Behavior of circular concrete columns reinforced with hollow composite sections and GFRP bars

Alajarmeh, Omar; Manalo, Allan; Benmokrane, Brahim; Mohammed, Ali A.; Abousnina, Rajab; Elchalakani, Mohamed; Edoo, Azam

doi:10.1016/j.marstruc.2020.102785

Cited by 25 publications

(10 citation statements)

References 24 publications

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“…It is noted that the contribution of longitudinal FRP bars in compression and lateral confining pressure play significant role in the accurate predictions of these empirical models. [66][67][68] Hadi et al 69 proposed Equation (1) to predict the axial load-carrying capacities of FRP-RC circular concrete columns.…”

Section: Empirical Modelingmentioning

confidence: 99%

Neural network‐based models versus empirical models for the prediction of axial load‐carrying capacities of FRP‐reinforced circular concrete columns

Ali,

Ahmad,

Iqbal

et al. 2023

Structural Concrete

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This study presents new neural‐network (NN)‐based models to predict the axial load‐carrying capacities of fiber‐reinforced polymer (FRP) bar reinforced‐concrete (RC) circular columns. A database of FRP‐reinforced concrete (RC) circular columns having outside diameter and height ranged between 160–305 and 640–2500 mm, respectively was established from the literature. The axial load‐carrying capacities of FRP‐RC columns were first predicted using the empirical models developed in the literature and then predicted using deep neural‐network (DNN) and convolutional neural‐network (CNN)‐based models. The developed DNN and CNN models were calibrated using various neurons integrated in the hidden layers for the accurate predictions. Based on the results, the proposed DNN and CNN models accurately predicted the axial load‐carrying capacities of FRP‐RC circular columns with R2 = 0.943 and R2 = 0.936, respectively. Further, a comparative analysis showed that the proposed DNN and CNN models are more accurate than the empirical models with 52% and 42% reduction in mean absolute percentage error (MAPE) and root mean square error (RMSE), respectively involved in the empirical models. Moreover, within NN‐based prediction models, the prediction accuracy of DNN model is comparatively higher than the CNN model due to the integration of neurons in each layer (9‐64‐64‐64‐64‐1) and embedded rectified linear unit (ReLu) activation function. Overall, the proposed DNN and CNN models can be utilized as paramount in the future studies.

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Section: Empirical Modelingmentioning

confidence: 99%

Neural network‐based models versus empirical models for the prediction of axial load‐carrying capacities of FRP‐reinforced circular concrete columns

Ali,

Ahmad,

Iqbal

et al. 2023

Structural Concrete

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“…The accuracy of the stress-strain model can be judged by comparing the predicted curves with the test curves. The specific operation is to substitute the theoretical values of peak stress f cc , peak strain ε cc , ultimate stress f cu and ultimate strain ε cu of confined concrete columns into Equations (10) and (11) to determine the values of parameters a and c, thus obtaining the predicted stress-strain relationship curves of confined concrete column specimens in this database. Figure 14 compares the model prediction curve with the actual test curve of partially stirrup-only confined concrete columns studied by this test and others in the database.…”

Section: Model Performancementioning

confidence: 99%

“…In addition, FRP can also be made into FRP reinforcement with superior environmental and mechanical properties to replace ordinary reinforcement. For example, Omar Alajarmeh et al [11] studied the behaviour of circular concrete columns reinforced with hollow composite sections and GFRP bars. However, because FRPs still have the disadvantages of brittle failure and a high cost, which greatly limit its application, the application of FRP-confined concrete structure is still limited.…”

Section: Introductionmentioning

confidence: 99%

Influence of the Cross-Sectional Shape and Corner Radius on the Compressive Behaviour of Concrete Columns Confined by FRP and Stirrups

