Machine learning-assisted pattern recognition algorithms for estimating ultimate tensile strength in fused deposition modelled polylactic acid specimens

IF 2.9 4区材料科学 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY

Materials Technology Pub Date : 2023-12-17 DOI:10.1080/10667857.2023.2295089

Akshansh Mishra, Vijaykumar S. Jatti, Eyob Messele Sefene, Ashwini V. Jatti, Addisalem Desalegn Sisay, Nitin K. Khedkar, Sachin Salunkhe, Marek Pagáč, Emad S. Abouel Nasr

引用次数: 0

Abstract

In this study, we investigate the application of supervised machine learning algorithms for estimating the Ultimate Tensile Strength (UTS) of Polylactic Acid (PLA) specimens fabricated using the Fu...

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来源期刊

Materials Technology 工程技术-材料科学：综合

CiteScore

6.00

自引率

9.70%

发文量

105

审稿时长

8.7 months

期刊介绍： Materials Technology: Advanced Performance Materials provides an international medium for the communication of progress in the field of functional materials (advanced materials in which composition, structure and surface are functionalised to confer specific, applications-oriented properties). The focus is on materials for biomedical, electronic, photonic and energy applications. Contributions should address the physical, chemical, or engineering sciences that underpin the design and application of these materials. The scientific and engineering aspects may include processing and structural characterisation from the micro- to nanoscale to achieve specific functionality.