalue Segment Assimilating Nucleus (SUSAN), an edge detection algorithm developed in the field of image analysis and processing. Numerical results on some benchmark examples, along with the numerical performances of the proposed method, are introduced to demonstrate the capacities of the presented approach.
ISSN:1615-147X
1615-1488
DOI:10.1007/s00158-018-2010-7