Title
Data-Driven Bending Elasticity Design by Shell Thickness.
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.
Year
DOI
Venue
2016
10.1111/cgf.12972
Comput. Graph. Forum
Keywords
Field
DocType
Categories and Subject Descriptors (according to ACM CCS),I,3,5 [Computer Graphics]: Computational Geometry and Object ModelingPhysically based modeling,J,6 [Computer-Aided Engineering]: Computer-aided design (CAD)
Computer vision,Data-driven,Interactive design,Simulation,Computer science,Mechanical engineering,Bending,Artificial intelligence,3D printing,Echo state network,Deformation (mechanics),Elasticity (economics)
Journal
Volume
Issue
ISSN
35
5
0167-7055
Citations 
PageRank 
References 
6
0.40
49
Authors
5
Name
Order
Citations
PageRank
Xiaoting Zhang1582.95
Xinyi Le28513.26
Zihao Wu360.40
Emily Whiting428217.71
Charlie C. L. Wang51280100.10