In this study, nine simplified short composite columns consisting of core CFST (concrete filled steel tube) of different diameters and outer reinforced concrete were constructed to study their compressive performance ...In this study, nine simplified short composite columns consisting of core CFST (concrete filled steel tube) of different diameters and outer reinforced concrete were constructed to study their compressive performance under axial or eccentric compression. The failure mode is characterized by the crush of the outer concrete. The bearing capacity increases at first and then decreases with further increase of the position coefficient. It can be concluded that position coefficient is an important structural parameter that has considerable influences on the ultimate bearing capacity of the composite columns. The outer concrete, steel tubes and longitudinal reinforcement are found to work in a cooperative manner under axial or eccentric compression when the position coefficient is about 0.5. An improved bearing capacity algorithm that takes the position coefficient into account has been proposed based on the experimental and simulation results and current technical specification in China. It has been proven to be precise and safe.展开更多
Most of the previous research on concrete-filled steel tube is restricted to a deterministic approach. To gain clear insight into the random properties of circular concrete-filled steel tube, reliability analysis is c...Most of the previous research on concrete-filled steel tube is restricted to a deterministic approach. To gain clear insight into the random properties of circular concrete-filled steel tube, reliability analysis is carried out in the present study. To obtain the Structural nonlinear response and ultimate resistance capacity, material and geometrical nonlinear analysis of circular concrete-filled steel tube is performed with a three-dimensional degenerated beam ele- ment. Then we investigate the reliability of concrete-filled steel tube using the first-order reliability method combined with nonlinear finite element analysis. The influences of such parameters as material strength, slenderness, initial geo- metrical imperfection, etc. on the reliability of circular concrete-filled steel tube column are studied. It can be con- cluded that inevitable random fluctuation of those parameters has significant influence on structural reliability, and that stochastic or reliability methods can provide a more rational and subjective evaluation on the safety of CFT structures than a deterministic approach.展开更多
The application of artificial neural network to predict the ultimate bearing capacity of CFST （ concrete-filled square steel tubes） short columns under axial loading is explored. Input parameters consiste of concret...The application of artificial neural network to predict the ultimate bearing capacity of CFST （ concrete-filled square steel tubes） short columns under axial loading is explored. Input parameters consiste of concrete compressive strength, yield strength of steel tube, confinement index, sectional dimension and width-to-thickness ratio. The ultimate bearing capacity is the only output parameter. A multilayer feedforward neural network is used to describe the nonlinear relationships between the input and output variables. Fifty-five experimental data of CFST short columns under axial loading are used to train and test the neural network. A comparison between the neural network model and three parameter models shows that the neural network model possesses good accuracy and could be a practical method for predicting the ultimate strength of axially loaded CFST short columns.展开更多
基金Funded by the National Natural Science Foundation of China(Grant No. 51178119)
文摘In this study, nine simplified short composite columns consisting of core CFST (concrete filled steel tube) of different diameters and outer reinforced concrete were constructed to study their compressive performance under axial or eccentric compression. The failure mode is characterized by the crush of the outer concrete. The bearing capacity increases at first and then decreases with further increase of the position coefficient. It can be concluded that position coefficient is an important structural parameter that has considerable influences on the ultimate bearing capacity of the composite columns. The outer concrete, steel tubes and longitudinal reinforcement are found to work in a cooperative manner under axial or eccentric compression when the position coefficient is about 0.5. An improved bearing capacity algorithm that takes the position coefficient into account has been proposed based on the experimental and simulation results and current technical specification in China. It has been proven to be precise and safe.
基金supported by the Fundamental Research Funds for the Central Universities (SWJTU09CX012 and SWJTU11BR006)the Doctoral Fund for Youth Scholars of Ministry of Educationof China (No. 20110184120010)
文摘Most of the previous research on concrete-filled steel tube is restricted to a deterministic approach. To gain clear insight into the random properties of circular concrete-filled steel tube, reliability analysis is carried out in the present study. To obtain the Structural nonlinear response and ultimate resistance capacity, material and geometrical nonlinear analysis of circular concrete-filled steel tube is performed with a three-dimensional degenerated beam ele- ment. Then we investigate the reliability of concrete-filled steel tube using the first-order reliability method combined with nonlinear finite element analysis. The influences of such parameters as material strength, slenderness, initial geo- metrical imperfection, etc. on the reliability of circular concrete-filled steel tube column are studied. It can be con- cluded that inevitable random fluctuation of those parameters has significant influence on structural reliability, and that stochastic or reliability methods can provide a more rational and subjective evaluation on the safety of CFT structures than a deterministic approach.
文摘The application of artificial neural network to predict the ultimate bearing capacity of CFST （ concrete-filled square steel tubes） short columns under axial loading is explored. Input parameters consiste of concrete compressive strength, yield strength of steel tube, confinement index, sectional dimension and width-to-thickness ratio. The ultimate bearing capacity is the only output parameter. A multilayer feedforward neural network is used to describe the nonlinear relationships between the input and output variables. Fifty-five experimental data of CFST short columns under axial loading are used to train and test the neural network. A comparison between the neural network model and three parameter models shows that the neural network model possesses good accuracy and could be a practical method for predicting the ultimate strength of axially loaded CFST short columns.
