Prediction of Axial Capacity of Concrete-Filled Square Steel Tubes Using Neural Networks

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.

A new calculation method for axial load capacity of separated concrete-filled steel tubes based on limit equilibrium theory

A new calculation method for axial load capacity of separated concrete-filled steel tubes based on limit equilibrium theory was proposed,which took into account the decrease of confinement effect by steel tube and the non-uniform distribution of ultimate stress in cored concrete.The accuracy of the analytical result is validated through running the numerical result by finite element method (FEM) and experimental data as well.The influences of the key parameters on the load capacity of the concrete-filled steel tube (CFST) was studied,including the separation ratio,concrete compressive strength,and steel strength.The results indicate that the load capacity of the tube increases with concrete strength and steel strength under the separation ratio less than 4%,while decreases with a higher separation ratio improved.

Axial bearing behavior of super-long piles in deep soft clay over stiff layers

In order to find out the bearing behavior of super-long piles located in deep soft clay over stiff layers around Dongting Lake, China, a test pile was first designed with the field loading test finished afterward. Based on the measured test results, load transfer mechanism and bearing behavior of the pile shaft were discussed in detail. Then, by introducing a bi-linear model for shaft friction and the tri-linear model for pile tip resistance, respectively, the governing differential equation of pile soil system was set up by the load transfer method with the analytical solutions derived as well, taking into account the effect by stratified feature and various bearing conditions of subsoil, material nonlinearity, and the sediment under pile tip. Furthermore, formulas to determine the axial capacity of super-long piles by the pile top settlement were advised and applied to analyze the test pile. Good agreement between the predicted load settlement variations and the measured data is obtained to verify the validity of the present method. The results also show that, the axial bearing capacity of super-long piles should be controlled by the allowable pile top settlement, and buckling stability of the pile shaft should be paid attention as well.

Axial compression physical testing of traditional and bird beak SHS T-joints

The static tests of nine traditional and bird beak square hollow structure(SHS) T-joints with different β values and connection types under axial compression at brace end were carried out. Experimental test schemes, failure modes of specimens, jack load-vertical displacement curves, jack load-deformation of chord and strain intensity distribution curves of joints were presented. The effects of β and connection types on axial compression property of joints were studied. The results show that the ultimate axial compression capacity of common bird beak SHS T-joints and diamond bird beak SHS T-joints is larger than that of traditional SHS T-joint specimens with big values of β. The ultimate axial compression capacity of diamond bird beak SHS T-joints is larger than that of common bird beak SHS T-joints. As β increases, the increase of the ultimate axial compression capacity of diamond bird beak SHS T-joints over that of common bird beak joints grows. The ultimate axial compression capacity and the initial axial stiffness of all kinds of joints increase as β increases, and the initial axial stiffness of the diamond bird beak SHS T-joints is the largest. The ductilities of common bird beak and diamond bird beak SHS T-joints increase as β increases, but the ductility of the traditional SHS T-joints decreases as β increases.

Joint member angle limits of composite beams and CFT square columns

This work aims to understand the relationship between the member angle limit and the energy ratio for 24 test samples of composite beams and CFT square steel tube columns. This work also compares the formula applicability for member angle limit with the previous test result to provide the basic data for the design of composite beam-CFT column. The evaluation of the member angle limit was performed with concrete compressive strength (fC =22.16 MPa, 30.49 MPa), breadth-to-thickness ratio (B/t=25.0, 33.3, 43.5), and axial capacity ratio (N/N0=0, 0.3, 0.4, 0.5) as the main variables of the test samples. For the relationship between the member angle limit (Ru) and the energy ratio (ES/EC ), the test result shows that the energy ratio becomes lower as the axial capacity ratio and the breadth-to-thickness ratio increase. The energy ratio is lower for the Type B test sample compared with that of Types A and C. For the formula suggested by SATO, the test samples are distributed evenly for comparison between test values and the member angle limit; however, other formulas indicate a deviation. Specifically, for the comparison between R u,cal and R u (Test), Maeda's formula shows severe deviation.

Research on axial bearing capacity of rectangular concrete-filled steel tubular columns based on artificial neural networks

Design of rectangular concrete-filled steel tubular （CFT） columns has been a big concern owing to their complex constraint mechanism. Generally, most existing methods are based on simplified mechanical model with limited experimental data, which is not reliable under many conditions, e.g., columns using high strength materials. Artificial neural network （ANN） models have shown the effectiveness to solve complex problems in many areas of civil engineering in recent years. In this paper, ANN models were employed to predict the axial bearing capacity of rectangular CFT columns based on the experimental data. 305 experimental data from articles were collected, and 275 experimental samples were chosen to train the ANN models while 30 experimental samples were used for testing. Based on the comparison among different models, artificial neural network modell （ANN1） and artificial neural network model2 （ANN2） with a 20- neuron hidden layer were chosen as the fit prediction models. ANN1 has five inputs： the length （D） and width （B） of cross section, the thickness of steel （t）, the yield strength of steel （fy）, the cylinder strength of concrete （fc＇）- ANN2 has ten inputs： D, B, t, fy, f′, the length to width ratio （D/B）, the length to thickness ratio （D/t）, the width to thickness ratio （B/t）, restraint coefficient （ξ）, the steel ratio （α）. The axial beating capacity is the output data for both models.The outputs from ANN1 and ANN2 were verified and compared with those from EC4, ACI, GJB4142 and AISC360-10. The results show that the implemented models have good prediction and generalization capacity. Parametric study was conducted using ANN1 and ANN2 which indicates that effect law of basic parameters of columns on the axial bearing capacity of rectangular CFT columns differs from design codes.The results also provide convincing design reference to rectangular CFT columns.

A LDA STUDY OF THE TURBULENT FLOW FIELD IN A BAFFLED VESSEL GENERATED BY A PTD AND A PTU

The flow fields in fully baffled, cylindrical vessels of 250 and 360 mm diameter respectively, with a series of downflow pitched turbines (PTD) and upflow pitched turbines (PTU) have been measured using the two component LDA. The flow fields of the PTD and PTU are substantially more complex than the conventional patterns reported previously. Instead of a single circulation loop, the present results show that a primary circulation loop does not reach the bottom of the tank for an impeller clearance of the T/2, but it is accompanied by a secondary circulation loop. However, when the diameter of the impeller decrease from T/2 to T/3, the secondary circulation loop disappear. The distribution of axial pumping capacity is also provided.

Test and damage assessment of shallow buried RC tunnel under explosion

As a major element of the transportation network,tunnels are unavoidably threatened by accidental loads such as vehicle bombs and tank truck explosions.The goal of this research is to explore the dynamic characteristics and damage assessment of tunnel structures under contact blast loads.First,three scaled-down reinforced concrete tunnel models were made,and the explosion test and static loading test were carried out successively to evaluate the axial residual bearing capacity,axial displacement and failure mechanism of the tunnel.Secondly,the finite element model is built by utilizing LS-DYNA,and the reliability of the finite element method is confirmed by comparing the data of the explosion test with the static loading test.At the same time,the calculation method for damage coefficient and the classification criteria for damage grade based on axial residual bearing capacity are presented.Then,based on the finite element method,the propagation process of the explosion shock wave in the tunnel and the damage mechanism of the tunnel are investigated.Finally,seven explosion scenarios are developed,the damage degree of these seven tunnels under the blast load is quantitatively analyzed,and further anti-blast design ideas are put forth.The study in this article may give an intended reference for the damage assessment,anti-explosion design and strengthening work of reinforced concrete tunnels.