Data-Driven Bending Elasticity Design by Shell Thickness

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• 作者：Xiaoting Zhang ; Xinyi Le ; Zihao Wu ; Emily Whiting and Charlie C.L. Wang
• 刊名：Computer Graphics Forum
• 出版年：2016
• 出版时间：August 2016
• 年：2016
• 卷：35
• 期：5
• 页码：157-166
• 全文大小：6563K
• ISSN：1467-8659

文摘

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.