SIGGRAPH Asia 2013 Technical Briefs 2013
DOI: 10.1145/2542355.2542361
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Cross-sectional structural analysis for 3D printing optimization

Abstract: We propose a novel cross-sectional structural analysis technique that efficiently detects critical stress inside a 3D object. We slice the object into cross-sections and compute stress based on bending momentum equilibrium. Unlike traditional approaches based on finite element methods, our method does not require a volumetric mesh or solution of linear systems, enabling interactive analysis speed. Based on the stress analysis, the orientation of an object is optimized to increase mechanical strength when manuf… Show more

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Cited by 116 publications
(93 citation statements)
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“…Xie et al [38] propose an accelerated analysis algorithm through locally updating stiffness matrix of FEM. Furthermore, Umetani et al [29] and Xu et al [39] analyze the key stress of the model based on bending momentum equilibrium which enables interactive analysis speed. In this work, the method proposed by Umetani et al [29] is used to detect structural weak and strong regions.…”
Section: Related Workmentioning
confidence: 99%
See 4 more Smart Citations
“…Xie et al [38] propose an accelerated analysis algorithm through locally updating stiffness matrix of FEM. Furthermore, Umetani et al [29] and Xu et al [39] analyze the key stress of the model based on bending momentum equilibrium which enables interactive analysis speed. In this work, the method proposed by Umetani et al [29] is used to detect structural weak and strong regions.…”
Section: Related Workmentioning
confidence: 99%
“…Furthermore, Umetani et al [29] and Xu et al [39] analyze the key stress of the model based on bending momentum equilibrium which enables interactive analysis speed. In this work, the method proposed by Umetani et al [29] is used to detect structural weak and strong regions. The weak regions are enhanced, and the strong regions are adaptively hollowed which is not considered in [29] and [39].…”
Section: Related Workmentioning
confidence: 99%
See 3 more Smart Citations