Graphene origami-enabled auxetic metamaterial tapered beams in fluid: Nonlinear vibration and postbuckling analyses via physics-embedded machine learning model

This paper presents a numerical study on nonlinear free vibration and postbuckling be-haviours of functionally graded (FG) graphene origami (GOri)-enabled auxetic metamate-rial (GOEAM) tapered beams immersed in fluid, with a particular focus on the effect of negative Poisson's ratio (NPR) on the nonlinear frequencies and postbuckling equilibrium paths. The metamaterial properties of the novel GOEAM are determined by a physics -embedded machine learning based micromechanics model. The beam deformation is gov-erned by Timoshenko beam theory and von Karman nonlinearity, and the governing equa-tions are solved using the differential quadrature method (DQM). The fluid pressure ex-erted on the surface of the beam is calculated using the velocity potential function and Bernoulli's equation. Comprehensive parametric studies demonstrate that due to the use of GOri reinforcement, an FG-GOEAM beam with NPR outperforms its metallic counterpart with considerably increased nonlinear fundamental frequency and enhanced postbuckling resistance. The nonlinear free vibration and postbuckling behaviours of the beams can be effectively tuned through GOri parameters.& COPY; 2023 Elsevier Inc. All rights reserved.