Design and volume optimization of space structures

Handle URI:
http://hdl.handle.net/10754/625845
Title:
Design and volume optimization of space structures
Authors:
Jiang, Caigui ( 0000-0002-1342-4094 ) ; Tang, Chengcheng ( 0000-0002-4875-6670 ) ; Seidel, Hans-Peter; Wonka, Peter ( 0000-0003-0627-9746 )
Abstract:
We study the design and optimization of statically sound and materially efficient space structures constructed by connected beams. We propose a systematic computational framework for the design of space structures that incorporates static soundness, approximation of reference surfaces, boundary alignment, and geometric regularity. To tackle this challenging problem, we first jointly optimize node positions and connectivity through a nonlinear continuous optimization algorithm. Next, with fixed nodes and connectivity, we formulate the assignment of beam cross sections as a mixed-integer programming problem with a bilinear objective function and quadratic constraints. We solve this problem with a novel and practical alternating direction method based on linear programming relaxation. The capability and efficiency of the algorithms and the computational framework are validated by a variety of examples and comparisons.
KAUST Department:
KAUST
Citation:
Jiang C, Tang C, Seidel H-P, Wonka P (2017) Design and volume optimization of space structures. ACM Transactions on Graphics 36: 1–14. Available: http://dx.doi.org/10.1145/3072959.3073619.
Publisher:
Association for Computing Machinery (ACM)
Journal:
ACM Transactions on Graphics
Issue Date:
21-Jul-2017
DOI:
10.1145/3072959.3073619
Type:
Article
ISSN:
0730-0301
Sponsors:
We thank the anonymous reviewers for their insightful comments and suggestions for improving the paper. This research was supported by the KAUST Office of Sponsored Research, the Visual Computing Center (VCC) at KAUST and by the Max Planck Center for Visual Computing and Communication. Chengcheng Tang would like to thank the support of NSF grant IIS-1528025, a Google Focused Research Award, a gift from the Adobe Corporation, and a hardware donation from NVIDIA. The authors would like to thank Helmut Pottmann, Leonidas Guibas, Renjie Chen, Lorenzo Greco, and Qingyun Sun for discussions, Virginia Unkefer and Olga Diamanti for proofreading, and Marko Tomicic for creating the renderings used in Figure 1 and Figure 3 (middle).
Additional Links:
https://dl.acm.org/citation.cfm?doid=3072959.3073619
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorJiang, Caiguien
dc.contributor.authorTang, Chengchengen
dc.contributor.authorSeidel, Hans-Peteren
dc.contributor.authorWonka, Peteren
dc.date.accessioned2017-10-10T05:52:02Z-
dc.date.available2017-10-10T05:52:02Z-
dc.date.issued2017-07-21en
dc.identifier.citationJiang C, Tang C, Seidel H-P, Wonka P (2017) Design and volume optimization of space structures. ACM Transactions on Graphics 36: 1–14. Available: http://dx.doi.org/10.1145/3072959.3073619.en
dc.identifier.issn0730-0301en
dc.identifier.doi10.1145/3072959.3073619en
dc.identifier.urihttp://hdl.handle.net/10754/625845-
dc.description.abstractWe study the design and optimization of statically sound and materially efficient space structures constructed by connected beams. We propose a systematic computational framework for the design of space structures that incorporates static soundness, approximation of reference surfaces, boundary alignment, and geometric regularity. To tackle this challenging problem, we first jointly optimize node positions and connectivity through a nonlinear continuous optimization algorithm. Next, with fixed nodes and connectivity, we formulate the assignment of beam cross sections as a mixed-integer programming problem with a bilinear objective function and quadratic constraints. We solve this problem with a novel and practical alternating direction method based on linear programming relaxation. The capability and efficiency of the algorithms and the computational framework are validated by a variety of examples and comparisons.en
dc.description.sponsorshipWe thank the anonymous reviewers for their insightful comments and suggestions for improving the paper. This research was supported by the KAUST Office of Sponsored Research, the Visual Computing Center (VCC) at KAUST and by the Max Planck Center for Visual Computing and Communication. Chengcheng Tang would like to thank the support of NSF grant IIS-1528025, a Google Focused Research Award, a gift from the Adobe Corporation, and a hardware donation from NVIDIA. The authors would like to thank Helmut Pottmann, Leonidas Guibas, Renjie Chen, Lorenzo Greco, and Qingyun Sun for discussions, Virginia Unkefer and Olga Diamanti for proofreading, and Marko Tomicic for creating the renderings used in Figure 1 and Figure 3 (middle).en
dc.publisherAssociation for Computing Machinery (ACM)en
dc.relation.urlhttps://dl.acm.org/citation.cfm?doid=3072959.3073619en
dc.rights© ACM, 2017. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Graphics, {, , (2017-07-21)} http://doi.acm.org/10.1145/3072959.3073619en
dc.titleDesign and volume optimization of space structuresen
dc.typeArticleen
dc.contributor.departmentKAUSTen
dc.identifier.journalACM Transactions on Graphicsen
dc.eprint.versionPost-printen
dc.contributor.institutionMax Planck Institute for Informaticsen
dc.contributor.institutionStanford Universityen
kaust.authorJiang, Caiguien
kaust.authorTang, Chengchengen
kaust.authorWonka, Peteren
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