Treed gaussian process for manufacturing imperfection identification of pultruded GFRP thin-walled profile

The process of manufacturing pultruded FRP (Fiber Reinforced Polymers) profiles involves unavoidable imperfections that affect their structural performances. This is is even more relevant for the stability of axially loaded slender elements, due to the importance of imperfections and notches to initiate the buckling phenomenon. Thus, they become a predominant factor for the design of lightweight FRP beam-like structures. A Bayesian approach is proposed to estimate the presence and location of manufacturing imperfections in pultruded GFRPs (Glass Fiber Reinforced Polymers) profiles. Specifically, the Treed Gaussian Process (TGP) procedure is applied. This approach combines regression Gaussian Processes (GP) and Bayesian-based Recursive Partitioning. The experimental and numerical modal shapes of wide flange pultruded profile were investigated. The experimental data were compared with the numerical results of several Finite Element Models (FEM) characterised by different crack sizes.