Abstract
This paper studies aeroelastic flutter behaviors of hydrogen-functionalized graphene nanoplatelet-reinforced composite (HFGRC) beams. Displacements of the beams are described based on the first-order shear deformation theory (FSDT). Material properties of the HFGRCs are predicted by the micromechanics models which have been modified by machine learning (ML) assistance. Combined with Ritz trial functions, Hamilton’s principle is employed to derive the dynamic equations of the beams under supersonic airflow. The eigenvalue equation is derived and is numerically solved to get the flutter velocities. A detailed parametric study is conducted to investigate the effect of boundary conditions, GPL distribution pattern, temperature change, and hydrogenation percentage on the flutter behaviors of the beams.
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