利用双神经网络-代用模型和遗传算法同时优化纤维复合材料层压板的纤维路径和几何尺寸

IF 1.8 3区材料科学 Q3 MATERIALS SCIENCE, COMPOSITES

Advanced Composite Materials Pub Date : 2024-02-01 DOI:10.1080/09243046.2024.2305488

Kenji Asakawa, Yoshiyasu Hirano, Toshio Ogasawara

引用次数: 0

摘要

CFRP 的特点是各向异性。因此，将纤维方向作为设计变量可进一步减轻结构重量。在这项研究中，纤维方向的设计变量是钢材的...

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Simultaneous optimization of fiber paths and geometric dimensions for fiber composite laminates using double neural network-surrogate model and genetic algorithm

CFRP is characterized by its anisotropic properties. Therefore, further structural weight reduction might be achieved by introducing the fiber direction as a design variable. For this study, steeri...

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来源期刊

Advanced Composite Materials 工程技术-材料科学：复合

CiteScore

5.00

自引率

20.70%

发文量

审稿时长

3 months

期刊介绍： "Advanced Composite Materials (ACM), a bi-monthly publication of the Japan Society for Composite Materials and the Korean Society for Composite Materials, provides an international forum for researchers, manufacturers and designers who are working in the field of composite materials and their structures. Issues contain articles on all aspects of current scientific and technological progress in this interdisciplinary field. The topics of interest are physical, chemical, mechanical and other properties of advanced composites as well as their constituent materials; experimental and theoretical studies relating microscopic to macroscopic behavior; testing and evaluation with emphasis on environmental effects and reliability; novel techniques of fabricating various types of composites and of forming structural components utilizing these materials; design and analysis for specific applications. Advanced Composite Materials publishes refereed original research papers, review papers, technical papers and short notes as well as some translated papers originally published in the Journal of the Japan Society for Composite Materials. Issues also contain news items such as information on new materials and their processing."