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dc.contributor.authorGavriil, Konstantinos
dc.contributor.authorGuseinov, Ruslan
dc.contributor.authorPÉREZ, JESÚS
dc.contributor.authorPELLIS, DAVIDE
dc.contributor.authorHenderson, Paul
dc.contributor.authorRist, Florian
dc.contributor.authorPottmann, Helmut
dc.contributor.authorBickel, Bernd
dc.date.accessioned2020-10-21T06:37:17Z
dc.date.available2020-10-21T06:37:17Z
dc.date.issued2020-11-27
dc.identifier.citationKonstantinos Gavriil, Ruslan Guseinov, Jesús Pérez, Davide Pellis, Paul Henderson, Florian Rist, Helmut Pottmann, and Bernd Bickel. 2020. Computational Design of Cold Bent Glass Façades. ACM Trans. Graph. 39, 6, Article 208 (December 2020), 16 pages. https://doi.org/10.1145/3414685.3417843
dc.identifier.doi10.1145/3414685.3417843
dc.identifier.urihttp://hdl.handle.net/10754/665638
dc.description.abstractCold bent glass is a promising and cost-efficient method for realizing doubly curved glass facades. They are produced by attaching planar glass sheets to curved frames and require keeping the occurring stress within safe limits. However, it is very challenging to navigate the design space of cold bent glass panels due to the fragility of the material, which impedes the form-finding for practically feasible and aesthetically pleasing cold bent glass facades. We propose an interactive, data-driven approach for designing cold bent glass facades that can be seamlessly integrated into a typical architectural design pipeline. Our method allows non-expert users to interactively edit a parametric surface while providing real-time feedback on the deformed shape and maximum stress of cold bent glass panels. Designs are automatically refined to minimize several fairness criteria while maximal stresses are kept within glass limits. We achieve interactive frame rates by using a differentiable Mixture Density Network trained from more than a million simulations. Given a curved boundary, our regression model is capable of handling multistable configurations and accurately predicting the equilibrium shape of the panel and its corresponding maximal stress. We show predictions are highly accurate and validate our results with a physical realization of a cold bent glass surface.
dc.description.sponsorshipWe thank IST Austria’s Scientific Computing team for their support, Corinna Datsiou and Sophie Pennetier for their expert input on the practical applications of cold bent glass, and Zaha Hadid Architects and Waagner Biro for providing the architectural datasets. Photo of Fondation Louis Vuitton by Francisco Anzola / CC BY 2.0 / cropped. Photo of Opus by Danica O. Kus. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 675789 - Algebraic Representations in Computer-Aided Design for complEx Shapes (ARCADES), from the European Research Council (ERC) under grant agreement No 715767 - MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and Modeling, and SFB-Transregio “Discretization in Geometry and Dynamics” through grant I 2978 of the Austrian Science Fund (FWF). F. Rist and K. Gavriil have been partially supported by KAUST baseline funding.
dc.language.isoen
dc.publisherACM
dc.rightsArchived with thanks to ACM Transactions on Graphics
dc.subjectmechanical simulation
dc.subjectcold bent glass
dc.subjectneural networks
dc.subjectcomputational design
dc.subjectinverse design
dc.titleComputational Design of Cold Bent Glass Façades
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentVisual Computing Center (VCC)
dc.identifier.journalACM Transactions on Graphics
dc.eprint.versionPost-print
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
pubs.publication-statusAccepted
dc.identifier.arxivid2009.03667
kaust.personPottmann, Helmut
kaust.personRist, Florian
refterms.dateFOA2020-10-21T06:37:18Z
dc.date.published-online2020-11-27
dc.date.published-print2020-11-26
dc.date.posted2020-09-08


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