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_id	caadria2022_299
id	caadria2022_299
authors	Cui, Qiang, Zhang, Huikai, Pawar, Siddharth Suhas, Yu, Chuan, Feng, Xiqiao and Qiu, Song
year	2022
title	Topology Optimization for 3D-Printable Large-Scale Metallic Hollow Structures With Self-Supporting
doi	https://doi.org/10.52842/conf.caadria.2022.2.101
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 101-110
summary	Design for Additive Manufacturing (DfAM), is a one of the most commonly used and foundational techniques used in the development of new products, and particularly those that involve large-scale metallic structures composed of hollow components. One such AM technique is Wire Arc Additive Manufacturing (WAAM), which is the application of robotic welding technology applied to Additive Manufacturing. Due to the lack of a simple method to describe the fabricating constraint of WAAM and the complex hollow morphology, which difficultly deploys topology optimization structural techniques that use WAAM. In this paper, we develop a design strategy that unifies ground-structure optimization method with generative design that considers the features of hollow components, WAAM overhang angle limits and manufacturing thickness limits. The method is unique in that the user can interact with the design results, make changes to parameters, and alter the design based on the user‚s aesthetic or specific manufacturing setup needs. We deploy the method in the design and 3D printing of an optimized Electric Vehicle Chassis and successfully test in under different loading conditions.
keywords	Topology optimization, Generative design, Self-supporting, Hollow structures, Metallic 3D printing, SDG 12
series	CAADRIA
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last changed	2022/07/22 07:34

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