• Title/Summary/Keyword: R-CFST

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Study of the longitudinal reinforcement in reinforced concrete-filled steel tube short column subjected to axial loading

  • Alifujiang Xiamuxi;Caijian Liu;Alipujiang Jierula
    • Steel and Composite Structures
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    • v.47 no.6
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    • pp.709-728
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    • 2023
  • Experimental and analytical studies were conducted to clarify the influencing mechanisms of the longitudinal reinforcement on performance of axially loaded Reinforced Concrete-Filled Steel Tube (R-CFST) short columns. The longitudinal reinforcement ratio was set as parameter, and 10 R-CFST specimens with five different ratios and three Concrete-Filled Steel Tube (CFST) specimens for comparison were prepared and tested. Based on the test results, the failure modes, load transfer responses, peak load, stiffness, yield to strength ratio, ductility, fracture toughness, composite efficiency and stress state of steel tube were theoretically analyzed. To further examine, analytical investigations were then performed, material model for concrete core was proposed and verified against the test, and thereafter 36 model specimens with four different wall-thickness of steel tube, coupling with nine reinforcement ratios, were simulated. Finally, considering the experimental and analytical results, the prediction equations for ultimate load bearing capacity of R-CFSTs were modified from the equations of CFSTs given in codes, and a new equation which embeds the effect of reinforcement was proposed, and equations were validated against experimental data. The results indicate that longitudinal reinforcement significantly impacts the behavior of R-CFST as steel tube does; the proposed analytical model is effective and reasonable; proper ratios of longitudinal reinforcement enable the R-CFSTs obtain better balance between the performance and the construction cost, and the range for the proper ratios is recommended between 1.0% and 3.0%, regardless of wall-thickness of steel tube; the proposed equation is recommended for more accurate and stable prediction of the strength of R-CFSTs.

Improving the axial compression capacity prediction of elliptical CFST columns using a hybrid ANN-IP model

  • Tran, Viet-Linh;Jang, Yun;Kim, Seung-Eock
    • Steel and Composite Structures
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    • v.39 no.3
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    • pp.319-335
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    • 2021
  • This study proposes a new and highly-accurate artificial intelligence model, namely ANN-IP, which combines an interior-point (IP) algorithm and artificial neural network (ANN), to improve the axial compression capacity prediction of elliptical concrete-filled steel tubular (CFST) columns. For this purpose, 145 tests of elliptical CFST columns extracted from the literature are used to develop the ANN-IP model. In this regard, axial compression capacity is considered as a function of the column length, the major axis diameter, the minor axis diameter, the thickness of the steel tube, the yield strength of the steel tube, and the compressive strength of concrete. The performance of the ANN-IP model is compared with the ANN-LM model, which uses the robust Levenberg-Marquardt (LM) algorithm to train the ANN model. The comparative results show that the ANN-IP model obtains more magnificent precision (R2 = 0.983, RMSE = 59.963 kN, a20 - index = 0.979) than the ANN-LM model (R2 = 0.938, RMSE = 116.634 kN, a20 - index = 0.890). Finally, a new Graphical User Interface (GUI) tool is developed to use the ANN-IP model for the practical design. In conclusion, this study reveals that the proposed ANN-IP model can properly predict the axial compression capacity of elliptical CFST columns and eliminate the need for conducting costly experiments to some extent.

An artificial intelligence-based design model for circular CFST stub columns under axial load

  • Ipek, Suleyman;Erdogan, Aysegul;Guneyisi, Esra Mete
    • Steel and Composite Structures
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    • v.44 no.1
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    • pp.119-139
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    • 2022
  • This paper aims to use the artificial intelligence approach to develop a new model for predicting the ultimate axial strength of the circular concrete-filled steel tubular (CFST) stub columns. For this, the results of 314 experimentally tested circular CFST stub columns were employed in the generation of the design model. Since the influence of the column diameter, steel tube thickness, concrete compressive strength, steel tube yield strength, and column length on the ultimate axial strengths of columns were investigated in these experimental studies, here, in the development of the design model, these variables were taken into account as input parameters. The model was developed using the backpropagation algorithm named Bayesian Regularization. The accuracy, reliability, and consistency of the developed model were evaluated statistically, and also the design formulae given in the codes (EC4, ACI, AS, AIJ, and AISC) and the previous empirical formulations proposed by other researchers were used for the validation and comparison purposes. Based on this evaluation, it can be expressed that the developed design model has a strong and reliable prediction performance with a considerably high coefficient of determination (R-squared) value of 0.9994 and a low average percent error of 4.61. Besides, the sensitivity of the developed model was also monitored in terms of dimensional properties of columns and mechanical characteristics of materials. As a consequence, it can be stated that for the design of the ultimate axial capacity of the circular CFST stub columns, a novel artificial intelligence-based design model with a good and robust prediction performance was proposed herein.

