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One important application of fiber reinforced polymer (FRP) is to confine concrete as FRP jackets in seismic retrofit process

of reinforced concrete structures. Confinement can improve concrete properties such as compressive strength and ultimate axial

strain. For the safe and economic design of FRP jackets, the stress-strain behavior of FRP-confined concrete under monotonic

and cyclic compression needs to be properly understood and modeled. According to literature review, it has been realized that

although there are many studies on the monotonic compressive loading of FRP-confined concrete, only a few studies have been

conducted on the cyclic compressive loading. Therefore, this study is aimed at investigating the behavior of FRP-confined

concrete under cyclic compressive loading. A total of 18 cylindrical specimens of FRP-confined concretewere tested in uniaxial

compressive loading with different wrap thickness, and loading patterns. The results obtained from the tests are presented and

examined based on analysis of test results predictive equations for plastic strain and stress deterioration were derived. The

results are also compared with those from two current models,comparison revealed the lack of sufficient accuracy of the current

models to predict stress-strain behavior and accordingly some provisions should be incorporated.

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An analytical nonlinear stress-strain model and a microscopic damage index for confined and unconfined concretes together with a macroscopic damage index for reinforced concrete (RC) structures under cyclic loading are proposed. In order to eliminate the problem of scale effect, an adjustable finite element computer program was generated to simulate RC structures subjected to cyclic loading. By comparing the simulated and experimental results of tests on the full-scale structural members and concrete cylindrical samples, the proposed stress-strain model for confined and unconfined concretes under cyclic loading was accordingly modified and then validated. The proposed model has a strong mathematical structure and can readily be adapted to achieve a higher degree of precision by modifying the relevant coefficients based on more precise tests. To apply the proposed damage indices at the microscopic and macroscopic levels, respectively, stress-strain data of finite elements (confined and unconfined concrete elements) and moment-curvature data of critical section are employed. The proposed microscopic damage index can easily be calculated by using the proposed simple analytic nonlinear stress-strain model for confined and unconfined concretes. The proposed macroscopic damage index is based on the evaluation of nonlinear local degradation of materials and taking into account the pseudo-plastic hinge produced in the critical section of the structural element. One of the advantages of the macroscopic damage index is that the moment-curvature data of the critical section is sufficient in itself and there is no need to obtain the force-displacement data of the structural member.

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Concrete filled steel tube is constructed using various tube shapes to obtain most efficient properties of concrete core and steel tube. The compressive strength of concrete is considerably increased by the lateral confined steel tube in circular concrete filled steel tube (CCFT). The aim of this study was to present an integrated approach for predicting the steel-confined compressive strength of concrete in CCFT columns under axial loading based on large number of experimental data using artificial neural networks. Neural networks process information in a similar way the human brain does. Neural networks learn by example. The main parameters investigated in this study include the compressive strength of unconfined concrete (f'c), outer diameter (D) and length (L) of column, wall thickness (t) and tensile yield stress (fy) of steel tube. Subsequently, using the reliable network, empirical equations are developed for the confinement effect. The results of proposed model are compared with recently existing model on the basis of the experimental results. The findings demonstrate the precision and applicability of the empirical approach to determine capacity of CCFT columns.