Finite element modeling of piezoresistivity in graphene coated glass fiber reinforced polymer composites

Multifunctional materials with high electrical sensitivity, such as graphene, have been widely explored through experimental and computational methods for structural health monitoring (SHM) of composite materials. However, most computational approaches operate at the microscale and require interfacial properties, making them computationally expensive. This study presents a novel computational approach for modeling the electrical response of graphene sensors embedded in fiber-reinforced polymer composites using finite element modeling (FEM) at the macroscale. Moreover, graphene fabric sheets have not been considered in the computational study of laminated composites, a gap that this study aims to address. Validation studies are conducted using ABAQUS®, where a graphene sheet is coated on a glass fiber-reinforced polymer (GFRP) composite. Simulations are performed under loading at strain rates of 0.2 mm/min, 2 mm/min, and 20 mm/min. The corresponding electrical responses, coupled with mechanical responses, are obtained using the User VARiables for Mapping (UVARM) subroutine. The simulation results show good agreement with experiments in terms of the root mean square error (RMSE) metric. Values of 3.574, 0.889, and 1.31 in fractional change in resistance (FCR) at the respective strain rates demonstrate strong correlation. The study is further extended by embedding the graphene sensor in unidirectional GFRP with fiber orientations of [0^∘]4s, [90^∘]4s, and [0^∘,45^∘,−45^∘,90^∘]_s. The FCRs at damage are 29%, 15%, and 30%, respectively, indicating that a specific level of FCR can signify deformation and failure in the structure. This study offers valuable insights for advancing macroscale FEM of piezoresistivity in sensors embedded within composite laminates.