Interlaminar shear behavior of basalt FRP and hybrid FRP laminates

Abstract

This paper focuses on the interlaminar shear behavior of basalt fiber reinforced polymer (FRP) laminates impregnated with epoxy and vinyl ester resins as well as hybrid basalt and carbon FRP laminates. Meanwhile, the interlaminar shear behavior of carbon and E-glass FRP laminates was also studied for comparison. The experiments were conducted according to the ASTM-D-2344 standard, and the failure modes, load–deformation (L–D) relationships, and interlaminar shear stress to normalized deformation relationships of various FRP laminates were analyzed. The differences in interlaminar shear behavior among different fibers and resins were identified. The fracture surfaces of the laminate specimens with different fibers were examined by scanning electron microscopy. Furthermore, the hybrid effect on interlaminar shear behavior was discussed and the interlaminar shear strength was predicted based on above analysis. The results show that the L–D relationships of FRP laminates can be classified into three types, which are determined by the interlaminar shear strength between fiber layers and the resin as well as by the failure modes. The interlaminar shear strength of basalt FRP with vinyl ester resin is higher than that of the glass FRP but less than that of the carbon FRP. The adoption of epoxy resin and the hybridization of basalt and carbon fibers can enhance the interlaminar shear strength of basalt FRP. In addition, the scanning electron microscopy images of fracture surfaces of the laminate specimens confirm the differences of interlaminar behavior of various composites. The hybrid effect on the interlaminar shear behavior is reflected in the integration of both advantages of basalt FRP and carbon FRP in the interlaminar shear stress to nominal deformation relationship, which results in both higher interlaminar shear strength at the cracking and the final stages. Finally, the interlaminar shear strength of different FRP laminates can be accurately predicted by the proposed model.