Steel and Composite Structures

  • 제30권2호
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  • Pages.185-199
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  • 2019
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  • 1229-9367(pISSN)
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  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Stability study on tenon-connected SHS and CFST columns in modular construction

  • Chen, Yisu (School of Civil Engineering, The University of Sydney) ;
  • Hou, Chao (School of Civil Engineering, The University of Sydney) ;
  • Peng, Jiahao (School of Civil Engineering, The University of Sydney)
  • 투고 : 2018.09.11
  • 심사 : 2019.01.23
  • 발행 : 2019.01.25
⟨ 이전 논문 다음 논문 ⟩

초록

Modular construction is an emerging technology to accommodate the increasing restrictions in terms of construction period, energy efficiency and environmental impacts, since each structural module is prefabricated offsite beforehand and assembled onsite using industrialized techniques. However, some innate structural drawbacks of this innovative method are also distinct, such as connection tying inaccessibility, column instability and system robustness. This study aims to explore the theoretical and numerical stability analysis of a tenon-connected square hollow section (SHS) steel column to address the tying and stability issue in modular construction. Due to the excellent performance of composite structures in fire resistance and buckling prevention, concrete-filled steel tube (CFST) columns are also taken into account in the analysis to evaluate the feasibility of adopting composite sections in modular buildings. Characteristic equations with three variables, i.e., the length ratio, the bending stiffness ratio and the rotational stiffness ratio, are generated from the fourth-order governing differential equations. The rotational stiffness ratio is recognized as the most significant factor, with interval analysis conducted for its mechanical significance and domain. Numerical analysis using ABAQUS is conducted for validation of characteristic equations. Recommendations and instructions in predicting the buckling performance of both SHS and CFST columns are then proposed.

키워드

과제정보

연구 과제 주관 기관 : The University of Sydney

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피인용 문헌

  1. Ultimate axial capacity prediction of CCFST columns using hybrid intelligence models - a new approach vol.40, pp.3, 2021, https://doi.org/10.12989/scs.2021.40.3.461