Finite Element Analysis of Reinforced Concrete Beams Prestressed by Fe-Based Shape Memory Alloy Bars
Prestressing of concrete structures using Fe-based shape memory alloys has been investigated extensively by experiments in the last decade. However, detailed investigations on the stress produced by the Fe-based shape memory alloys and its influence on concrete damage during deformation of concrete...
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Veröffentlicht in: | Applied sciences 2022-04, Vol.12 (7), p.3255 |
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Sprache: | eng |
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Zusammenfassung: | Prestressing of concrete structures using Fe-based shape memory alloys has been investigated extensively by experiments in the last decade. However, detailed investigations on the stress produced by the Fe-based shape memory alloys and its influence on concrete damage during deformation of concrete structure has not been investigated yet. In this study, the prestressing effect by Fe-based shape memory alloy bars on bending behavior of reinforced concrete beam was investigated numerically. A finite element simulation model was developed to investigated the bending responses of the beams including nonlinear material properties such as concrete cracking and crushing as well as the plastic deformation of the Fe-based shape memory alloy. The model is able to capture the bending behavior of the beam prestressed with the Fe-based shape memory alloy bars. Based on the numerical and experimental results, the prestressing effect by the shape memory alloy bars was investigated in detail. Although the developed model slightly overestimated the experimentally obtained bending load-deflection curves of the concrete beams, it was shown that the developed model can be used for an optimization study to select the best possible design parameters for prestressing the concrete beam with the Fe-based shape memory alloy bars. A possible reason for the overestimation is the idealized perfect bonding assumption between Fe-SMA and concrete used in the model, while slip at the interface occurred in the experiments. |
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ISSN: | 2076-3417 2076-3417 |
DOI: | 10.3390/app12073255 |