Three-dimensional finite element model for FRP-confined circular concrete cylinders under axial compression

This paper presents a 3D FE model for FRP-confined circular concrete cylinders based on a plastic-damage constitutive model for concrete recently proposed by Yu et al. (2010b). This 3D model is capable of modeling deformation non-uniformity in the axial direction due to factors such as end restraints. Numerical results obtained using the FE model for FRP-confined cylinders with end restraints or with a vertical gap in the FRP jacket conform to expected trends although their quantitative accuracy awaits confirmation by laboratory tests. This FE model has the potential for extension to more general cases of FRP-confined concrete columns (e.g. rectangular concrete columns) and can provide a useful tool for the exploration of confinement mechanisms in the development of simple stress-strain models for design use

Numerical Calibration of a Simplified Model for FRP Confinement of Columns

This paper presents the calibration of a simplified analytical model for concrete columns confined by fiber reinforced polymer (FRP) jackets. The model allows evaluating the increase of strength, ductility and dissipated energy without defining the lateral confinement pressure and it can be easily extended for the assessment of FRP confinement in design applications. This model was obtained by a simplified procedure based on the best fit of experimental data available in the literature and the coefficient of determination (R2) was evaluated in order to estimate the accuracy of the regression analysis. A numerical database resulting from finite element (FE) analyses was compiled and reported for integrating the model\u2019s calibration obtained by the few experimental data. The FE models are built based on results of experimental tests available in the literature and several FE simulations are carried out. The experimental results are then integrated with numerical results and new forms of the simplified expressions are obtained by new best fit. The new values of R2 confirm an improvement of the accuracy of the regression analysis. Finally, the performance of the simplified model is compared with existing formulas available in the literature