Quantitative Damage Monitoring of Filament Wound Composites by Using Machine Learning-Based Techniques

IF 2.3 4区 材料科学 Q3 MATERIALS SCIENCE, COMPOSITES Applied Composite Materials Pub Date : 2023-11-06 DOI:10.1007/s10443-023-10174-0
Amir Bani Mohammad Ali, Saleh Valizadeh Sotubadi, Sajad Alimirzaei, Mehdi Ahmadi Najafabadi, Lotfollah Pahlavan
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基于机器学习技术的纤维缠绕复合材料损伤定量监测
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来源期刊
Applied Composite Materials
Applied Composite Materials 工程技术-材料科学:复合
CiteScore
4.20
自引率
4.30%
发文量
81
审稿时长
1.6 months
期刊介绍: Applied Composite Materials is an international journal dedicated to the publication of original full-length papers, review articles and short communications of the highest quality that advance the development and application of engineering composite materials. Its articles identify problems that limit the performance and reliability of the composite material and composite part; and propose solutions that lead to innovation in design and the successful exploitation and commercialization of composite materials across the widest spectrum of engineering uses. The main focus is on the quantitative descriptions of material systems and processing routes. Coverage includes management of time-dependent changes in microscopic and macroscopic structure and its exploitation from the material''s conception through to its eventual obsolescence.
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