• Steel and Composite Structures
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• v.27 no.1
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• pp.75-87
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• 2018

This paper presents a new method to compute the shear strength of composited structural B-C-W members. These B-C-W members, defined as concrete-filled steel box beams, columns and shear walls, consist of a slender rectangular steel plate box filled with concrete and inserted steel plates connecting the two long-side steel plates. These structural elements are intended to be used in structural members of super-tall buildings and nuclear safety-related structures. The concrete confined by the steel plate acts to be in a multi-axial stressed state: therefore, its shear strength was calculated on the basis of a concrete's failure criterion model. The shear strength of the steel plates on the long sides of the structural element was computed using the von Mises plastic strength theory without taking into account the buckling of the steel plate. The spacing and strength of the inserted plates to induce plate yielding before buckling was determined using elastic plate theory. Therefore, a predictive method to compute the shear strength of composited structural B-C-W members without considering the shear span ratio was obtained. A coefficient considering the influence of the shear span ratio was introduced into the formula to compute the anti-lateral bearing capacity of composited structural B-C-W members. Comparisons were made between the numerical results and the test results along with this method to predict the anti-lateral bearing capacity of concrete-filled steel box walls. Nonlinear static analysis of concrete-filled steel box walls was also conducted by using ABAQUS and the results agreed well with the experimental data.

• Computers and Concrete
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• v.2 no.1
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• pp.79-96
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• 2005

The use of high-strength concrete (HSC) has significantly increased over the last decade, especially in offshore structures, long-span bridges, and tall buildings. The behavior of such concrete is noticeably different from that of normal-strength concrete (NSC) due to its different microstructure and mode of failure. In particular, the shear capacity of structural members made of HSC is a concern and must be carefully evaluated. The shear fracture surface in HSC members is usually trans-granular (propagates across coarse aggregates) and is therefore smoother than that in NSC members, which reduces the effect of shear transfer mechanisms through aggregate interlock across cracks, thus reducing the ultimate shear strength. Current code provisions for shear design are mainly based on experimental results obtained on NSC members having compressive strength of up to 50MPa. The validity of such methods to calculate the shear strength of HSC members is still questionable. In this study, a new approach based on artificial neural networks (ANNs) was used to predict the shear capacity of NSC and HSC beams without shear reinforcement. Shear capacities predicted by the ANN model were compared to those of five other methods commonly used in shear investigations: the ACI method, the CSA simplified method, Response 2000, Eurocode-2, and Zsutty's method. A sensitivity analysis was conducted to evaluate the ability of ANNs to capture the effect of main shear design parameters (concrete compressive strength, amount of longitudinal reinforcement, beam size, and shear span to depth ratio) on the shear capacity of reinforced NSC and HSC beams. It was found that the ANN model outperformed all other considered methods, providing more accurate results of shear capacity, and better capturing the effect of basic shear design parameters. Therefore, it offers an efficient alternative to evaluate the shear capacity of NSC and HSC members without stirrups.