Application of computer simulation to model transient vibration responses of GPLs reinforced doubly curved concrete panel under instantaneous heating

Yinghao Zhao, Wenjun Dai,Zeyu Wang,Adham E. Ragab

MATERIALS TODAY COMMUNICATIONS(2024)

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摘要
In this article for the first time, with the aid of computer simulation, transient vibration responses of the concrete doubly curved panel exposed to immediate heating are reported owing to the significance of concrete panels used in civil applications. The substrate includes spring element, shear, torsion, and substrate-structure friction factor. A novel model of a two-parameter substrate is introduced in this research with enough flexibility to involve three forms of polynomial, sinusoidal, and cosinusoidal expansion with various terms in its stiffness. With the aid of Halpin-Tsai micromechanics and the well-known rule of mixtures, the material properties of the graphene nanoplatelet (GPLs) composites reinforced doubly curved concrete panels are modeled. As well as this, for accurate modeling of the current work, the thermal conductivity of each continuous GPLs layer along with thickness direction using mathematical simulation is presented. Finally, entropy, the constitutive heat conduction equation, the Heaviside unit step function, and thermal shock loading are used in the final governing equations. The Laplace transform is employed to solve the temporal variation of the system's response, while its spatial response is determined with the aid of the harmonic differential quadrature approach (HDQA). For more verification of the current work results and due to the lack of research in the field of the transient response of thermally induced vibrations of the panel, the results of the current work are verified with a Machine learning algorithm. Then, in the results section, some recommendations for enhancing the transient vibrations of the present concrete structure will be thoroughly examined.
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关键词
Thermodynamic response,Functionally graded doubly curved panel,Innovative frictional linear and torsional elastic,model,Innovative machine learning algorithm
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