Experimental Investigation and Failure Analysis of Fastened GRP under Bending Using Finite Element Method and Artificial Neural Networks

This paper presents a novel approach that predicts the strength and failure modes of jointed Glass Reinforced Polyester (GRP) samples under bending using Finite Element Method (FEM) and Artificial Neural Network (ANN). The mechanical behavior of fastened glass fiber reinforced plastics composites under bending have been experimentally investigated. Samples were obtained from Amiantit Oman, a manufacturing company operating in Russail Industrial Zone in the Sultanate of Oman. The experimental program involved the conduct of three point bending tests as well as bending tests of mechanically fastened joints under static loads. The experimental results showed that the dimensions of the specimen such as the bending span length, specimen width, and specimen pitch affect GRP strength and stiffness. FEM and ANN results predicted accurately the types of failure modes and their locations along the specimens and compared well with the experimental results