Machine learning assisted investigation of defect influence on the mechanical properties of additively manufactured architected materials

• Main Authors: Hu, Erhai, Seetoh, Ian, Lai, Chang Quan
• 其他作者: School of Mechanical and Aerospace Engineering
• 格式: Article
• 語言: English
• 出版: 2022
• 主題: Engineering::Materials; Engineering::Mechanical engineering; Additive Manufacturing; Architected Materials
• 在線閱讀: https://hdl.handle.net/10356/156164

Additive manufacturing techniques can introduce defects that worsen the mechanical properties of 3D printed parts. Current techniques for quantifying the detrimental effects of these defects can only provide detailed analysis for a small number of geometries. Here, we investigate the effect of each...