Wei

Wang

et al. 2022

Polymers

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Axial compression tests were carried out on 72 FRP (fiber reinforced polymer)–stirrup composite−confined concrete columns. Stirrups ensure the residual bearing capacity and ductility after the FRP fractures. To reduce the effect of stress concentration at the corners of the confined square−section concrete columns and improve the restraint effect, an FRP–stirrup composite−confined concrete structure with rounded corners is proposed. Different corner radii of the stirrup and outer FRP were designed, and the corner radius of the stirrup was adjusted accurately to meet the designed corner radius of the outer FRP. The cross−section of the specimens gradually changed from square to circular as the corner radius increased. The influence of the cross−sectional shape and corner radius on the compressive behaviour of FRP–stirrup composite−confined concrete was analysed. An increase in the corner radius can cause the strain distribution of the FRP to be more uniform and strengthen the restraint effect. The larger the corner radius of the specimen, the better the improvement of mechanical properties. The strength of the circular section specimen was greatly improved. In addition, the test parameters also included the FRP layers, FRP types and stirrup spacing. With the same corner radius, increasing the number of FRP layers or densifying the stirrup spacing effectively improved the mechanical properties of the specimens. Finally, a database of FRP–stirrup composite−confined concrete column test results with different corner radii was established. The general calculation models were proposed, respectively, for the peak points, ultimate points and stress–strain models that are applicable to FRP−, stirrup− and FRP–stirrup−confined concrete columns with different cross−sectional shapes under axial compression.

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“…To solve the problem of performance degradation of a concrete column caused by steel corrosion, some restrained concrete columns with FRP tubes or FRP sheets have been developed [ 7 , 8 ]. In addition, the use of FRP bars and stirrups instead of steel materials in concrete columns has been encouraged [ 9 ]; for example, glass-GFRP (GFRP) bars and spiral stirrups have been applied in piers and piles.…”

Section: Introductionmentioning

confidence: 99%

Study on Shear Behaviors and Damage Assessment of Circular Concrete Short Columns Reinforced with GFRP Bars and Spiral Stirrups

et al. 2023

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This study investigated the shear resistance and damage evolution of glass fiber-reinforced polymer (GFRP)-reinforced concrete short columns. Five circular concrete short columns reinforced with GFRP bars and spiral stirrups were fabricated and tested under lateral thrust in the laboratory. The test variables involved the stirrup reinforcement ratio, the longitudinal reinforcement ratio and the type of stirrups. The failure modes, load-displacement curves, strain responses and crack characteristics of these columns were documented and discussed. The accuracy of shear design equations in predicting shear capacity of such columns was evaluated. In addition, the digital image correlation (DIC) instrument was used to identify the full-field strain and damage zones of circular concrete short columns. Several smart aggregate (SA) transducers coupled to the surface of these columns were used to monitor its damage status. The energy ratio index (ERI) and the damage index based on smart aggregate were established to characterize damage level of such columns. The test results indicate that the shear capacity is improved 5.6% and 31.1% and the lateral ultimate displacement is increased 67.7% and 400% as the stirrup reinforcement ratio of the concrete short column is increased from 0 to 0.19% and 0.47%, respectively. The shear capacity equation proposed by Ali and his co-workers, considering a strain limit of , gives accurate predictions of the shear capacity of circular concrete short columns reinforced with GFRP bars and spiral stirrups. The variation in ERI values is explained by the development of damage zones of the column obtained with DIC technology and with the proposed damage index based on the smart aggregate it is feasible to evaluate the damage level of circular short concrete columns.

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Behavior of circular concrete columns reinforced with hollow composite sections and GFRP bars

Cited by 25 publications

References 24 publications

Neural network‐based models versus empirical models for the prediction of axial load‐carrying capacities of FRP‐reinforced circular concrete columns

Neural network‐based models versus empirical models for the prediction of axial load‐carrying capacities of FRP‐reinforced circular concrete columns

Influence of the Cross-Sectional Shape and Corner Radius on the Compressive Behaviour of Concrete Columns Confined by FRP and Stirrups

Study on Shear Behaviors and Damage Assessment of Circular Concrete Short Columns Reinforced with GFRP Bars and Spiral Stirrups

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