Non-destructive strength prediction of composite laminates utilizing deep learning and the stochastic finite element methods

A hybrid methodology based on numerical and non-destructive experimental schemes, which is able to predict the structural level strength of composite laminates is proposed on the current work. The main objective is to predict the strength by substituting the up to failure experiments with non-destructive experiments where the investigated...

Probabilistic failure analysis of quasi-isotropic CFRP structures utilizing the stochastic finite element and the Karhunen–Loève expansion methods

The accuracy of structural analysis in composite structures depends on the proper estimation of the uncertainties mainly related to the mechanical properties of the constituent materials. On this basis, a sophisticated numerical tool is proposed, able to perform stochastic finite element analysis on composite structures with material...

Carbon fiber-reinforced polymer pultrusions adhesively bonded inside aluminum joints: experimental and numerical study

In the context of lightweight structure design for the transportation and robotics industries, new types of composite structures are being developed, in the form of trusses made of fiber-reinforced polymer composite members of small diameter. The main objective of this work is to study adhesive joints, bonding pultruded composite tubes inside...

Comparative study of adhesive joint designs for composite trusses based on numerical models

In the context of lightweight structure design for the transportation and robotics industries, new types of composite structures are being developed, in the form of trusses made of fiber-reinforced polymer composite members of small diameter (a few millimeters thick at most). Some concepts of wound trusses can be found in the literature, but...