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Article . 2022
License: CC BY NC
Data sources: ZENODO
ZENODO
Article . 2022
License: CC BY NC
Data sources: Datacite
ZENODO
Article . 2022
License: CC BY NC
Data sources: Datacite
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Comparison of Strength of Generatively Designed 3D Printed Models under Uniaxial Load

Authors: Saurav Patwardhan; Advay Deshpande;

Comparison of Strength of Generatively Designed 3D Printed Models under Uniaxial Load

Abstract

This research aims to investigate the utility of generative design as a viable alternative to conventional design practices for structural members on the basis of strength and deformation. The necessity of generative design may arise due to either space constraints in a particular application or the need for a specific load taking capacity from a set amount of material mass. In this project, a total of 3 models were created – one for tension, one for compression and one for bending; first according to generative design using an artificial intelligence computer software and then according to conventional design practices and known specimens. It was ensured that the masses of these models were approximately equal. These models have then been 3d printed using an open-ware printer using ABS plastic by the FDM process and have been tested using ramped loading to compare their load bearing ability, strength, and failure pattern.

Keywords

3d printing, generative design, fused deposition modelling, anisotropy, failure pattern

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average