Data-Driven Bending Elasticity Design by Shell Thickness

Xiaoting Zhang, Xinyi Le, Zihao Wu, Charlie Wang

Research output: Contribution to journalArticleScientificpeer-review

14 Citations (Scopus)

Abstract

We present a method to design the deformation behavior of 3D printed models by an interactive tool, where the variation of bending elasticity at different regions of a model is realized by a change in shell thickness. Given a soft material to be used in 3D printing, we propose an experimental setup to acquire the bending behavior of this material on tubes with different diameters and thicknesses. The relationship between shell thickness and bending elasticity is stored in an echo state network using the acquired dataset. With the help of the network, an interactive design tool is developed to generate non-uniformly hollowed models to achieve desired bending behaviors. The effectiveness of this method is verified on models fabricated by different 3D printers by studying whether their physical deformation can match the designed target shape.
Original languageEnglish
Pages (from-to)157-166
Number of pages10
JournalComputer Graphics Forum (online)
Volume35
Issue number5
DOIs
Publication statusPublished - 2016
EventEurographics Symposium on Geometry Processing 2016 - Berlin, Germany
Duration: 20 Jun 201624 Jun 2016

Keywords

  • Computer Graphics
  • Computational Geometry and Object Modeling—Physically based modeling
  • Computer-Aided Engineering
  • Computer-aided design

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