Recycled aggregate concrete filled steel SHS beam-columns subjected to cyclic loading

  • Yang, You-Fu;Zhu, Lin-Tao
    • Steel and Composite Structures
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    • v.9 no.1
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    • pp.19-38
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    • 2009
  • The present paper provides test data to evaluate the seismic performance of recycled aggregate concrete (RAC) filled steel square hollow section (SHS) beam-columns. Fifteen specimens, including 12 RAC filled steel tubular (RACFST) columns and 3 reference conventional concrete filled steel tubular (CFST) columns, were tested under reversed cyclic flexural loading while subjected to constant axially compressive load. The test parameters include: (1) axial load level (n), from 0.05 to 0.47; and (2) recycled coarse aggregate replacement ratio (r), from 0 to 50%. It was found that, generally, the seismic performance of RACFST columns was similar to that of the reference conventional CFST columns, and RACFST columns exhibited high levels of bearing capacity and ductility. Comparisons are made with predicted RACFST beam-column bearing capacities and flexural stiffness using current design codes. A theoretical model for conventional CFST beam-columns is employed in this paper for square RACFST beam-columns. The predicted load versus deformation hysteretic curves are found to exhibit satisfactory agreement with test results.

Soft computing-based estimation of ultimate axial load of rectangular concrete-filled steel tubes

  • Asteris, Panagiotis G.;Lemonis, Minas E.;Nguyen, Thuy-Anh;Le, Hiep Van;Pham, Binh Thai
    • Steel and Composite Structures
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    • v.39 no.4
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    • pp.471-491
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    • 2021
  • In this study, we estimate the ultimate load of rectangular concrete-filled steel tubes (CFST) by developing a novel hybrid predictive model (ANN-BCMO) which is a combination of balancing composite motion optimization (BCMO) - a very new optimization technique and artificial neural network (ANN). For this aim, an experimental database consisting of 422 datasets is used for the development and validation of the ANN-BCMO model. Variables in the database are related with the geometrical characteristics of the structural members, and the mechanical properties of the constituent materials (steel and concrete). Validation of the hybrid ANN-BCMO model is carried out by applying standard statistical criteria such as root mean square error (RMSE), coefficient of determination (R2), and mean absolute error (MAE). In addition, the selection of appropriate values for parameters of the hybrid ANN-BCMO is conducted and its robustness is evaluated and compared with the conventional ANN techniques. The results reveal that the new hybrid ANN-BCMO model is a promising tool for prediction of the ultimate load of rectangular CFST, and prove the effective role of BCMO as a powerful algorithm in optimizing and improving the capability of the ANN predictor.

Shape effect on axially loaded CFDST columns

  • R, Manigandan;Kumar, Manoj
    • Steel and Composite Structures
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    • v.43 no.6
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    • pp.759-772
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    • 2022
  • Concrete-filled double skinned steel tubular (CFDST) columns have been used to construct modern structures such as tall buildings and bridges as well as infrastructures as they provide better, lesser weight, and greater stiffness in structural performance than conventional reinforced concrete or steel members. Different shapes of CFDST columns may be needed to satisfy the architectural and aesthetic criteria. In the study, three-dimensional FE simulations of circular and elliptical CFDST columns under axial compression were developed and verified through the experimental test data from the perspectives of full load-displacement histories, ultimate axial strengths, and failure modes. The verified FE models were used to investigate and compare the structural performance of CFDST columns with circular and elliptical cross-section shapes by evaluating the overall load-deformation curves, interaction stress-deformation responses, and composite actions of the column. At last, the accuracy of available design models in predicting the ultimate axial strengths of CFST columns were investigated. Research results showed that circular and elliptical CFDST column behaviors were generally similar. The overall structural performance of circular CFDST columns was relatively improved compared to the elliptical CFDST column.

Push-out resistance of concrete-filled spiral-welded mild-steel and stainless-steel tubes

  • Loke, Chi K.;Gunawardena, Yasoja K.R.;Aslani, Farhad;Uy, Brian
    • Steel and Composite Structures
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    • v.33 no.6
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    • pp.823-836
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    • 2019
  • Spiral welded tubes (SWTs) are fabricated by helically bending a steel plate and welding the resulting abutting edges. The cost-effectiveness of concrete-filled steel tube (CFST) columns can be enhanced by utilising such SWTs rather than the more conventional longitudinal seam welded tubes. Even though the steel-concrete interface bond strength of such concrete-filled spiral-welded steel tubes (CF-SWSTs) is an important consideration in relation to ensuring composite behaviour of such elements, especially at connections, it has not been investigated in detail to date. CF-SWSTs warrant separate consideration of their bond behaviour to CFSTs of other tube types due to the distinct weld seam geometry and fabrication induced surface imperfection patterns of SWTs. To address this research gap, axial push-out tests on forty CF-SWSTs were carried out where the effects of tube material, outside diameter (D), outside diameter to wall thickness (D/t), length of the steel-concrete interface (L) and concrete strength grade (f'c) were investigated. D, D/t and L/D values in the range 102-305 mm, 51-152.5 and 1.8-5.9 were considered while two nominal concrete grades, 20 MPa and 50 MPa, were used for the tests. The test results showed that the push-out bond strengths of CF-SWSTs of both mild-steel and stainless-steel were either similar to or greater than those of comparable CFSTs of other tube types. The bond strengths obtained experimentally for the tested CF-SWSTs, irrespective of the tube material type, were found to be well predicted by the guidelines contained in AISC-360.