Thermomechanical in-plane dynamic instability of asymmetric restrained functionally graded graphene reinforced composite arches via machine learning-based models

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@Article{YANG:2023:compstruct,

• author = "Zhicheng Yang and Shaoyu Zhao and Jie Yang and Airong Liu and Jiyang Fu",
• title = "Thermomechanical in-plane dynamic instability of asymmetric restrained functionally graded graphene reinforced composite arches via machine learning-based models",
• journal = "Composite Structures",
• year = "2023",
• volume = "308",
• pages = "116709",
• keywords = "genetic algorithms, genetic programming, Defective graphene, Functionally graded arch, Asymmetric elastic constraint, Dynamic instability, Thermomechanical action, Genetic programming assisted micromechanical model",
• URL = "https://www.sciencedirect.com/science/article/pii/S0263822323000533",
• ISSN = "0263-8223",
• DOI = "doi:10.1016/j.compstruct.2023.116709",
• abstract = "This paper studies the thermomechanical in-plane dynamic instability of asymmetric restrained functionally graded graphene reinforced composite (FG-GRC) arches, where graphene sheets with atom vacancy defects are distributed along the arch thickness according to a power law distribution. The temperature-dependent mechanical properties of the graphene reinforced composites are determined by a genetic programming (GP) assisted micromechanical model. The governing equations for the thermomechanical in-plane dynamic instability are derived by Hamilton's principle and solved by differential quadrature method (DQM) in conjunction with Bolotin method. Comprehensive numerical studies are performed to examine the effects of vacancy defect and graded distribution of graphene, temperature variation, load position, as well as boundary conditions on the free vibration, elastic buckling, and dynamic instability behaviors of the FG-GRC arch. Numerical results show that the structural performance of the FG-GRC arch is weakened by graphene defect and temperature rise and is significantly influenced by both graphene distribution and boundary conditions",

}

Genetic Programming entries for Zhicheng Yang Shaoyu Zhao Jie Yang Airong Liu Jiyang Fu

Citations