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Thick-shell finite element analysis of reinforced concrete flat plates with non-uniform connection stresses
Abstract This paper presents the application of a thick-shell nonlinear finite element analysis procedure to estimate the punching shear resisting performance of reinforced concrete slab-column connections under variable connection shear stress conditions. In the analyses performed, varied connection shear stress conditions stem from slabs being supported by columns with different cross-section aspect ratios, being subjected to different distributions of gravity loading, being constructed with different planar reinforcement ratios in orthogonal directions, as well as the application of unbalanced bending moments. Forty-eight isolated slab-column connection specimens presented in the literature were modelled and analyzed using a thick-shell finite analysis procedure. All numerical results were developed using a predefined set of material models and analysis parameters, a consistent meshing procedure, and are shown to provide meaningful agreement with experimental data without the need for case-specific model calibration or the adoption of specialised failure criteria. The results show that thick-shell modelling methods can be suitable for estimating the punching shear response of slabs subjected to non-uniform shear stress development in connection regions, and can provide similar levels of precision to that obtained for the analysis of idealised slab-column connections typically used for design procedure and model development.
Highlights Low-cost shell FEA for punching shear assessment of reinforced concrete flat plates. Analysis of 45 non-idealised connection specimens representative of real-world construction. Good agreement between FEA simulations and reported results without model calibration. Result accuracy comparable to that obtained for more typical idealised connection specimens.
Thick-shell finite element analysis of reinforced concrete flat plates with non-uniform connection stresses
Abstract This paper presents the application of a thick-shell nonlinear finite element analysis procedure to estimate the punching shear resisting performance of reinforced concrete slab-column connections under variable connection shear stress conditions. In the analyses performed, varied connection shear stress conditions stem from slabs being supported by columns with different cross-section aspect ratios, being subjected to different distributions of gravity loading, being constructed with different planar reinforcement ratios in orthogonal directions, as well as the application of unbalanced bending moments. Forty-eight isolated slab-column connection specimens presented in the literature were modelled and analyzed using a thick-shell finite analysis procedure. All numerical results were developed using a predefined set of material models and analysis parameters, a consistent meshing procedure, and are shown to provide meaningful agreement with experimental data without the need for case-specific model calibration or the adoption of specialised failure criteria. The results show that thick-shell modelling methods can be suitable for estimating the punching shear response of slabs subjected to non-uniform shear stress development in connection regions, and can provide similar levels of precision to that obtained for the analysis of idealised slab-column connections typically used for design procedure and model development.
Highlights Low-cost shell FEA for punching shear assessment of reinforced concrete flat plates. Analysis of 45 non-idealised connection specimens representative of real-world construction. Good agreement between FEA simulations and reported results without model calibration. Result accuracy comparable to that obtained for more typical idealised connection specimens.
Thick-shell finite element analysis of reinforced concrete flat plates with non-uniform connection stresses
Abolhelm, Reza (author) / Hrynyk, Trevor D. (author)
Engineering Structures ; 304
2024-02-07
Article (Journal)
Electronic Resource
English
Elsevier | 2024
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