Flexural improvement of reinforced concrete beams strengthened with self-prestressing shape memory alloys
Auteur(s): |
Ahmed Alkhairo
Nazar Oukaili Riadh Al-Mahaidi |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Advances in Structural Engineering, 11 décembre 2023, n. 2, v. 27 |
Page(s): | 195-214 |
DOI: | 10.1177/13694332231216302 |
Abstrait: |
The study reported here aims to investigate the application of shape memory alloys (SMAs) in the form of strips for strengthening cracked reinforced concrete (RC) beams. The study proposes an innovative technique for prestressing RC beams by utilizing the shape recovery property of the alloy. Nine full-scale RC beams with a length of 3.75 m and a cross-section of 200 mm × 300 mm were categorized into three groups based on the steel reinforcement ratio, and tested under static loading. Three RC beams were used as control specimens and the other six were retrofitted with either one layer or two layers of SMA strips. The beams to be strengthened were exposed to an initial applied load before the installation of the SMA strip to simulate the deterioration scenario. SMA strips were retrofitted on the soffits of the deteriorated beams and activated by applying temperature from an external heat source while the temperature-deflection-strain measurements were monitored. Specimens were tested again up to failure to evaluate the strength improvement of the retrofitted specimens. Beams retrofitted with one layer of SMA experienced a deflection recovery up to 2.3 mm upon activation and an additional service load of up to 62%, whereas beams retrofitted with two layers experienced a deflection recovery up to 2.8 mm and an additional service load of up to 95%. In general, the deflection recovery was proportional to the ratio of the total reinforcement ratio after strengthening to the initial reinforcement ratio before strengthening. Therefore, tested specimens with two SMA layers experienced less improvement than specimens with one SMA layer. Finally, the experimental results were evaluated with two analytical methods: ACI method and the non-linear sectional analysis proposed by Oukaili. |
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14.01.2024