Data-Driven Bending Elasticity Design by Shell Thickness

Journal article (2016)

Authors

Xiaoting Zhang Dartmouth College, The Chinese University of Hong Kong
Xinyi Le The Chinese University of Hong Kong, Shanghai Jiao Tong University
Zihao Wu The Chinese University of Hong Kong
C.C. Wang Materials and Manufacturing - IDE , The Chinese University of Hong Kong
Research Group
Materials and Manufacturing (IDE) (TU Delft)
Computer Graphics Computer-aided design Computational Geometry and Object Modeling—Physically based modeling Computer-Aided Engineering
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Published Date

2016

Language

English

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Faculty

Industrial Design Engineering

Department

Sustainable Design Engineering

Research Group

Materials and Manufacturing

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.