Research on the Theoretical Models of FRP-Confined Gangue Aggregate Concrete Partially Filled Steel Tube Columns
Autor(en): |
Jian Wang
Junwu Xia Chuanzhi Sun Jinsheng Cheng Shengbo Zhou Jibing Deng |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Buildings, 22 Oktober 2024, n. 11, v. 14 |
Seite(n): | 3516 |
DOI: | 10.3390/buildings14113516 |
Abstrakt: |
FRP-confined gangue aggregate concrete partially filled steel tubes (CGCPFTs) can not only effectively enhance the performance of coal gangue concrete, but also fully exploit the elastic-plastic mechanical behavior of the steel tubes. However, research on theoretical models that can describe their mechanical properties is yet to be conducted. To fill this gap, theoretical models for structural design and analysis were proposed for CGCPFTs. For the analytical model, based on the available experimental data, a prediction method for the stress–strain behavior of the gangue aggregate concrete in CGCPFTs, which is confined only by FRP and partly confined by both FRP and the steel tubes, was first proposed. Additionally, the condition for the synergetic deformation of the two confined states of gangue aggregate concrete within the CGCPFT was proposed. Based on the condition, an iterative incremental process was developed which subsequently allows for the theoretical calculation of the load–displacement curve for the CGCPFT under monotonic axial compression. For the design model, by introducing the constraint contribution coefficient of the steel tube, the existing closed-loop calculation formula for the stress–strain relationship of FRP-confined concrete was revised. Furthermore, by expressing the axial and lateral stresses of the steel tube as a unified circumferential effect on the concrete, the calculation methods for the ultimate strength and strain in the closed-loop formula were redefined, thus achieving the prediction of the stress–strain behavior of CGCPFTs. The comparison with the test data obtained by the author and their team revealed that both the analysis and design models could provide accurate predictions. |
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Datenseite - Reference-ID
10804485 - Veröffentlicht am:
10.11.2024 - Geändert am:
10.11.2024