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  5. System reliability-based design of composite frames with concrete – filled steel plate shear walls

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Article
en
2024

System reliability-based design of composite frames with concrete – filled steel plate shear walls

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0 Files

en
2024
Vol 64
Vol. 64
DOI: 10.1016/j.istruc.2024.106576

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Huu Tai Thai
Huu Tai Thai

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Hau Tran
Huu Tai Thai
Brian Uy

Abstract

Nowadays, many high-rise buildings are constructed from concrete-filled steel tubular (CFST) columns and concrete-filled steel plate (CFSP) shear walls due to their superior merits. However, these composite buildings are still designed by traditional load and resistance factor design (LRFD) approach which is conservative and impossible to explicitly capture the complex behaviour of CFST structures. Hence, this paper develops an efficient framework for the system design of CFST structures utilizing nonlinear simulation and reliability analysis. Firstly, a C+ + source code for a new material model is developed in OpenSees to capture the behaviour of semi-rigid connections. This material is implemented into the numerical model of CFST structures. Secondly, a framework based on subset simulation is developed for the reliability analysis. This code rigorously considers uncertainties of variables such as numerical model, geometric and material properties or applied loads of both American (US) and Australian (AS) standards. Finally, case study and parametric study are conducted by using the developed framework to propose resistance reduction factors for the investigated frames. The results of the study show that the resistance reduction factor can be taken as 0.8 for both AS and US codes. This proposed factor can be a great source of reference for the system design of CFST buildings with composite shear walls.

How to cite this publication

Hau Tran, Huu Tai Thai, Brian Uy (2024). System reliability-based design of composite frames with concrete – filled steel plate shear walls. , 64, DOI: https://doi.org/10.1016/j.istruc.2024.106576.

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Publication Details

Type

Article

Year

2024

Authors

3

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1016/j.istruc.2024.106576

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